Birkholz, Adam B; Schlegel, H Bernhard
2015-12-28
The development of algorithms to optimize reaction pathways between reactants and products is an active area of study. Existing algorithms typically describe the path as a discrete series of images (chain of states) which are moved downhill toward the path, using various reparameterization schemes, constraints, or fictitious forces to maintain a uniform description of the reaction path. The Variational Reaction Coordinate (VRC) method is a novel approach that finds the reaction path by minimizing the variational reaction energy (VRE) of Quapp and Bofill. The VRE is the line integral of the gradient norm along a path between reactants and products and minimization of VRE has been shown to yield the steepest descent reaction path. In the VRC method, we represent the reaction path by a linear expansion in a set of continuous basis functions and find the optimized path by minimizing the VRE with respect to the linear expansion coefficients. Improved convergence is obtained by applying constraints to the spacing of the basis functions and coupling the minimization of the VRE to the minimization of one or more points along the path that correspond to intermediates and transition states. The VRC method is demonstrated by optimizing the reaction path for the Müller-Brown surface and by finding a reaction path passing through 5 transition states and 4 intermediates for a 10 atom Lennard-Jones cluster.
On the Reaction Path Hamiltonian
孙家钟; 李泽生
1994-01-01
A vector-fiber bundle structure of the reaction path Hamiltonian, which has been introduced by Miller, Handy and Adams, is explored with respect to molecular vibrations orthogonal to the reaction path. The symmetry of the fiber bundle is characterized by the real orthogonal group O(3N- 7) for the dynamical system with N atoms. Under the action of group O(3N- 7). the kinetic energy of the reaction path Hamiltonian is left invariant. Furthermore , the invariant behaviour of the Hamiltonian vector fields is investigated.
The Shortest Path with Intelligent Algorithm
Surachai Panich
2010-01-01
Full Text Available Problem statement: Path planning algorithms need to be developed and implemented in a suitable manner to give better understanding about the intelligent system and also stimulates technological supply to enormous demands in an intelligent vehicle industry. Approach: This study concerned with intelligent path planning using A* search algorithm. Results: This study introduced intelligent path planning with A* search algorithm, which use to generate the most efficient path to goal. The algorithm was tested on simulator. Conclusion: This study is an implementation of a path planning for an intelligent path planning. The implementations are tested and verified with the simulation software. The path planning algorithms were selected for the implementation and to verify them.
Quantum Adiabatic Evolution Algorithms with Different Paths
Farhi, E; Gutmann, S; Farhi, Edward; Goldstone, Jeffrey; Gutmann, Sam
2002-01-01
In quantum adiabatic evolution algorithms, the quantum computer follows the ground state of a slowly varying Hamiltonian. The ground state of the initial Hamiltonian is easy to construct; the ground state of the final Hamiltonian encodes the solution of the computational problem. These algorithms have generally been studied in the case where the "straight line" path from initial to final Hamiltonian is taken. But there is no reason not to try paths involving terms that are not linear combinations of the initial and final Hamiltonians. We give several proposals for randomly generating new paths. Using one of these proposals, we convert an algorithmic failure into a success.
Reaction path synthesis methodology for waste minimization
HU; Shanying; LI; Mingheng; LI; Yourun; SHEN; Jingzhu; LIU
2004-01-01
It is a key step for reducing waste generation in chemical processes to design optimal reaction paths. In this paper, methods of waste minimization for reaction path synthesis problems are proposed to realize eco-industrial production mode with minimum waste emission. A new conception of simple stoichiometric reaction is presented for reaction path synthesis problem. All simple stoichiometric reactions can be obtained by mathematical transformation for atom matrix of a reaction system. Based on the conception, a two-tier optimization method for complex reaction path synthesis problems is addressed. The first step is to determine the economic optimal overall reactions, and the second step to decompose each overall reaction into several sub-reactions and find out the best thermodynamic feasible reaction path. Further, a method of reaction path synthesis with waste closed-cycle is proposed based on simple stoichiometric reactions for achieving zero waste emission to poly-generation problem of multi-products. Case studies show that the proposed methods can efficiently solve practical reaction path synthesis problems.
Robot path planning using genetic algorithms
无
2001-01-01
Presents a strategy for soccer robot path planning using genetic algorithms for which, real number coding method is used, to overcome the defects of binary coding method, and the double crossover operation a dopted, to avoid the common defect of early convergence and converge faster than the standard genetic algo rithms concludes from simulation results that the method is effective for robot path planning.
Dynamic Shortest Path Algorithms for Hypergraphs
2012-01-01
Performance comparison of algorithms for the dynamic shortest path problem,” IEICE Transactions on Fundamentals of Electronics , Communications and...computation,” IEEE/ACM Transactions on Networking, vol. 8, no. 6, pp. 734–746, 2000. [8] G. Ramalingam and T. Reps, “An incremental algorithm for a...multihop performance,” IEEE Transactions on Mobile Computing, pp. 337–348, 2003. [17] S. Chachulski, M. Jennings, S. Katti, and D. Katabli, “Trading
Stochastic Evolutionary Algorithms for Planning Robot Paths
Fink, Wolfgang; Aghazarian, Hrand; Huntsberger, Terrance; Terrile, Richard
2006-01-01
A computer program implements stochastic evolutionary algorithms for planning and optimizing collision-free paths for robots and their jointed limbs. Stochastic evolutionary algorithms can be made to produce acceptably close approximations to exact, optimal solutions for path-planning problems while often demanding much less computation than do exhaustive-search and deterministic inverse-kinematics algorithms that have been used previously for this purpose. Hence, the present software is better suited for application aboard robots having limited computing capabilities (see figure). The stochastic aspect lies in the use of simulated annealing to (1) prevent trapping of an optimization algorithm in local minima of an energy-like error measure by which the fitness of a trial solution is evaluated while (2) ensuring that the entire multidimensional configuration and parameter space of the path-planning problem is sampled efficiently with respect to both robot joint angles and computation time. Simulated annealing is an established technique for avoiding local minima in multidimensional optimization problems, but has not, until now, been applied to planning collision-free robot paths by use of low-power computers.
A Path Algorithm for Constrained Estimation.
Zhou, Hua; Lange, Kenneth
2013-01-01
Many least-square problems involve affine equality and inequality constraints. Although there are a variety of methods for solving such problems, most statisticians find constrained estimation challenging. The current article proposes a new path-following algorithm for quadratic programming that replaces hard constraints by what are called exact penalties. Similar penalties arise in l1 regularization in model selection. In the regularization setting, penalties encapsulate prior knowledge, and penalized parameter estimates represent a trade-off between the observed data and the prior knowledge. Classical penalty methods of optimization, such as the quadratic penalty method, solve a sequence of unconstrained problems that put greater and greater stress on meeting the constraints. In the limit as the penalty constant tends to ∞, one recovers the constrained solution. In the exact penalty method, squared penalties!are replaced by absolute value penalties, and the solution is recovered for a finite value of the penalty constant. The exact path-following method starts at the unconstrained solution and follows the solution path as the penalty constant increases. In the process, the solution path hits, slides along, and exits from the various constraints. Path following in Lasso penalized regression, in contrast, starts with a large value of the penalty constant and works its way downward. In both settings, inspection of the entire solution path is revealing. Just as with the Lasso and generalized Lasso, it is possible to plot the effective degrees of freedom along the solution path. For a strictly convex quadratic program, the exact penalty algorithm can be framed entirely in terms of the sweep operator of regression analysis. A few well-chosen examples illustrate the mechanics and potential of path following. This article has supplementary materials available online.
Robot path planning using a genetic algorithm
Cleghorn, Timothy F.; Baffes, Paul T.; Wang, Liu
1988-01-01
Robot path planning can refer either to a mobile vehicle such as a Mars Rover, or to an end effector on an arm moving through a cluttered workspace. In both instances there may exist many solutions, some of which are better than others, either in terms of distance traversed, energy expended, or joint angle or reach capabilities. A path planning program has been developed based upon a genetic algorithm. This program assumes global knowledge of the terrain or workspace, and provides a family of good paths between the initial and final points. Initially, a set of valid random paths are constructed. Successive generations of valid paths are obtained using one of several possible reproduction strategies similar to those found in biological communities. A fitness function is defined to describe the goodness of the path, in this case including length, slope, and obstacle avoidance considerations. It was found that with some reproduction strategies, the average value of the fitness function improved for successive generations, and that by saving the best paths of each generation, one could quite rapidly obtain a collection of good candidate solutions.
Adaptive path planning: Algorithm and analysis
Chen, Pang C.
1995-03-01
To address the need for a fast path planner, we present a learning algorithm that improves path planning by using past experience to enhance future performance. The algorithm relies on an existing path planner to provide solutions difficult tasks. From these solutions, an evolving sparse work of useful robot configurations is learned to support faster planning. More generally, the algorithm provides a framework in which a slow but effective planner may be improved both cost-wise and capability-wise by a faster but less effective planner coupled with experience. We analyze algorithm by formalizing the concept of improvability and deriving conditions under which a planner can be improved within the framework. The analysis is based on two stochastic models, one pessimistic (on task complexity), the other randomized (on experience utility). Using these models, we derive quantitative bounds to predict the learning behavior. We use these estimation tools to characterize the situations in which the algorithm is useful and to provide bounds on the training time. In particular, we show how to predict the maximum achievable speedup. Additionally, our analysis techniques are elementary and should be useful for studying other types of probabilistic learning as well.
Adaptive path planning: Algorithm and analysis
Chen, Pang C.
1993-03-01
Path planning has to be fast to support real-time robot programming. Unfortunately, current planning techniques are still too slow to be effective, as they often require several minutes, if not hours of computation. To alleviate this problem, we present a learning algorithm that uses past experience to enhance future performance. The algorithm relies on an existing path planner to provide solutions to difficult tasks. From these solutions, an evolving sparse network of useful subgoals is learned to support faster planning. The algorithm is suitable for both stationary and incrementally-changing environments. To analyze our algorithm, we use a previously developed stochastic model that quantifies experience utility. Using this model, we characterize the situations in which the adaptive planner is useful, and provide quantitative bounds to predict its behavior. The results are demonstrated with problems in manipulator planning. Our algorithm and analysis are sufficiently general that they may also be applied to task planning or other planning domains in which experience is useful.
An Adaptive Path Planning Algorithm for Cooperating Unmanned Air Vehicles
Cunningham, C.T.; Roberts, R.S.
2000-09-12
An adaptive path planning algorithm is presented for cooperating Unmanned Air Vehicles (UAVs) that are used to deploy and operate land-based sensor networks. The algorithm employs a global cost function to generate paths for the UAVs, and adapts the paths to exceptions that might occur. Examples are provided of the paths and adaptation.
Analyzing Complex Reaction Mechanisms Using Path Sampling.
van Erp, Titus S; Moqadam, Mahmoud; Riccardi, Enrico; Lervik, Anders
2016-11-08
We introduce an approach to analyze collective variables (CVs) regarding their predictive power for a reaction. The method is based on already available path sampling data produced by, for instance, transition interface sampling or forward flux sampling, which are path sampling methods used for efficient computation of reaction rates. By a search in CV space, a measure of predictiveness can be optimized and, in addition, the number of CVs can be reduced using projection operations which keep this measure invariant. The approach allows testing hypotheses on the reaction mechanism but could, in principle, also be used to construct the phase-space committor surfaces without the need of additional trajectory sampling. The procedure is illustrated for a one-dimensional double-well potential, a theoretical model for an ion-transfer reaction in which the solvent structure can lower the barrier, and an ab initio molecular dynamics study of water auto-ionization. The analysis technique enhances the quantitative interpretation of path sampling data which can provide clues on how chemical reactions can be steered in desired directions.
Global path planning of mobile robots using a memetic algorithm
Zhu, Zexuan; Wang, Fangxiao; He, Shan; Sun, Yiwen
2015-08-01
In this paper, a memetic algorithm for global path planning (MAGPP) of mobile robots is proposed. MAGPP is a synergy of genetic algorithm (GA) based global path planning and a local path refinement. Particularly, candidate path solutions are represented as GA individuals and evolved with evolutionary operators. In each GA generation, the local path refinement is applied to the GA individuals to rectify and improve the paths encoded. MAGPP is characterised by a flexible path encoding scheme, which is introduced to encode the obstacles bypassed by a path. Both path length and smoothness are considered as fitness evaluation criteria. MAGPP is tested on simulated maps and compared with other counterpart algorithms. The experimental results demonstrate the efficiency of MAGPP and it is shown to obtain better solutions than the other compared algorithms.
Mobile robot dynamic path planning based on improved genetic algorithm
Wang, Yong; Zhou, Heng; Wang, Ying
2017-08-01
In dynamic unknown environment, the dynamic path planning of mobile robots is a difficult problem. In this paper, a dynamic path planning method based on genetic algorithm is proposed, and a reward value model is designed to estimate the probability of dynamic obstacles on the path, and the reward value function is applied to the genetic algorithm. Unique coding techniques reduce the computational complexity of the algorithm. The fitness function of the genetic algorithm fully considers three factors: the security of the path, the shortest distance of the path and the reward value of the path. The simulation results show that the proposed genetic algorithm is efficient in all kinds of complex dynamic environments.
Research on the ant colony algorithm in robot path planning
Wang, Yong; Ma, Jianming; Wang, Ying
2017-05-01
Using the A* algorithm principle proposed adaptive adjustment heuristic function, to reduce the degree of divergence algorithm; The state transition of the next ant improvement strategies, to improve the diversity of path planning solution; Control the change of the pheromone, to avoid algorithm trapped in local optimal solution; The improved ant colony algorithm makes the robot along an optimal or suboptimal path to arrive at the target.
Optimal Path Planning for Mobile Robot Using Tailored Genetic Algorithm
Dong Xiao Xian
2013-07-01
Full Text Available During routine inspecting, mobile robot may be requested to visit multiple locations to execute special tasks occasionally. This study aims at optimal path planning for multiple goals visiting task based on tailored genetic algorithm. The proposed algorithm will generate an optimal path that has the least idle time, which is proven to be more effective on evaluating a path in our previous work. In proposed algorithm, customized chromosome representing a path and genetic operators including repair and cut are developed and implemented. Afterwards, simulations are carried out to verify the effectiveness and applicability. Finally, analysis of simulation results is conducted and future work is addressed.
NONMONOTONE PRECONDITIONAL CURVILINEAR PATH ALGORITHMS FOR UNCONSTRAINED OPTIMIZATION
朱德通
2003-01-01
This paper presents nonmonotonic quasi-Newton algorithms via two pre-conditional curvilinear paths, the preconditional modified gradient path and the precon-ditional optimal path, for unconstrained optimization problem. We employ the stableBunch-Parlett factorization method to form two curvilinear paths very easily. Thenonmonotone criterion is used to speed up the convergence progress in the contoursof objective function with large curvature. Theoretical analyses are given which provethat the proposed algorithms are globally convergent and have a local superlinear con-vergence rate under some reasonable conditions. The results of numerical experimentsare reported to show the effectiveness of the proposed algorithms.
Performance analysis of FXLMS algorithm with secondary path modeling error
SUN Xu; CHEN Duanshi
2003-01-01
Performance analysis of filtered-X LMS (FXLMS) algorithm with secondary path modeling error is carried out in both time and frequency domain. It is shown firstly that the effects of secondary path modeling error on the performance of FXLMS algorithm are determined by the distribution of the relative error of secondary path model along with frequency.In case of that the distribution of relative error is uniform the modeling error of secondary path will have no effects on the performance of the algorithm. In addition, a limitation property of FXLMS algorithm is proved, which implies that the negative effects of secondary path modeling error can be compensated by increasing the adaptive filter length. At last, some insights into the "spillover" phenomenon of FXLMS algorithm are given.
A TRANSFORMATION PATH ALGORITHM FOR UNCONSTRAINED SIGNOMIAL GEOMETRIC PROGRAMMING
王燕军; 张可村
2004-01-01
In this paper we present a transformation path algorithm for Unconstrained Signomial Geometric Programming (USGP). The algorithm is proposed from a new point of view based on exploring the characteristics of USGP problem. Firstly by some stable transformations, a particular subproblem is derived which is very easy to solve.Secondly, a special path is formed conveniently. And then the step of the algorithm consists in finding a "good" point to the current iterate by choosing it along the special path and within a trust region. It is proved that the algorithm is globally convergent.
Global path planning approach based on ant colony optimization algorithm
WEN Zhi-qiang; CAI Zi-xing
2006-01-01
Ant colony optimization (ACO) algorithm was modified to optimize the global path. In order to simulate the real ant colonies, according to the foraging behavior of ant colonies and the characteristic of food, conceptions of neighboring area and smell area were presented. The former can ensure the diversity of paths and the latter ensures that each ant can reach the goal. Then the whole path was divided into three parts and ACO was used to search the second part path. When the three parts pathes were adjusted,the final path was found. The valid path and invalid path were defined to ensure the path valid. Finally, the strategies of the pheromone search were applied to search the optimum path. However, when only the pheromone was used to search the optimum path, ACO converges easily. In order to avoid this premature convergence, combining pheromone search and random search, a hybrid ant colony algorithm(HACO) was used to find the optimum path. The comparison between ACO and HACO shows that HACO can be used to find the shortest path.
Approximation algorithms for curvature-constrained shortest paths
Wang, Hongyan; Agarwal, P.K. [Duke Univ., Durham, NC (United States)
1996-12-31
Let B be a point robot in the plane, whose path is constrained to have curvature of at most 1, and let {Omega} be a set of polygonal obstacles with n vertices. We study the collision-free, optimal path-planning problem for B. Given a parameter {epsilon}, we present an O((n{sup 2}/{epsilon}{sup 2}) log n)-time algorithm for computing a collision-free, curvature-constrained path between two given positions, whose length is at most (1 + {epsilon}) times the length of an optimal robust path (a path is robust if it remains collision-free even if certain positions on the path are perturbed). Our algorithm thus runs significantly faster than the previously best known algorithm by Jacobs and Canny whose running time is O((n+L/{epsilon}){sup 2} + n{sup 2} (n+1/{epsilon}) log n), where L is the total edge length of the obstacles. More importantly, the running time of our algorithm does not depend on the size of obstacles. The path returned by this algorithm is not necessarily robust. We present an O((n/{epsilon}){sup 2.5} log n)-time algorithm that returns a robust path whose length is at most (1 + {epsilon}) times the length of an optimal robust path. We also give a stronger characterization of curvature-constrained shortest paths, which, apart from being crucial for our algorithm, is interesting in its own right. Roughly speaking, we prove that, except in some special cases, a shortest path touches obstacles only at points that have a visible vertex nearby.
Experiments with the auction algorithm for the shortest path problem
Larsen, Jesper; Pedersen, Ib
1999-01-01
The auction approach for the shortest path problem (SPP) as introduced by Bertsekas is tested experimentally. Parallel algorithms using the auction approach are developed and tested. Both the sequential and parallel auction algorithms perform significantly worse than a state-of-the-art Dijkstra......-like reference algorithm. Experiments are run on a distributed-memory MIMD class Meiko parallel computer....
A Global Path Planning Algorithm Based on Bidirectional SVGA
Taizhi Lv
2017-01-01
Full Text Available For path planning algorithms based on visibility graph, constructing a visibility graph is very time-consuming. To reduce the computing time of visibility graph construction, this paper proposes a novel global path planning algorithm, bidirectional SVGA (simultaneous visibility graph construction and path optimization by A⁎. This algorithm does not construct a visibility graph before the path optimization. However it constructs a visibility graph and searches for an optimal path at the same time. At each step, a node with the lowest estimation cost is selected to be expanded. According to the status of this node, different through lines are drawn. If this line is free-collision, it is added to the visibility graph. If not, some vertices of obstacles which are passed through by this line are added to the OPEN list for expansion. In the SVGA process, only a few visible edges which are in relation to the optimal path are drawn and the most visible edges are ignored. For taking advantage of multicore processors, this algorithm performs SVGA in parallel from both directions. By SVGA and parallel performance, this algorithm reduces the computing time and space. Simulation experiment results in different environments show that the proposed algorithm improves the time and space efficiency of path planning.
PCB Drill Path Optimization by Combinatorial Cuckoo Search Algorithm
Wei Chen Esmonde Lim
2014-01-01
Full Text Available Optimization of drill path can lead to significant reduction in machining time which directly improves productivity of manufacturing systems. In a batch production of a large number of items to be drilled such as printed circuit boards (PCB, the travel time of the drilling device is a significant portion of the overall manufacturing process. To increase PCB manufacturing productivity and to reduce production costs, a good option is to minimize the drill path route using an optimization algorithm. This paper reports a combinatorial cuckoo search algorithm for solving drill path optimization problem. The performance of the proposed algorithm is tested and verified with three case studies from the literature. The computational experience conducted in this research indicates that the proposed algorithm is capable of efficiently finding the optimal path for PCB holes drilling process.
PCB drill path optimization by combinatorial cuckoo search algorithm.
Lim, Wei Chen Esmonde; Kanagaraj, G; Ponnambalam, S G
2014-01-01
Optimization of drill path can lead to significant reduction in machining time which directly improves productivity of manufacturing systems. In a batch production of a large number of items to be drilled such as printed circuit boards (PCB), the travel time of the drilling device is a significant portion of the overall manufacturing process. To increase PCB manufacturing productivity and to reduce production costs, a good option is to minimize the drill path route using an optimization algorithm. This paper reports a combinatorial cuckoo search algorithm for solving drill path optimization problem. The performance of the proposed algorithm is tested and verified with three case studies from the literature. The computational experience conducted in this research indicates that the proposed algorithm is capable of efficiently finding the optimal path for PCB holes drilling process.
Path-tracking Algorithm for Aircraft Fuel Tank Inspection Robots
Niu Guochen; Wang Li; Gao Qingji; Hu Dandan
2014-01-01
A 3D path-tracking algorithm based on end- point approximation is proposed to implement the path traversal of robots designed to inspect aircraft fuel tanks. Kinematic models of single-joint segments and multiple- joint segments were created. First, each joint segment of the path was divided into many equal sections and the rotation angle was computed. The rotation angle was found for the plane determined by one divided point and the secondary terminal joint segment. Second, the shortest dist...
Calculating Graph Algorithms for Dominance and Shortest Path
Sergey, Ilya; Midtgaard, Jan; Clarke, Dave
2012-01-01
We calculate two iterative, polynomial-time graph algorithms from the literature: a dominance algorithm and an algorithm for the single-source shortest path problem. Both algorithms are calculated directly from the definition of the properties by fixed-point fusion of (1) a least fixed point expr...... of program calculation with common practice from the school of static program analysis, and build a novel view on iterative graph algorithms as instances of abstract interpretation...... expressing all finite paths through a directed graph and (2) Galois connections that capture dominance and path length. The approach illustrates that reasoning in the style of fixed-point calculus extends gracefully to the domain of graph algorithms. We thereby bridge common practice from the school......We calculate two iterative, polynomial-time graph algorithms from the literature: a dominance algorithm and an algorithm for the single-source shortest path problem. Both algorithms are calculated directly from the definition of the properties by fixed-point fusion of (1) a least fixed point...
Drilling Path Optimization Based on Particle Swarm Optimization Algorithm
ZHU Guangyu; ZHANG Weibo; DU Yuexiang
2006-01-01
This paper presents a new approach based on the particle swarm optimization (PSO) algorithm for solving the drilling path optimization problem belonging to discrete space. Because the standard PSO algorithm is not guaranteed to be global convergence or local convergence, based on the mathematical algorithm model, the algorithm is improved by adopting the method of generate the stop evolution particle over again to get the ability of convergence to the global optimization solution. And the operators are improved by establishing the duality transposition method and the handle manner for the elements of the operator, the improved operator can satisfy the need of integer coding in drilling path optimization. The experiment with small node numbers indicates that the improved algorithm has the characteristics of easy realize, fast convergence speed, and better global convergence characteristics, hence the new PSO can play a role in solving the problem of drilling path optimization in drilling holes.
A path following algorithm for mobile robots
Bakker, T.; Asselt, van C.J.; Bontsema, J.; Müller, J.; Straten, van G.
2010-01-01
This paper considers path following control for a robotic platform. The vehicle used for the experiments is a specially designed robotic platform for performing autonomous weed control. The platform is four-wheel steered and four-wheel driven. A diesel engine powers the wheels via a hydraulic transm
A path following algorithm for mobile robots
Bakker, T.; Asselt, van C.J.; Bontsema, J.; Müller, J.; Straten, van G.
2010-01-01
This paper considers path following control for a robotic platform. The vehicle used for the experiments is a specially designed robotic platform for performing autonomous weed control. The platform is four-wheel steered and four-wheel driven. A diesel engine powers the wheels via a hydraulic
Threat Modeling-Oriented Attack Path Evaluating Algorithm
LI Xiaohong; LIU Ran; FENG Zhiyong; HE Ke
2009-01-01
In order to evaluate all attack paths in a threat tree,based on threat modeling theory,a weight distribution algorithm of the root node in a threat tree is designed,which computes threat coefficients of leaf nodes in two ways including threat occurring possibility and the degree of damage.Besides,an algorithm of searching attack path was also obtained in accordence with its definition.Finally,an attack path evaluation system was implemented which can output the threat coefficients of the leaf nodes in a target threat tree,the weight distribution information,and the attack paths.An example threat tree is given to verify the effectiveness of the algorithms.
An Improved Physarum polycephalum Algorithm for the Shortest Path Problem
Xiaoge Zhang
2014-01-01
Full Text Available Shortest path is among classical problems of computer science. The problems are solved by hundreds of algorithms, silicon computing architectures and novel substrate, unconventional, computing devices. Acellular slime mould P. polycephalum is originally famous as a computing biological substrate due to its alleged ability to approximate shortest path from its inoculation site to a source of nutrients. Several algorithms were designed based on properties of the slime mould. Many of the Physarum-inspired algorithms suffer from a low converge speed. To accelerate the search of a solution and reduce a number of iterations we combined an original model of Physarum-inspired path solver with a new a parameter, called energy. We undertook a series of computational experiments on approximating shortest paths in networks with different topologies, and number of nodes varying from 15 to 2000. We found that the improved Physarum algorithm matches well with existing Physarum-inspired approaches yet outperforms them in number of iterations executed and a total running time. We also compare our algorithm with other existing algorithms, including the ant colony optimization algorithm and Dijkstra algorithm.
An improved Physarum polycephalum algorithm for the shortest path problem.
Zhang, Xiaoge; Wang, Qing; Adamatzky, Andrew; Chan, Felix T S; Mahadevan, Sankaran; Deng, Yong
2014-01-01
Shortest path is among classical problems of computer science. The problems are solved by hundreds of algorithms, silicon computing architectures and novel substrate, unconventional, computing devices. Acellular slime mould P. polycephalum is originally famous as a computing biological substrate due to its alleged ability to approximate shortest path from its inoculation site to a source of nutrients. Several algorithms were designed based on properties of the slime mould. Many of the Physarum-inspired algorithms suffer from a low converge speed. To accelerate the search of a solution and reduce a number of iterations we combined an original model of Physarum-inspired path solver with a new a parameter, called energy. We undertook a series of computational experiments on approximating shortest paths in networks with different topologies, and number of nodes varying from 15 to 2000. We found that the improved Physarum algorithm matches well with existing Physarum-inspired approaches yet outperforms them in number of iterations executed and a total running time. We also compare our algorithm with other existing algorithms, including the ant colony optimization algorithm and Dijkstra algorithm.
Optimal Path Selection for Mobile Robot Navigation Using Genetic Algorithm
D Tamilselvi
2011-07-01
Full Text Available The proposed Navigation Strategy using GA(Genetic Algorithm finds an optimal path in the simulated grid environment. GA forces to find a path that is connected to the robot start and target positions via predefined points. Each point in the environmental model is called genome and the path connecting Start and Target is called as Chromosome. According to the problem formulation, the length of the algorithm chromosomes (number of genomes is dynamic. Moreover every genome is not a simple digit. In this case, every genome represents the nodes in the 2D grid environment. After implementing the cross over and mutation concepts the resultant chromosome (path is subjected to optimization process which gives the optimal path as a result. The problem faced with is there may be chances for the loss of the fittest chromosome while performing the reproduction operations. The solution is achieved by inducing the concept of elitism thereby maintaining the population richness. The efficiency of the algorithm is analyzed with respect to execution time and path cost to reach the destination. Path planning, collision avoidance and obstacle avoidance are achieved in both static and dynamic environment.
无
2006-01-01
A novel method of global optimal path planning for mobile robot was proposed based on the improved Dijkstra algorithm and ant system algorithm. This method includes three steps: the first step is adopting the MAKLINK graph theory to establish the free space model of the mobile robot, the second step is adopting the improved Dijkstra algorithm to find out a sub-optimal collision-free path, and the third step is using the ant system algorithm to adjust and optimize the location of the sub-optimal path so as to generate the global optimal path for the mobile robot. The computer simulation experiment was carried out and the results show that this method is correct and effective. The comparison of the results confirms that the proposed method is better than the hybrid genetic algorithm in the global optimal path planning.
ROBIL: Robot Path Planning Based on PBIL Algorithm
Bo-Yeong Kang
2014-09-01
Full Text Available Genetic algorithm (GAs have attracted considerable interest for their usefulness in solving complex robot path planning problems. Specifically, researchers have combined conventional GAs with problem-specific operators and initialization techniques to find the shortest paths in a variety of robotic environments. Unfortunately, these approaches have exhibited inherently unstable performance, and they have tended to make other aspects of the problem-solving process (e.g., adjusting parameter sensitivities and creating high-quality initial populations unmanageable. As an alternative to conventional GAs, we propose a new population-based incremental learning (PBIL algorithm for robot path planning, a probabilistic model of nodes, and an edge bank for generating promising paths. Experimental results demonstrate the computational superiority of the proposed method over conventional GA approaches.
Efficient path sampling on multiple reaction channels
van Erp, Titus S.
2007-01-01
Due to the time scale problem, rare events are not accessible by straight forward molecular dynamics. The presence of multiple reaction channels complicates the problem even further. The feasibility of the standard free energy based methods relies strongly on the success in finding a proper reaction coordinate. This can be very difficult task in high-dimensional complex systems and even more if several distinct reaction channels exist. Moreover, even if a proper reaction coordinate can be fou...
Dynamic Shortest Path Algorithms for Hypergraphs
2014-01-01
hypergraphs, energy efficient routing in multichannel multiradio networks, and the Enron email data set. The experiment with the Enron email data set...efficient routing inmultichannel multiradio networks, and the Enron email data set. The experiment with the Enron email data set illustrates the application...FOR HYPERGRAPHS 3 of each actor. In Section VII, we apply the proposed shortest hy- perpath algorithms to the Enron e-mail data set. We propose a
A bi-criteria path planning algorithm for robotics applications
Clawson, Zachary; Ding, Xuchu; Englot, Brendan; Frewen, Thomas A.; Sisson, William M.; Vladimirsky, Alexander
2015-01-01
Realistic path planning applications often require optimizing with respect to several criteria simultaneously. Here we introduce an efficient algorithm for bi-criteria path planning on graphs. Our approach is based on augmenting the state space to keep track of the "budget" remaining to satisfy the constraints on secondary cost. The resulting augmented graph is acyclic and the primary cost can be then minimized by a simple upward sweep through budget levels. The efficiency and accuracy of our...
Self Avoiding Paths Routing Algorithm in Scale-Free Networks
Rachadi, Abdeljalil; Zahid, Noureddine
2013-01-01
In this paper, we present a new routing algorithm called "the Self Avoiding Paths Routing Algorithm". Its application to traffic flow in scale-free networks shows a great improvement over the so called "efficient routing" protocol while at the same time maintaining a relatively low average packet travel time. It has the advantage of minimizing path overlapping throughout the network in a self consistent manner with a relatively small number of iterations by maintaining an equilibrated path distribution especially among the hubs. This results in a significant shifting of the critical packet generation rate over which traffic congestion occurs, thus permitting the network to sustain more information packets in the free flow state. The performance of the algorithm is discussed both on a Bar\\'abasi-Albert (BA) network and real autonomous system (AS) network data.
Survey of Robot 3D Path Planning Algorithms
Liang Yang
2016-01-01
Full Text Available Robot 3D (three-dimension path planning targets for finding an optimal and collision-free path in a 3D workspace while taking into account kinematic constraints (including geometric, physical, and temporal constraints. The purpose of path planning, unlike motion planning which must be taken into consideration of dynamics, is to find a kinematically optimal path with the least time as well as model the environment completely. We discuss the fundamentals of these most successful robot 3D path planning algorithms which have been developed in recent years and concentrate on universally applicable algorithms which can be implemented in aerial robots, ground robots, and underwater robots. This paper classifies all the methods into five categories based on their exploring mechanisms and proposes a category, called multifusion based algorithms. For all these algorithms, they are analyzed from a time efficiency and implementable area perspective. Furthermore a comprehensive applicable analysis for each kind of method is presented after considering their merits and weaknesses.
Room Acoustical Simulation Algorithm Based on the Free Path Distribution
VORLÄNDER, M.
2000-04-01
A new algorithm is presented which provides estimates of impulse responses in rooms. It is applicable to arbitrary shaped rooms, thus including non-diffuse spaces like workrooms or offices. In the latter cases, for instance, sound propagation curves are of interest to be applied in noise control. In the case of concert halls and opera houses, the method enables very fast predictions of room acoustical criteria like reverberation time, strength or clarity. The method is based on a low-resolved ray tracing and recording of the free paths. Estimates of impulse responses are derived from evaluation of the free path distribution and of the free path transition probabilities.
The thermodynamic natural path in chemical reaction kinetics
Moishe garfinkle
2000-01-01
Full Text Available The Natural Path approach to chemical reaction kinetics was developed to bridge the considerable gap between the Mass Action mechanistic approach and the non-mechanistic irreversible thermodynamic approach. The Natural Path approach can correlate empirical kinetic data with a high degree precision, as least equal to that achievable by the Mass-Action rate equations, but without recourse mechanistic considerations. The reaction velocities arising from the particular rate equation chosen by kineticists to best represent the kinetic behavior of a chemical reaction are the natural outcome of the Natural Path approach. Moreover, by virtue of its thermodynamic roots, equilibrium thermodynamic functions can be extracted from reaction kinetic data with considerable accuracy. These results support the intrinsic validity of the Natural Path approach.
Reaction Path Optimization with Holonomic Constraints and Kinetic Energy Potentials.
Brokaw, Jason B; Haas, Kevin R; Chu, Jhih-Wei
2009-08-11
Two methods are developed to enhance the stability, efficiency, and robustness of reaction path optimization using a chain of replicas. First, distances between replicas are kept equal during path optimization via holonomic constraints. Finding a reaction path is, thus, transformed into a constrained optimization problem. This approach avoids force projections for finding minimum energy paths (MEPs), and fast-converging schemes such as quasi-Newton methods can be readily applied. Second, we define a new objective function - the total Hamiltonian - for reaction path optimization, by combining the kinetic energy potential of each replica with its potential energy function. Minimizing the total Hamiltonian of a chain determines a minimum Hamiltonian path (MHP). If the distances between replicas are kept equal and a consistent force constant is used, then the kinetic energy potentials of all replicas have the same value. The MHP in this case is the most probable isokinetic path. Our results indicate that low-temperature kinetic energy potentials (optimization and can significantly reduce the required steps of minimization by 2-3 times without causing noticeable differences between a MHP and MEP. These methods are applied to three test cases, the C7eq-to-Cax isomerization of an alanine dipeptide, the (4)C1-to-(1)C4 transition of an α-d-glucopyranose, and the helix-to-sheet transition of a GNNQQNY heptapeptide. By applying the methods developed in this work, convergence of reaction path optimization can be achieved for these complex transitions, involving full atomic details and a large number of replicas (>100). For the case of helix-to-sheet transition, we identify pathways whose energy barriers are consistent with experimental measurements. Further, we develop a method based on the work energy theorem to quantify the accuracy of reaction paths and to determine whether the atoms used to define a path are enough to provide quantitative estimation of energy barriers.
Mobile transporter path planning using a genetic algorithm approach
Baffes, Paul; Wang, Lui
1988-01-01
The use of an optimization technique known as a genetic algorithm for solving the mobile transporter path planning problem is investigated. The mobile transporter is a traveling robotic vehicle proposed for the Space Station which must be able to reach any point of the structure autonomously. Specific elements of the genetic algorithm are explored in both a theoretical and experimental sense. Recent developments in genetic algorithm theory are shown to be particularly effective in a path planning problem domain, though problem areas can be cited which require more research. However, trajectory planning problems are common in space systems and the genetic algorithm provides an attractive alternative to the classical techniques used to solve these problems.
Algorithm for Pocket Milling using Zig-zag Tool Path
P. Selvaraj
2006-04-01
Full Text Available Pocket-milling operations are widely used for scooping out materials during the machiningof aircraft components. This paper presents a tool-path planning algorithm for pocket-millingusing zig-zag method. The algorithm consists of basically three modules, viz., generating toolpathelements using pocket geometry entities as input, finding out intersection points (edgepoints, and rearranging points in a zig-zag fashion. OPTPATH algorithm1,2 is used for generatingtool-path elements. These elements thus generated are used to find out the intersection pointswith all entities. The valid points are arranged in a zig-zag way, which are used for machiningany pocket considered. This algorithm works satisfactorily for all the pocket boundaries havingline-line, line-arc, and arc-arc geometry entities.
Improving Christofides' Algorithm for the s-t Path TSP
An, Hyung-Chan; Shmoys, David B
2011-01-01
We present a deterministic (1+sqrt(5))/2-approximation algorithm for the s-t path TSP. Given a symmetric metric cost between n vertices including two prespecified endpoints, the problem is to find a shortest Hamiltonian path between the two endpoints; Hoogeveen showed that the natural variant of Christofides' algorithm is a 5/3-approximation algorithm for this problem, and this asymptotically tight bound in fact has been the best approximation ratio known until now. We modify this algorithm so that it chooses the initial spanning tree based on an optimal solution to the Held-Karp relaxation rather than a minimum spanning tree; we prove this simple but crucial modification leads to an improved approximation ratio, surpassing the 20-year-old barrier set by the natural Christofides' algorithm variant. Our algorithm also proves an upper bound of (1+sqrt(5))/2 on the integrality gap of the path-variant Held-Karp relaxation. The techniques devised in this paper can be applied to other optimization problems over s-t...
LP-Based Approximation Algorithms for Traveling Salesman Path Problems
An, Hyung-Chan
2011-01-01
We present a (5/3 - epsilon)-approximation algorithm for some constant epsilon>0 for the traveling salesman path problem under the unit-weight graphical metric, and prove an upper bound on the integrality gap of the path-variant Held-Karp relaxation both under this metric and the general metric. Given a complete graph with the metric cost and two designated endpoints in the graph, the traveling salesman path problem is to find a minimum Hamiltonian path between these two endpoints. The best previously known performance guarantee for this problem was 5/3 and was due to Hoogeveen. We give the first constant upper bound on the integrality gap of the path-variant Held-Karp relaxation, showing it to be at most 5/3 by providing a new analysis of Hoogeveen's algorithm. This analysis exhibits a well-characterized critical case, and we show that the recent result of Oveis Gharan, Saberi and Singh on the traveling salesman circuit problem under the unit-weight graphical metric can be modified for the path case to compl...
Path Planning with a Lazy Significant Edge Algorithm (LSEA
Joseph Polden
2013-04-01
Full Text Available Probabilistic methods have been proven to be effective for robotic path planning in a geometrically complex environment. In this paper, we propose a novel approach, which utilizes a specialized roadmap expansion phase, to improve lazy probabilistic path planning. This expansion phase analyses roadmap connectivity information to bias sampling towards objects in the workspace that have not yet been navigated by the robot. A new method to reduce the number of samples required to navigate narrow passages is also proposed and tested. Experimental results show that the new algorithm is more efficient than the traditional path planning methodologies. It was able to generate solutions for a variety of path planning problems faster, using fewer samples to arrive at a valid solution.
Nonlinear reaction coordinate analysis in the reweighted path ensemble
Lechner, W.; Rogal, J.; Juraszek, J.; Ensing, B.; Bolhuis, P.G.
2010-01-01
We present a flexible nonlinear reaction coordinate analysis method for the transition path ensemble based on the likelihood maximization approach developed by Peters and Trout [J. Chem. Phys. 125, 054108 (2006)] . By parametrizing the reaction coordinate by a string of images in a collective variab
Multiple object tracking using the shortest path faster association algorithm.
Xi, Zhenghao; Liu, Heping; Liu, Huaping; Yang, Bin
2014-01-01
To solve the persistently multiple object tracking in cluttered environments, this paper presents a novel tracking association approach based on the shortest path faster algorithm. First, the multiple object tracking is formulated as an integer programming problem of the flow network. Then we relax the integer programming to a standard linear programming problem. Therefore, the global optimum can be quickly obtained using the shortest path faster algorithm. The proposed method avoids the difficulties of integer programming, and it has a lower worst-case complexity than competing methods but better robustness and tracking accuracy in complex environments. Simulation results show that the proposed algorithm takes less time than other state-of-the-art methods and can operate in real time.
Multiple Object Tracking Using the Shortest Path Faster Association Algorithm
Zhenghao Xi
2014-01-01
Full Text Available To solve the persistently multiple object tracking in cluttered environments, this paper presents a novel tracking association approach based on the shortest path faster algorithm. First, the multiple object tracking is formulated as an integer programming problem of the flow network. Then we relax the integer programming to a standard linear programming problem. Therefore, the global optimum can be quickly obtained using the shortest path faster algorithm. The proposed method avoids the difficulties of integer programming, and it has a lower worst-case complexity than competing methods but better robustness and tracking accuracy in complex environments. Simulation results show that the proposed algorithm takes less time than other state-of-the-art methods and can operate in real time.
Ant Colony Based Path Planning Algorithm for Autonomous Robotic Vehicles
Yogita Gigras
2012-11-01
Full Text Available The requirement of an autonomous robotic vehicles demand highly efficient algorithm as well as software. Today’s advanced computer hardware technology does not provide these types of extensive processing capabilities, so there is still a major space and time limitation for the technologies that are available for autonomous robotic applications. Now days, small to miniature mobile robots are required for investigation, surveillance and hazardous material detection for military and industrial applications. But these small sized robots have limited power capacity as well as memory and processing resources. A number of algorithms exist for producing optimal path for dynamically cost. This paper presents a new ant colony based approach which is helpful in solving path planning problem for autonomous robotic application. The experiment of simulation verified its validity of algorithm in terms of time.
艾文宝; 张可村
2001-01-01
In this paper, we propose a general path following method, in which the starting point can be any feasible interior pair and each iteration uses a step with the largest possible reduction in duality gap. The algorithm maintains the O ( nL) ineration complexity. It enjoys quadratic convergence if the optimal vertex is nondegenerate.
A Bat Algorithm with Mutation for UCAV Path Planning
Gaige Wang
2012-01-01
Full Text Available Path planning for uninhabited combat air vehicle (UCAV is a complicated high dimension optimization problem, which mainly centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. Original bat algorithm (BA is used to solve the UCAV path planning problem. Furthermore, a new bat algorithm with mutation (BAM is proposed to solve the UCAV path planning problem, and a modification is applied to mutate between bats during the process of the new solutions updating. Then, the UCAV can find the safe path by connecting the chosen nodes of the coordinates while avoiding the threat areas and costing minimum fuel. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic BA. The realization procedure for original BA and this improved metaheuristic approach BAM is also presented. To prove the performance of this proposed metaheuristic method, BAM is compared with BA and other population-based optimization methods, such as ACO, BBO, DE, ES, GA, PBIL, PSO, and SGA. The experiment shows that the proposed approach is more effective and feasible in UCAV path planning than the other models.
A benchmark for reaction coordinates in the transition path ensemble.
Li, Wenjin; Ma, Ao
2016-04-01
The molecular mechanism of a reaction is embedded in its transition path ensemble, the complete collection of reactive trajectories. Utilizing the information in the transition path ensemble alone, we developed a novel metric, which we termed the emergent potential energy, for distinguishing reaction coordinates from the bath modes. The emergent potential energy can be understood as the average energy cost for making a displacement of a coordinate in the transition path ensemble. Where displacing a bath mode invokes essentially no cost, it costs significantly to move the reaction coordinate. Based on some general assumptions of the behaviors of reaction and bath coordinates in the transition path ensemble, we proved theoretically with statistical mechanics that the emergent potential energy could serve as a benchmark of reaction coordinates and demonstrated its effectiveness by applying it to a prototypical system of biomolecular dynamics. Using the emergent potential energy as guidance, we developed a committor-free and intuition-independent method for identifying reaction coordinates in complex systems. We expect this method to be applicable to a wide range of reaction processes in complex biomolecular systems.
Path Planning Algorithms for the Adaptive Sensor Fleet
Stoneking, Eric; Hosler, Jeff
2005-01-01
The Adaptive Sensor Fleet (ASF) is a general purpose fleet management and planning system being developed by NASA in coordination with NOAA. The current mission of ASF is to provide the capability for autonomous cooperative survey and sampling of dynamic oceanographic phenomena such as current systems and algae blooms. Each ASF vessel is a software model that represents a real world platform that carries a variety of sensors. The OASIS platform will provide the first physical vessel, outfitted with the systems and payloads necessary to execute the oceanographic observations described in this paper. The ASF architecture is being designed for extensibility to accommodate heterogenous fleet elements, and is not limited to using the OASIS platform to acquire data. This paper describes the path planning algorithms developed for the acquisition phase of a typical ASF task. Given a polygonal target region to be surveyed, the region is subdivided according to the number of vessels in the fleet. The subdivision algorithm seeks a solution in which all subregions have equal area and minimum mean radius. Once the subregions are defined, a dynamic programming method is used to find a minimum-time path for each vessel from its initial position to its assigned region. This path plan includes the effects of water currents as well as avoidance of known obstacles. A fleet-level planning algorithm then shuffles the individual vessel assignments to find the overall solution which puts all vessels in their assigned regions in the minimum time. This shuffle algorithm may be described as a process of elimination on the sorted list of permutations of a cost matrix. All these path planning algorithms are facilitated by discretizing the region of interest onto a hexagonal tiling.
The enzymatic reaction catalyzed by lactate dehydrogenase exhibits one dominant reaction path
Masterson, Jean E.; Schwartz, Steven D.
2014-10-01
Enzymes are the most efficient chemical catalysts known, but the exact nature of chemical barrier crossing in enzymes is not fully understood. Application of transition state theory to enzymatic reactions indicates that the rates of all possible reaction paths, weighted by their relative probabilities, must be considered in order to achieve an accurate calculation of the overall rate. Previous studies in our group have shown a single mechanism for enzymatic barrier passage in human heart lactate dehydrogenase (LDH). To ensure that this result was not due to our methodology insufficiently sampling reactive phase space, we implement high-perturbation transition path sampling in both microcanonical and canonical regimes for the reaction catalyzed by human heart LDH. We find that, although multiple, distinct paths through reactive phase space are possible for this enzymatic reaction, one specific reaction path is dominant. Since the frequency of these paths in a canonical ensemble is inversely proportional to the free energy barriers separating them from other regions of phase space, we conclude that the rarer reaction paths are likely to have a negligible contribution. Furthermore, the non-dominate reaction paths correspond to altered reactive conformations and only occur after multiple steps of high perturbation, suggesting that these paths may be the result of non-biologically significant changes to the structure of the enzymatic active site.
Path planning algorithms for assembly sequence planning. [in robot kinematics
Krishnan, S. S.; Sanderson, Arthur C.
1991-01-01
Planning for manipulation in complex environments often requires reasoning about the geometric and mechanical constraints which are posed by the task. In planning assembly operations, the automatic generation of operations sequences depends on the geometric feasibility of paths which permit parts to be joined into subassemblies. Feasible locations and collision-free paths must be present for part motions, robot and grasping motions, and fixtures. This paper describes an approach to reasoning about the feasibility of straight-line paths among three-dimensional polyhedral parts using an algebra of polyhedral cones. A second method recasts the feasibility conditions as constraints in a nonlinear optimization framework. Both algorithms have been implemented and results are presented.
Improved ant colony algorithm for global path planning
Li, Pengfei; Wang, Hongbo; Li, Xiaogang
2017-03-01
The ant colony algorithm has many advantages compared with other algorithms in path planning, but its shortcomings still cannot be ignored. For example, the convergence speed is very low at initial stage, it is easy to fall into the local optimal solution, and the solution speed is slow and so on. In order to solve these problems and reduce the search time, this paper firstly makes the assignment of the main parameters of α, β, M and ρ in the ant colony algorithm through a large number of experimental data analysis. Then an improved ant colony algorithm based on dynamic parameters and new pheromone updating mechanism is proposed in this paper. Simulation results show that the improved ant colony algorithm can not only greatly shorten the algorithm running time, but also has greater probability to get the global optimal solution, and the convergence rate of algorithm is better than traditional ant colony algorithm. It is very advantageous for solving large-scale optimization problems.
On Models of Nonlinear Evolution Paths in Adiabatic Quantum Algorithms
SUN Jie; LU Song-Feng; Samuel L.Braunstein
2013-01-01
In this paper,we study two different nonlinear interpolating paths in adiabatic evolution algorithms for solving a particular class of quantum search problems where both the initial and final Hamiltonian are one-dimensional projector Hamiltonians on the corresponding ground state.If the overlap between the initial state and final state of the quantum system is not equal to zero,both of these models can provide a constant time speedup over the usual adiabatic algorithms by increasing some another corresponding "complexity".But when the initial state has a zero overlap with the solution state in the problem,the second model leads to an infinite time complexity of the algorithm for whatever interpolating functions being applied while the first one can still provide a constant running time.However,inspired by a related reference,a variant of the first model can be constructed which also fails for the problem when the overlap is exactly equal to zero if we want to make up the "intrinsic" fault of the second model — an increase in energy.Two concrete theorems are given to serve as explanations why neither of these two models can improve the usual adiabatic evolution algorithms for the phenomenon above.These just tell us what should be noted when using certain nonlinear evolution paths in adiabatic quantum algorithms for some special kind of problems.
A Complete Critical Path Algorithm for Test Generation of Combinational Circuits
周权; 魏道政
1991-01-01
It is known that critical path test generation method is not a complete algorithm for combinational circuits with reconvergent-fanout.In order to made it a complete algorithm,we put forward a reconvergent-fanoutoriented technique,the principal critical path algorithm,propagating the critical value back to primary inputs along a single path,the principal critical path,and allowing multiple path sensitization if needed.Relationship among test patterns is also discussed to accelerate test generation.
Optimal Route Based Advanced Algorithm using Hot Link Split Multi-Path Routing Algorithm
Akhilesh A. Waoo
2014-07-01
Full Text Available Present research work describes advancement in standard routing protocol AODV for mobile ad-hoc networks. Our mechanism sets up multiple optimal paths with the criteria of bandwidth and delay to store multiple optimal paths in the network. At time of link failure, it will switch to next available path. We have used the information that we get in the RREQ packet and also send RREP packet to more than one path, to set up multiple paths, It reduces overhead of local route discovery at the time of link failure and because of this End to End Delay and Drop Ratio decreases. The main feature of our mechanism is its simplicity and improved efficiency. This evaluates through simulations the performance of the AODV routing protocol including our scheme and we compare it with HLSMPRA (Hot Link Split Multi-Path Routing Algorithm Algorithm. Indeed, our scheme reduces routing load of network, end to end delay, packet drop ratio, and route error sent. The simulations have been performed using network simulator OPNET. The network simulator OPNET is discrete event simulation software for network simulations which means it simulates events not only sending and receiving packets but also forwarding and dropping packets. This modified algorithm has improved efficiency, with more reliability than Previous Algorithm.
Exploring chemical reaction mechanisms through harmonic Fourier beads path optimization.
Khavrutskii, Ilja V; Smith, Jason B; Wallqvist, Anders
2013-10-28
Here, we apply the harmonic Fourier beads (HFB) path optimization method to study chemical reactions involving covalent bond breaking and forming on quantum mechanical (QM) and hybrid QM∕molecular mechanical (QM∕MM) potential energy surfaces. To improve efficiency of the path optimization on such computationally demanding potentials, we combined HFB with conjugate gradient (CG) optimization. The combined CG-HFB method was used to study two biologically relevant reactions, namely, L- to D-alanine amino acid inversion and alcohol acylation by amides. The optimized paths revealed several unexpected reaction steps in the gas phase. For example, on the B3LYP∕6-31G(d,p) potential, we found that alanine inversion proceeded via previously unknown intermediates, 2-iminopropane-1,1-diol and 3-amino-3-methyloxiran-2-ol. The CG-HFB method accurately located transition states, aiding in the interpretation of complex reaction mechanisms. Thus, on the B3LYP∕6-31G(d,p) potential, the gas phase activation barriers for the inversion and acylation reactions were 50.5 and 39.9 kcal∕mol, respectively. These barriers determine the spontaneous loss of amino acid chirality and cleavage of peptide bonds in proteins. We conclude that the combined CG-HFB method further advances QM and QM∕MM studies of reaction mechanisms.
A surface hopping algorithm for nonadiabatic minimum energy path calculations.
Schapiro, Igor; Roca-Sanjuán, Daniel; Lindh, Roland; Olivucci, Massimo
2015-02-15
The article introduces a robust algorithm for the computation of minimum energy paths transiting along regions of near-to or degeneracy of adiabatic states. The method facilitates studies of excited state reactivity involving weakly avoided crossings and conical intersections. Based on the analysis of the change in the multiconfigurational wave function the algorithm takes the decision whether the optimization should continue following the same electronic state or switch to a different state. This algorithm helps to overcome convergence difficulties near degeneracies. The implementation in the MOLCAS quantum chemistry package is discussed. To demonstrate the utility of the proposed procedure four examples of application are provided: thymine, asulam, 1,2-dioxetane, and a three-double-bond model of the 11-cis-retinal protonated Schiff base.
Multi-path planning algorithm based on fitness sharing and species evolution
ZHANG Jing-juan; LI Xue-lian; HAO Yan-ling
2003-01-01
A new algorithm is proposed for underwater vehicles multi-path planning. This algorithm is based on fitness sharing genetic algorithm, clustering and evolution of multiple populations, which can keep the diversity of the solution path, and decrease the operating time because of the independent evolution of each subpopulation. The multi-path planning algorithm is demonstrated by a number of two-dimensional path planning problems. The results show that the multi-path planning algorithm has the following characteristics: high searching capability, rapid convergence and high reliability.
Quantum Adiabatic Algorithms, Small Gaps, and Different Paths
Farhi, Edward; Gosset, David; Gutmann, Sam; Meyer, Harvey B; Shor, Peter
2011-01-01
We construct a set of instances of 3SAT which are not solved efficiently using the simplest quantum adiabatic algorithm. These instances are obtained by picking random clauses all consistent with two disparate planted solutions and then penalizing one of them with a single additional clause. We argue that by randomly modifying the beginning Hamiltonian, one obtains (with substantial probability) an adiabatic path that removes this difficulty. This suggests that the quantum adiabatic algorithm should in general be run on each instance with many different random paths leading to the problem Hamiltonian. We do not know whether this trick will help for a random instance of 3SAT (as opposed to an instance from the particular set we consider), especially if the instance has an exponential number of disparate assignments that violate few clauses. We use a continuous imaginary time Quantum Monte Carlo algorithm in a novel way to numerically investigate the ground state as well as the first excited state of our system...
Algorithm Plans Collision-Free Path for Robotic Manipulator
Backes, Paul; Diaz-Calderon, Antonio
2007-01-01
An algorithm has been developed to enable a computer aboard a robot to autonomously plan the path of the manipulator arm of the robot to avoid collisions between the arm and any obstacle, which could be another part of the robot or an external object in the vicinity of the robot. In simplified terms, the algorithm generates trial path segments and tests each segment for potential collisions in an iterative process that ends when a sequence of collision-free segments reaches from the starting point to the destination. The main advantage of this algorithm, relative to prior such algorithms, is computational efficiency: the algorithm is designed to make minimal demands upon the limited computational resources available aboard a robot. This path-planning algorithm utilizes a modified version of the collision-detection method described in "Improved Collision-Detection Method for Robotic Manipulator" (NPO-30356), NASA Tech Briefs, Vol. 27, No. 3 (June 2003), page 72. The method involves utilization of mathematical models of the robot constructed prior to operation and similar models of external objects constructed automatically from sensory data acquired during operation. This method incorporates a previously developed method, known in the art as the method of oriented bounding boxes (OBBs), in which an object is represented approximately, for computational purposes, by a box that encloses its outer boundary. Because many parts of a robotic manipulator are cylindrical, the OBB method has been extended in this method to enable the approximate representation of cylindrical parts by use of octagonal or other multiple-OBB assemblies denoted oriented bounding prisms (OBPs). A multiresolution OBB/OBP representation of the robot and its manipulator arm and a multiresolution OBB representation of external objects (including terrain) are constructed and used in a process in which collisions at successively finer resolutions are detected through computational detection of overlaps
Unified path integral approach to theories of diffusion-influenced reactions
Prüstel, Thorsten; Meier-Schellersheim, Martin
2017-08-01
Building on mathematical similarities between quantum mechanics and theories of diffusion-influenced reactions, we develop a general approach for computational modeling of diffusion-influenced reactions that is capable of capturing not only the classical Smoluchowski picture but also alternative theories, as is here exemplified by a volume reactivity model. In particular, we prove the path decomposition expansion of various Green's functions describing the irreversible and reversible reaction of an isolated pair of molecules. To this end, we exploit a connection between boundary value and interaction potential problems with δ - and δ'-function perturbation. We employ a known path-integral-based summation of a perturbation series to derive a number of exact identities relating propagators and survival probabilities satisfying different boundary conditions in a unified and systematic manner. Furthermore, we show how the path decomposition expansion represents the propagator as a product of three factors in the Laplace domain that correspond to quantities figuring prominently in stochastic spatially resolved simulation algorithms. This analysis will thus be useful for the interpretation of current and the design of future algorithms. Finally, we discuss the relation between the general approach and the theory of Brownian functionals and calculate the mean residence time for the case of irreversible and reversible reactions.
State Space Path Integrals for Electronically Nonadiabatic Reaction Rates
Duke, Jessica Ryan
2016-01-01
We present a state-space-based path integral method to calculate the rate of electron transfer (ET) in multi-state, multi-electron condensed-phase processes. We employ an exact path integral in discrete electronic states and continuous Cartesian nuclear variables to obtain a transition state theory (TST) estimate to the rate. A dynamic recrossing correction to the TST rate is then obtained from real-time dynamics simulations using mean field ring polymer molecular dynamics. We employ two different reaction coordinates in our simulations and show that, despite the use of mean field dynamics, the use of an accurate dividing surface to compute TST rates allows us to achieve remarkable agreement with Fermi's golden rule rates for nonadiabatic ET in the normal regime of Marcus theory. Further, we show that using a reaction coordinate based on electronic state populations allows us to capture the turnover in rates for ET in the Marcus inverted regime.
K. Kumaravel
2015-05-01
Full Text Available Wireless Mesh Network (WMN uses the latest technology which helps in providing end users a high quality service referred to as the Internet’s “last mile”. Also considering WMN one of the most important technologies that are employed is multicast communication. Among the several issues routing which is significantly an important issue is addressed by every WMN technologies and this is done during the process of data transmission. The IEEE 802.11s Standard entails and sets procedures which need to be followed to facilitate interconnection and thus be able to devise an appropriate WMN. There has been introduction of several protocols by many authors which are mainly devised on the basis of machine learning and artificial intelligence. Multi-path routing may be considered as one such routing method which facilitates transmission of data over several paths, proving its capabilities as a useful strategy for achieving reliability in WMN. Though, multi-path routing in any manner cannot really guarantee deterministic transmission. As here there are multiple paths available for enabling data transmission from source to destination node. The algorithm that had been employed before in the studies conducted did not take in to consideration routing metrics which include energy aware metrics that are used for path selection during transferring of data. The following study proposes use of the hybrid multipath routing algorithm while taking in to consideration routing metrics which include energy, minimal loss for efficient path selection and transferring of data. Proposed algorithm here has two phases. In the first phase prim’s algorithm has been proposed so that in networks route discovery may be possible. For the second one the Hybrid firefly algorithm which is based on harmony search has been employed for selection of the most suitable and best through proper analysis of metrics which include energy awareness and minimal loss for every path that has
A Constant Factor Approximation Algorithm for Unsplittable Flow on Paths
Bonsma, Paul; Wiese, Andreas
2011-01-01
We study the unsplittable flow problem on a path $P$. We are given a set of $n$ tasks. Each task is specified by a sub path of $P$, a demand, and a profit. Moreover, each edge of $P$ has a given capacity. The aim is to find a subset of the tasks with maximum profit, for which the given demands can be simultaneously routed along $P$, subject to the capacities. The best known polynomial time approximation algorithm for this problem achieves a performance ratio of $O(\\log n)$ and the best known hardness result is weak NP-hardness. In this paper, we firstly show that the problem is strongly NP-hard, even when the capacities are constant, and all demands are chosen from $\\{1,2,3\\}$. Secondly, we present the first polynomial time constant-factor approximation algorithm for this problem, achieving an approximation factor of $7+\\epsilon$ for any $\\epsilon>0$. This answers an open question from Bansal et al. (SODA'09). We employ a novel framework which reduces the problem to instances where the capacities of the edges...
Birkholz, Adam B; Schlegel, H Bernhard
2016-05-14
Reaction path optimization is being used more frequently as an alternative to the standard practice of locating a transition state and following the path downhill. The Variational Reaction Coordinate (VRC) method was proposed as an alternative to chain-of-states methods like nudged elastic band and string method. The VRC method represents the path using a linear expansion of continuous basis functions, allowing the path to be optimized variationally by updating the expansion coefficients to minimize the line integral of the potential energy gradient norm, referred to as the Variational Reaction Energy (VRE) of the path. When constraints are used to control the spacing of basis functions and to couple the minimization of the VRE with the optimization of one or more individual points along the path (representing transition states and intermediates), an approximate path as well as the converged geometries of transition states and intermediates along the path are determined in only a few iterations. This algorithmic efficiency comes at a high per-iteration cost due to numerical integration of the VRE derivatives. In the present work, methods for incorporating redundant internal coordinates and potential energy surface interpolation into the VRC method are described. With these methods, the per-iteration cost, in terms of the number of potential energy surface evaluations, of the VRC method is reduced while the high algorithmic efficiency is maintained.
Optimal parallel algorithm for shortest-paths problem on interval graphs
MISHRA P.K.
2004-01-01
This paper presents an efficient parallel algorithm for the shortest-path problem in interval graph for computing shortest-paths in a weighted interval graph that runs in O(n) time with n intervals in a graph. A linear processor CRCW algorithm for determining the shortest-paths in an interval graphs is given.
Wang, Xuewu; Shi, Yingpan; Ding, Dongyan; Gu, Xingsheng
2016-02-01
Spot-welding robots have a wide range of applications in manufacturing industries. There are usually many weld joints in a welding task, and a reasonable welding path to traverse these weld joints has a significant impact on welding efficiency. Traditional manual path planning techniques can handle a few weld joints effectively, but when the number of weld joints is large, it is difficult to obtain the optimal path. The traditional manual path planning method is also time consuming and inefficient, and cannot guarantee optimality. Double global optimum genetic algorithm-particle swarm optimization (GA-PSO) based on the GA and PSO algorithms is proposed to solve the welding robot path planning problem, where the shortest collision-free paths are used as the criteria to optimize the welding path. Besides algorithm effectiveness analysis and verification, the simulation results indicate that the algorithm has strong searching ability and practicality, and is suitable for welding robot path planning.
A note on the pratical performance of the auction algorithm for the shortest path
Larsen, Jesper
1998-01-01
The performance of the auction algorithm for the shortest path problem has previously been investigated in four papers. Here the results of a series of new experiments with the code from the two most recent papers are reported. Experiments clearly show that the auction algorithm is inferior...... to the state-of-the-art shortest path algorithms....
A Practical Parallel Algorithm for All-Pair Shortest Path Based on Pipelining
Hua Wang; Ling Tian; Chun-Hua Jiang
2008-01-01
On the basis of Floyd algorithm with theextended path matrix, a parallel algorithm whichresolves all-pair shortest path (APSP) problem oncluster environment is analyzed and designed.Meanwhile, the parallel APSP pipelining algorithmmakes full use of overlapping technique betweencomputation and communication. Compared withbroadcast operation, the parallel algorithm reducescommunication cost. This algorithm has beenimplemented on MPI on PC-cluster. The theoreticalanalysis and experimental results show that the parallelalgorithm is an efficient and scalable algorithm.
Path following algorithm for the graph matching problem
Zaslavskiy, Mikhail; Vert, Jean-Philippe
2008-01-01
We propose a convex-concave programming approach for the labeled weighted graph matching problem. The convex-concave programming formulation is obtained by rewriting the graph matching problem as a least-square problem on the set of permutation matrices and relaxing it to two different optimization problems: a quadratic convex and a quadratic concave optimization problem on the set of doubly stochastic matrices. The concave relaxation has the same global minimum as the initial graph matching problem, but the search for its global minimum is also a hard combinatorial problem. We therefore construct an approximation of the concave problem solution by following a solution path of a convex-concave problem obtained by linear interpolation of the convex and concave formulations, starting from the convex relaxation. This method allows to easily integrate the information on graph label similarities into the optimization problem, and therefore to perform labeled graph matching. The algorithm is compared with some of t...
New SRLG-diverse path selection algorithm in survivable GMPLS networks
Wang Yan; Zheng Junhui; Zeng Jiazhi
2009-01-01
In conventional shared risk link group (SRLG)-diverse path selection (CSPS) algorithm in survivable GMPLS networks, SRLG is taken into account when selecting the backup paths, while the primary path selection method is the same as the algorithms without SRLG constraint. A problem of CSPS algorithm is that, after a primary path is selected, the success probability to select an SRLG-diverse backup path for it is low. If SRLG is taken into account when computing the primary path, then the probability to successfully select an SRLG-diverse backup path will be much increased. Based on this idea, an active SRLG-diverse path selection (ASPS) algorithm is proposed. To actively avoid selecting those SRLG links, when computing the primary path, a link that share risk with more links is assigned a larger link cost. To improve the resource utilization ratio, it is permitted that the bandwidth resources are shared among backup paths. What is more, differentiated reliability (DiR) requirements of different customers are considered in ASPS algorithm. The simulation results show that, compared with CSPS algorithm, ASPS algorithm not only increases successful protection probability but also improves resource utilization ratio.
Survey of Robot 3D Path Planning Algorithms
Liang Yang; Juntong Qi; Dalei Song; Jizhong Xiao; Jianda Han; Yong Xia
2016-01-01
Robot 3D (three-dimension) path planning targets for finding an optimal and collision-free path in a 3D workspace while taking into account kinematic constraints (including geometric, physical, and temporal constraints). The purpose of path planning, unlike motion planning which must be taken into consideration of dynamics, is to find a kinematically optimal path with the least time as well as model the environment completely. We discuss the fundamentals of these most successful robot 3D path...
MOD* Lite: An Incremental Path Planning Algorithm Taking Care of Multiple Objectives.
Oral, Tugcem; Polat, Faruk
2016-01-01
The need for determining a path from an initial location to a target one is a crucial task in many applications, such as virtual simulations, robotics, and computer games. Almost all of the existing algorithms are designed to find optimal or suboptimal solutions considering only a single objective, namely path length. However, in many real life application path length is not the sole criteria for optimization, there are more than one criteria to be optimized that cannot be transformed to each other. In this paper, we introduce a novel multiobjective incremental algorithm, multiobjective D* lite (MOD* lite) built upon a well-known path planning algorithm, D* lite. A number of experiments are designed to compare the solution quality and execution time requirements of MOD* lite with the multiobjective A* algorithm, an alternative genetic algorithm we developed multiobjective genetic path planning and the strength Pareto evolutionary algorithm.
Using Link Analysis Technique with a Modified Shortest-Path Algorithm to Fight Money Laundering
CHEN Yunkai; MAI Quanwen; LU Zhengding
2006-01-01
Effective link analysis techniques are needed to help law enforcement and intelligence agencies fight money laundering.This paper presents a link analysis technique that uses a modified shortest-path algorithms to identify the strongest association paths between entities in a money laundering network.Based on two-tree Dijkstra and Priority-First-Search (PFS) algorithm, a modified algorithm is presented.To apply the algorithm, a network representation transformation is made first.
A Practical Parallel Algorithm for All-Pair Shortest Path Based on Pipelining
Hua Wang; Ling Tian; Chun-Hua Jiang
2008-01-01
On the basis of Floyd algorithm with the extended path matrix, a parallel algorithm which resolves all-pair shortest path (APSP) problem on cluster environment is analyzed and designed. Meanwhile, the parallel APSP pipelining algorithm makes full use of overlapping technique between computation and communication. Compared with broadcast operation, the parallel algorithm reduces communication cost. This algorithm has been implemented on MPI on PC-cluster. The theoretical analysis and experimental results show that the parallel algorithm is an efficient and scalable algorithm.
Research on the Optimization and Simulation of the Shortest Path Based on Algorithm of Dijkstra
2010-01-01
<正>Dijkstra algorithm is a theoretical basis to solve transportation network problems of the shortest path, which has a wide range of application in path optimization. Through analyzing traditional Dijkstra algorithm,on account of the insufficiency of this algorithm in path optimization,this paper uses adjacency list and circular linked list with combination to store date,and through the improved quick sorting algorithm for weight sorting, accomplish a quick search to the adjacent node,and so an improved Dijkstra algorithm is got.Then apply it to the optimal path search,and make simulation analysis for this algorithm through the example,also verify the effectiveness of the proposed algorithm.
Research on stereo vision path-planning algorithms for mobile robots autonomous navigation
ZHANG Guo-wei; LU Qiu-hong
2009-01-01
Using stereo vision for autonomous mobile robot path-planning is a hot technology. The environment mapping and path-planning algorithms were introduced, and they were applied in the autonomous mobile robot experiment platform. Through experiments in the robot platform, the effectiveness of these algorithms was verified.
Path planning of decentralized multi-quadrotor based on fuzzy-cell decomposition algorithm
Iswanto, Wahyunggoro, Oyas; Cahyadi, Adha Imam
2017-04-01
The paper aims to present a design algorithm for multi quadrotor lanes in order to move towards the goal quickly and avoid obstacles in an area with obstacles. There are several problems in path planning including how to get to the goal position quickly and avoid static and dynamic obstacles. To overcome the problem, therefore, the paper presents fuzzy logic algorithm and fuzzy cell decomposition algorithm. Fuzzy logic algorithm is one of the artificial intelligence algorithms which can be applied to robot path planning that is able to detect static and dynamic obstacles. Cell decomposition algorithm is an algorithm of graph theory used to make a robot path map. By using the two algorithms the robot is able to get to the goal position and avoid obstacles but it takes a considerable time because they are able to find the shortest path. Therefore, this paper describes a modification of the algorithms by adding a potential field algorithm used to provide weight values on the map applied for each quadrotor by using decentralized controlled, so that the quadrotor is able to move to the goal position quickly by finding the shortest path. The simulations conducted have shown that multi-quadrotor can avoid various obstacles and find the shortest path by using the proposed algorithms.
Double-link failure protection algorithm for shared sub-path in survivable WDM mesh networks
Lei Guo(郭磊); Hongfang Yu(虞红芳); Lemin Li(李乐民)
2004-01-01
We propose a novel shared sub-path protection (SSPP) algorithm to protect the double-link failures in wavelength division multiplexing (WDM) mesh networks. SSPP segments the primary path into several equal-length sub-paths and searches two link-disjoint backup paths for each sub-path. When computing the paths, SSPP considers the load balance and the resource sharing degree, so that the blocking ratio can be effectively reduced. The simulation results show that SSPP not only can completely protect the double-link failures but also can make the tradeoffs between the resource utilization ratio (or blocking ratio) and the protection-switching time.
Using Moore Dijkstra Algorithm with Multi-Agent System to Find Shortest Path over Network
Basem Alrifai
2015-06-01
Full Text Available finding the shortest path over network is very difficult and it is the target for much research, after many researches get the result in many of algorithm and many a mount based on the performance for these algorithm .Shortest paths problems are familiar problems in computer science and mathematics. In these problems, edge weights may represent distances, costs, or any other real-valued quantity that can be added along a path, and that one may wish to minimize. Thus, edge weights are real numbers and the specific operations used are addition to compute the weight of a path and minimum to select the best path weight. In this paper we use the Dijkstra's algorithm with new technique to find the shortest path over network to reduce the time we need to find the best path, in this paper we use node for network with the same value which can be use it to find the shortest path but this depend on the number of transition for every node when the node have high number then the node have the high priority to choose it by using this method we descries the time to find the short path .to make this algorithm more distinguish apply multi-agent system ( Automata with multiplicities to find the short path.
Challenging of path planning algorithms for autonomous robot in known environment
Farah, R. N.; Irwan, N.; Zuraida, Raja Lailatul; Shaharum, Umairah; Hanafi@Omar, Hafiz Mohd
2014-06-01
Most of the mobile robot path planning is estimated to reach its predetermined aim through the shortest path and avoiding the obstacles. This paper is a survey on path planning algorithms of various current research and existing system of Unmanned Ground Vehicles (UGV) where their challenging issues to be intelligent autonomous robot. The focuses are some short reviews on individual papers for UGV in the known environment. Methods and algorithms in path planning for the autonomous robot had been discussed. From the reviews, we obtained that the algorithms proposed are appropriate for some cases such as single or multiple obstacles, static or movement obstacle and optimal shortest path. This paper also describes some pros and cons for every reviewed paper toward algorithms improvement for further work.
LNN Blind Multi-user Detection Algorithm for Multi-path-fading CDMA Channels
LI Yan-ping; WANG Hua-kui; MIAO Rui-qing
2006-01-01
A blind multi-user detection algorithm (BMUD) which is suitable for multi-path-fading Channels based on Lagrange neural network (LNN) is proposed. Based on the minimum output energy (MOE) criterion, the blind detection algorithm is formulated as a constrained optimization problem inherently and is then resolved efficiently using the neural network. Compared with the previous RLS(recursive least squares )-MOE blind detection algorithm or for multi-path channel, the BMUD based on LNN has better performances: lower computational complexity, faster convergence speed and capability in the multi-path-fading channel. The bit error rate (BER) and signal-to-interference-and-noise ratio(SINR) performances of the detection algorithm in multi-path channel are close to that in single path channel.
AN OPTIMUM VEHICULAR PATH ALGORITHM FOR TRAFFIC NETWORK BASED ON HIERARCHICAL SPATIAL REASONING
无
2000-01-01
Human beings' intellection is the characteristic of a distinct hierarchy and can be taken to construct a heuristic in the shortest path algorithms.It is detailed in this paper how to utilize the hierarchical reasoning on the basis of greedy and directional strategy to establish a spatial heuristic,so as to improve running efficiency and suitability of shortest path algorithm for traffic network.The authors divide urban traffic network into three hierarchies and set forward a new node hierarchy division rule to avoid the unreliable solution of shortest path.It is argued that the shortest path,no matter distance shortest or time shortest,is usually not the favorite of drivers in practice.Some factors difficult to expect or quantify influence the drivers' choice greatly.It makes the drivers prefer choosing a less shortest,but more reliable or flexible path to travel on.The presented optimum path algorithm,in addition to the improvement of the running efficiency of shortest path algorithms up to several times,reduces the emergence of those factors,conforms to the intellection characteristic of human beings,and is more easily accepted by drivers.Moreover,it does not require the completeness of networks in the lowest hierarchy and the applicability and fault tolerance of the algorithm have improved.The experiment result shows the advantages of the presented algorithm.The authors argued that the algorithm has great potential application for navigation systems of large-scale traffic networks.
Path planning based on sliding window and variant A*algorithm for quadruped robot
张慧
2016-01-01
In order to improve the adaptability of the quadruped robot in complex environments , a path planning method based on sliding window and variant A * algorithm for quadruped robot is presen-ted .To improve the path planning efficiency and robot security , an incremental A*search algorithm ( IA*) and the A*algorithm having obstacle grids extending ( EA*) are proposed respectively .The IA* algorithm firstly searches an optimal path based on A * algorithm, then a new route from the current path to the new goal projection is added to generate a suboptimum route incrementally .In comparison with traditional method solving path planning problem from scratch , the IA* enables the robot to plan path more efficiently .EA* extends the obstacle by means of increasing grid g-value, which makes the route far away from the obstacle and avoids blocking the narrow passage .To navi-gate the robot running smoothly , a quadratic B-spline interpolation is applied to smooth the path . Simulation results illustrate that the IA* algorithm can increase the re-planning efficiency more than 5 times and demonstrate the effectiveness of the EA * algorithm.
V.PURUSHOTHAM REDDY
2011-02-01
Full Text Available In computer networks the routing is based on shortest path routing algorithms. Based on its advantages, an alternative method is used known as Genetic Algorithm based routing algorithm, which is highly scalable and insensitive to variations in network topology. Here we propose a coarse-grained parallel genetic algorithm to solve the shortest path routing problem with the primary goal of computation time reduction along with the use of migration scheme. This algorithm is developed and implemented on an MPI cluster. The effects of migration and its performance is studied in this paper.
GENERALIZATION OF DIJKSTRAâS ALGORITHM FOR EXTRACTION OF SHORTEST PATHS IN DIRECTED MULTIGRAPHS
Siddhartha Sankar Biswas
2013-01-01
Full Text Available The classical Dijkstraâs algorithm to find the shortest path in graphs is not applicable to multigraphs. In this study the authors generalize the classical Dijkstraâs algorithm to make it applicable to directed multigraphs. The modified algorithm is called by Generalized Dijkstraâs algorithm or GD Algorithm (GDA in short. The GDA outputs the shortest paths and the corresponding min cost. It is claimed that GDA may play a major role in many application areas of computer science, communication, transportation systems, in particular in those networks which cannot be modeled into graphs but into multigraphs."
A path planning algorithm based on Bezier curves for underwater vehicles
Shang Liuji; Wang Shuo
2010-01-01
An on-line path planning algorithm based on Bezier curves is presented for underwater vehicles.Aiming at the special requirements of underwater vehicles and 3D environment,the algorithm consists of two steps: the generation of spatial path and the processing of some constraints.A path for underwater vehicles is planned,which satisfies the velocity constraint and the centripetal acceleration constraint of underwater vehicles.The proposed path planning method can be used for the vehicle's locomotion and navigation control.
A focussed dynamic path finding algorithm with constraints
Leenen, L
2013-11-01
Full Text Available digital representation of the actual terrain. The MUPFP has to be solved in an environment where information can change whilst the optimal path is being calculated, i.e. obstacles and threats can move or appear and path costs can change. In previous work...
PP: A graphics post-processor for the EQ6 reaction path code
Stockman, H.W.
1994-09-01
The PP code is a graphics post-processor and plotting program for EQ6, a popular reaction-path code. PP runs on personal computers, allocates memory dynamically, and can handle very large reaction path runs. Plots of simple variable groups, such as fluid and solid phase composition, can be obtained with as few as two keystrokes. Navigation through the list of reaction path variables is simple and efficient. Graphics files can be exported for inclusion in word processing documents and spreadsheets, and experimental data may be imported and superposed on the reaction path runs. The EQ6 thermodynamic database can be searched from within PP, to simplify interpretation of complex plots.
The quickly switching routing algorithm based on multi-path in mobile Ad Hoc networks
无
2006-01-01
This paper proposes a new on-demand multi-alternate-path algorithm, called quickly switching routing algorithm(QSRA). It switches failure routing to an alternate path as quickly as the network can. Like a nervure shape, algorithm QSRA shapes disjoint-alternate-path structure, but is not limited to. It also contains another structure that every primary node has several links to alternate paths. This structure has two advantages, the first one is that primary nodes can select one alternate path immediately when primary routing is failure without going back to source node to re-discover a new routing or choose an alternate path; the second is that it guarantees primary nodes can select another alternate path as quickly as possible once one of alternate paths fails. Strongpoint of algorithm QSRA is reducing frequency of routing re-discovering. Besides, the structure occupies fewer resources than other routing algorithms due to its distributed structure. Simulation shows that QSRA has higher packets received ratio and lower control packet overhead and lower end-to-end delay.
Neural network and genetic algorithm based global path planning in a static environment
DU Xin; CHEN Hua-hua; GU Wei-kang
2005-01-01
Mobile robot global path planning in a static environment is an important problem. The paper proposes a method of global path planning based on neural network and genetic algorithm. We constructed the neural network model of environmental information in the workspace for a robot and used this model to establish the relationship between a collision avoidance path and the output of the model. Then the two-dimensional coding for the path via-points was converted to one-dimensional one and the fitness of both the collision avoidance path and the shortest distance are integrated into a fitness function. The simulation results showed that the proposed method is correct and effective.
OPTIMAL ALGORITHM FOR NO TOOlRETRACTIONS CONTOUR-PARALLEL OFFSET TOOL-PATH LINKING
HAO Yongtao; JIANG Lili
2007-01-01
A contour-parallel offset (CPO) tool-path linking algorithm is derived without toolretractions and with the largest practicability. The concept of "tool-path loop tree" (TPL-tree)providing the information on the parent/child relationships among the tool-path loops (TPLs) is presented. The direction, tool-path loop, leaf/branch, layer number, and the corresponding points of the TPL-tree are introduced. By defining TPL as a vector, and by traveling throughout the tree, a CPO tool-path without tool-retractions can be derived.
An Evaluation of Potentials of Genetic Algorithm in Shortest Path Problem
Hassany Pazooky, S.; Rahmatollahi Namin, Sh; Soleymani, A.; Samadzadegan, F.
2009-04-01
One of the most typical issues considered in combinatorial systems in transportation networks, is the shortest path problem. In such networks, routing has a significant impact on the network's performance. Due to natural complexity in transportation networks and strong impact of routing in different fields of decision making, such as traffic management and vehicle routing problem (VRP), appropriate solutions to solve this problem are crucial to be determined. During last years, in order to solve the shortest path problem, different solutions are proposed. These techniques are divided into two categories of classic and evolutionary approaches. Two well-known classic algorithms are Dijkstra and A*. Dijkstra is known as a robust, but time consuming algorithm in finding the shortest path problem. A* is also another algorithm very similar to Dijkstra, less robust but with a higher performance. On the other hand, Genetic algorithms are introduced as most applicable evolutionary algorithms. Genetic Algorithm uses a parallel search method in several parts of the domain and is not trapped in local optimums. In this paper, the potentiality of Genetic algorithm for finding the shortest path is evaluated by making a comparison between this algorithm and classic algorithms (Dijkstra and A*). Evaluation of the potential of these techniques on a transportation network in an urban area shows that due to the problem of classic methods in their small search space, GA had a better performance in finding the shortest path.
HCTNav: A Path Planning Algorithm for Low-Cost Autonomous Robot Navigation in Indoor Environments
Javier Garrido
2013-08-01
Full Text Available Low-cost robots are characterized by low computational resources and limited energy supply. Path planning algorithms aim to find the optimal path between two points so the robot consumes as little energy as possible. However, these algorithms were not developed considering computational limitations (i.e., processing and memory capacity. This paper presents the HCTNav path-planning algorithm (HCTLab research group’s navigation algorithm. This algorithm was designed to be run in low-cost robots for indoor navigation. The results of the comparison between HCTNav and the Dijkstra’s algorithms show that HCTNav’s memory peak is nine times lower than Dijkstra’s in maps with more than 150,000 cells.
L.Yang
2015-12-01
Full Text Available Three-dimensional path planning for underwater vehicles is an important problem that focuses on optimizing the route with consideration of various constraints in a complex underwater environment. In this paper, an improved ant colony optimization (IACO algorithm based on pheromone exclusion is proposed to solve the underwater vehicle 3D path planning problem. The IACO algorithm can balance the tasks of exploration and development in the ant search path, and enable the ants in the search process to explore initially and develop subsequently. Then, the underwater vehicle can find the safe path by connecting the chosen nodes of the 3D mesh while avoiding the threat area. This new approach can overcome common disadvantages of the basic ant colony algorithm, such as falling into local extremum, poor quality, and low accuracy. Experimental comparative results demonstrate that this proposed IACO method is more effective and feasible in underwater vehicle 3D path planning than the basic ACO model.
A O(E) Time Shortest Path Algorithm For Non Negative Weighted Undirected Graphs
Qureshi, Muhammad Aasim; Safdar, Sohail; Akbar, Rehan
2009-01-01
In most of the shortest path problems like vehicle routing problems and network routing problems, we only need an efficient path between two points source and destination, and it is not necessary to calculate the shortest path from source to all other nodes. This paper concentrates on this very idea and presents an algorithm for calculating shortest path for (i) nonnegative weighted undirected graphs (ii) unweighted undirected graphs. The algorithm completes its execution in O(E) for all graphs except few in which longer path (in terms of number of edges) from source to some node makes it best selection for that node. The main advantage of the algorithms is its simplicity and it does not need complex data structures for implementations.
An improved Physarum polycephalum algorithm for the shortest path problem
Zhang, Xiaoge; Wang, Qing; Adamatzky, Andrew; Chan, Felix T S; Mahadevan, Sankaran; Deng, Yong
2014-01-01
.... Acellular slime mould P. polycephalum is originally famous as a computing biological substrate due to its alleged ability to approximate shortest path from its inoculation site to a source of nutrients...
Path planning for mobile robots based on visibility graphs and A* algorithm
Contreras, Juan D.; Martínez S., Fernando; Martínez S., Fredy H.
2015-07-01
One of most worked issues in the last years in robotics has been the study of strategies to path planning for mobile robots in static and observable conditions. This is an open problem without pre-defined rules (non-heuristic), which needs to measure the state of the environment, finds useful information, and uses an algorithm to select the best path. This paper proposes a simple and efficient geometric path planning strategy supported in digital image processing. The image of the environment is processed in order to identify obstacles, and thus the free space for navigation. Then, using visibility graphs, the possible navigation paths guided by the vertices of obstacles are produced. Finally the A* algorithm is used to find a best possible path. The alternative proposed is evaluated by simulation on a large set of test environments, showing in all cases its ability to find a free collision plausible path.
An algorithm to find critical execution paths of software based on complex network
Huang, Guoyan; Zhang, Bing; Ren, Rong; Ren, Jiadong
2015-01-01
The critical execution paths play an important role in software system in terms of reducing the numbers of test date, detecting the vulnerabilities of software structure and analyzing software reliability. However, there are no efficient methods to discover them so far. Thus in this paper, a complex network-based software algorithm is put forward to find critical execution paths (FCEP) in software execution network. First, by analyzing the number of sources and sinks in FCEP, software execution network is divided into AOE subgraphs, and meanwhile, a Software Execution Network Serialization (SENS) approach is designed to generate execution path set in each AOE subgraph, which not only reduces ring structure's influence on path generation, but also guarantees the nodes' integrity in network. Second, according to a novel path similarity metric, similarity matrix is created to calculate the similarity among sets of path sequences. Third, an efficient method is taken to cluster paths through similarity matrices, and the maximum-length path in each cluster is extracted as the critical execution path. At last, a set of critical execution paths is derived. The experimental results show that the FCEP algorithm is efficient in mining critical execution path under software complex network.
A simple and accurate algorithm for path integral molecular dynamics with the Langevin thermostat
Liu, Jian; Li, Dezhang; Liu, Xinzijian
2016-07-01
We introduce a novel simple algorithm for thermostatting path integral molecular dynamics (PIMD) with the Langevin equation. The staging transformation of path integral beads is employed for demonstration. The optimum friction coefficients for the staging modes in the free particle limit are used for all systems. In comparison to the path integral Langevin equation thermostat, the new algorithm exploits a different order of splitting for the phase space propagator associated to the Langevin equation. While the error analysis is made for both algorithms, they are also employed in the PIMD simulations of three realistic systems (the H2O molecule, liquid para-hydrogen, and liquid water) for comparison. It is shown that the new thermostat increases the time interval of PIMD by a factor of 4-6 or more for achieving the same accuracy. In addition, the supplementary material shows the error analysis made for the algorithms when the normal-mode transformation of path integral beads is used.
A simple and accurate algorithm for path integral molecular dynamics with the Langevin thermostat.
Liu, Jian; Li, Dezhang; Liu, Xinzijian
2016-07-14
We introduce a novel simple algorithm for thermostatting path integral molecular dynamics (PIMD) with the Langevin equation. The staging transformation of path integral beads is employed for demonstration. The optimum friction coefficients for the staging modes in the free particle limit are used for all systems. In comparison to the path integral Langevin equation thermostat, the new algorithm exploits a different order of splitting for the phase space propagator associated to the Langevin equation. While the error analysis is made for both algorithms, they are also employed in the PIMD simulations of three realistic systems (the H2O molecule, liquid para-hydrogen, and liquid water) for comparison. It is shown that the new thermostat increases the time interval of PIMD by a factor of 4-6 or more for achieving the same accuracy. In addition, the supplementary material shows the error analysis made for the algorithms when the normal-mode transformation of path integral beads is used.
Z-Q. Luo; J.F. Sturm; S. Zhang (Shuzhong)
1996-01-01
textabstractThis paper establishes the superlinear convergence of a symmetric primal-dual path following algorithm for semidefinite programming under the assumptions that the semidefinite program has a strictly complementary primal-dual optimal solution and that the size of the central path neighbor
Ghosal, Dipak (University of California, Davis, CA); Mueller, Stephen Ng
2005-04-01
With multipath routing in mobile ad hoc networks (MANETs), a source can establish multiple routes to a destination for routing data. In MANETs, mulitpath routing can be used to provide route resilience, smaller end-to-end delay, and better load balancing. However, when the multiple paths are close together, transmissions of different paths may interfere with each other, causing degradation in performance. Besides interference, the physical diversity of paths also improves fault tolerance. We present a purely distributed multipath protocol based on the AODV-Multipath (AODVM) protocol called AODVM with Path Diversity (AODVM/PD) that finds multiple paths with a desired degree of correlation between paths specified as an input parameter to the algorithm. We demonstrate through detailed simulation analysis that multiple paths with low degree of correlation determined by AODVM/PD provides both smaller end-to-end delay than AODVM in networks with low mobility and better route resilience in the presence of correlated node failures.
Amoeba-Inspired Heuristic Search Dynamics for Exploring Chemical Reaction Paths.
Aono, Masashi; Wakabayashi, Masamitsu
2015-09-01
We propose a nature-inspired model for simulating chemical reactions in a computationally resource-saving manner. The model was developed by extending our previously proposed heuristic search algorithm, called "AmoebaSAT [Aono et al. 2013]," which was inspired by the spatiotemporal dynamics of a single-celled amoeboid organism that exhibits sophisticated computing capabilities in adapting to its environment efficiently [Zhu et al. 2013]. AmoebaSAT is used for solving an NP-complete combinatorial optimization problem [Garey and Johnson 1979], "the satisfiability problem," and finds a constraint-satisfying solution at a speed that is dramatically faster than one of the conventionally known fastest stochastic local search methods [Iwama and Tamaki 2004] for a class of randomly generated problem instances [ http://www.cs.ubc.ca/~hoos/5/benchm.html ]. In cases where the problem has more than one solution, AmoebaSAT exhibits dynamic transition behavior among a variety of the solutions. Inheriting these features of AmoebaSAT, we formulate "AmoebaChem," which explores a variety of metastable molecules in which several constraints determined by input atoms are satisfied and generates dynamic transition processes among the metastable molecules. AmoebaChem and its developed forms will be applied to the study of the origins of life, to discover reaction paths for which expected or unexpected organic compounds may be formed via unknown unstable intermediates and to estimate the likelihood of each of the discovered paths.
Amoeba-Inspired Heuristic Search Dynamics for Exploring Chemical Reaction Paths
Aono, Masashi; Wakabayashi, Masamitsu
2015-09-01
We propose a nature-inspired model for simulating chemical reactions in a computationally resource-saving manner. The model was developed by extending our previously proposed heuristic search algorithm, called "AmoebaSAT [Aono et al. 2013]," which was inspired by the spatiotemporal dynamics of a single-celled amoeboid organism that exhibits sophisticated computing capabilities in adapting to its environment efficiently [Zhu et al. 2013]. AmoebaSAT is used for solving an NP-complete combinatorial optimization problem [Garey and Johnson 1979], "the satisfiability problem," and finds a constraint-satisfying solution at a speed that is dramatically faster than one of the conventionally known fastest stochastic local search methods [Iwama and Tamaki 2004] for a class of randomly generated problem instances [http://www.cs.ubc.ca/~hoos/5/benchm.html]. In cases where the problem has more than one solution, AmoebaSAT exhibits dynamic transition behavior among a variety of the solutions. Inheriting these features of AmoebaSAT, we formulate "AmoebaChem," which explores a variety of metastable molecules in which several constraints determined by input atoms are satisfied and generates dynamic transition processes among the metastable molecules. AmoebaChem and its developed forms will be applied to the study of the origins of life, to discover reaction paths for which expected or unexpected organic compounds may be formed via unknown unstable intermediates and to estimate the likelihood of each of the discovered paths.
Thermochemistry, reaction paths, and kinetics on the tert-isooctane radical reaction with O2.
Snitsiriwat, Suarwee; Bozzelli, Joseph W
2014-07-03
Thermochemical properties of tert-isooctane hydroperoxide and its radicals are determined by computational chemistry. Enthalpies are determined using isodesmic reactions with B3LYP density function and CBS QB3 methods. Application of group additivity with comparison to calculated values is illustrated. Entropy and heat capacities are determined using geometric parameters and frequencies from the B3LYP/6-31G(d,p) calculations for the lowest energy conformer. Internal rotor potentials are determined for the tert-isooctane hydroperoxide and its radicals in order to identify isomer energies. Recommended values derived from the most stable conformers of tert-isooctane hydroperoxide of are -77.85 ± 0.44 kcal mol(-1). Isooctane is a highly branched molecule, and its structure has a significant effect on its thermochemistry and reaction barriers. Intramolecular interactions are shown to have a significant effect on the enthalpy of the isooctane parent and its radicals on peroxy/peroxide systems, the R• + O2 well depths and unimolecular reaction barriers. Bond dissociation energies and well depths, for tert-isooctane hydroperoxide → R• + O2 are 33.5 kcal mol(-1) compared to values of ∼38 to 40 kcal mol(-1) for the smaller tert-butyl-O2 → R• + O2. Transition states and kinetic parameters for intramolecular hydrogen atom transfer and molecular elimination channels are characterized to evaluate reaction paths and kinetics. Kinetic parameters are determined versus pressure and temperature for the chemically activated formation and unimolecular dissociation of the peroxide adducts. Multifrequency quantum RRK (QRRK) analysis is used for k(E) with master equation analysis for falloff. The major reaction paths at 1000 K are formation of isooctane plus HO2 followed by cyclic ether plus OH. Stabilization of the tert-isooctane hydroperoxy radical becomes important at lower temperatures.
Chang Liu
2015-01-01
Full Text Available Path planning is a classic optimization problem which can be solved by many optimization algorithms. The complexity of three-dimensional (3D path planning for autonomous underwater vehicles (AUVs requires the optimization algorithm to have a quick convergence speed. This work provides a new 3D path planning method for AUV using a modified firefly algorithm. In order to solve the problem of slow convergence of the basic firefly algorithm, an improved method was proposed. In the modified firefly algorithm, the parameters of the algorithm and the random movement steps can be adjusted according to the operating process. At the same time, an autonomous flight strategy is introduced to avoid instances of invalid flight. An excluding operator was used to improve the effect of obstacle avoidance, and a contracting operator was used to enhance the convergence speed and the smoothness of the path. The performance of the modified firefly algorithm and the effectiveness of the 3D path planning method were proved through a varied set of experiments.
Liu, Haiyan; Lu, Zhenyu; Cisneros, G Andres; Yang, Weitao
2004-07-08
The determination of reaction paths for enzyme systems remains a great challenge for current computational methods. In this paper we present an efficient method for the determination of minimum energy reaction paths with the ab initio quantum mechanical/molecular mechanical approach. Our method is based on an adaptation of the path optimization procedure by Ayala and Schlegel for small molecules in gas phase, the iterative quantum mechanical/molecular mechanical (QM/MM) optimization method developed earlier in our laboratory and the introduction of a new metric defining the distance between different structures in the configuration space. In this method we represent the reaction path by a discrete set of structures. For each structure we partition the atoms into a core set that usually includes the QM subsystem and an environment set that usually includes the MM subsystem. These two sets are optimized iteratively: the core set is optimized to approximate the reaction path while the environment set is optimized to the corresponding energy minimum. In the optimization of the core set of atoms for the reaction path, we introduce a new metric to define the distances between the points on the reaction path, which excludes the soft degrees of freedom from the environment set and includes extra weights on coordinates describing chemical changes. Because the reaction path is represented by discrete structures and the optimization for each can be performed individually with very limited coupling, our method can be executed in a natural and efficient parallelization, with each processor handling one of the structures. We demonstrate the applicability and efficiency of our method by testing it on two systems previously studied by our group, triosephosphate isomerase and 4-oxalocrotonate tautomerase. In both cases the minimum energy paths for both enzymes agree with the previously reported paths.
Smoothed analysis of the successive shortest path algorithm
Cornelissen, Kamiel; Brunsch, Tobias; Hoeksma, R.P.; Hurink, Johann L.; Manthey, Bodo; Röglin, Heiko
2013-01-01
The minimum-cost flow problem is a classic problem in combinatorial optimization with various applications. Several pseudo-polynomial, polynomial, and strongly polynomial algorithms have been developed in the past decades, and it seems that both the problem and the algorithms are well understood.
A symbolic shortest path algorithm for computing subgame-perfect Nash equilibria
Góngora Pedro A.
2015-09-01
Full Text Available Consider games where players wish to minimize the cost to reach some state. A subgame-perfect Nash equilibrium can be regarded as a collection of optimal paths on such games. Similarly, the well-known state-labeling algorithm used in model checking can be viewed as computing optimal paths on a Kripke structure, where each path has a minimum number of transitions. We exploit these similarities in a common generalization of extensive games and Kripke structures that we name “graph games”. By extending the Bellman-Ford algorithm for computing shortest paths, we obtain a model-checking algorithm for graph games with respect to formulas in an appropriate logic. Hence, when given a certain formula, our model-checking algorithm computes the subgame-perfect Nash equilibrium (as opposed to simply determining whether or not a given collection of paths is a Nash equilibrium. Next, we develop a symbolic version of our model checker allowing us to handle larger graph games. We illustrate our formalism on the critical-path method as well as games with perfect information. Finally, we report on the execution time of benchmarks of an implementation of our algorithms
A Branch-and-Cut Algorithm for Elementary Shortest Path Problem with Resource Constraints
Jepsen, Mads Kehlet; Petersen, Bjørn; Spoorendonk, Simon
The elementary shortest path with resource constraints are commonly solved with dynamic programming algorithms. We present a branch-and-cut algorithm for the undirected version. Two types of resources are discussed: A capacity and a fixed charge resource. The former is the subproblem of the capac...... of the capacitated vehicle routing problem and the latter is for the split delivery version....
Reaction paths of the water-assisted neutral hydrolysis of ethyl acetate.
Yamabe, Shinichi; Tsuchida, Noriko; Hayashida, Yousuke
2005-08-18
Density functional theory calculations were conducted on the title reactions with explicit inclusion of a variety of water molecules. Concerted reaction paths were examined first in the reaction model, ester(H2O)n --> MeCOOH(H2O)(n-1)EtOH, with n = 1-4. Their Gibbs activation energies are much larger than the experimental value, and the concerted paths are unfavorable. Various stepwise paths were investigated, and the ester(H2O)4 reactant gives a likely stepwise path. The n = 4 based reaction models, n = 4 + 5 and n = 4 + 12, were found to have similar proton-relay shapes with good hydrogen-bond directionality. The distinction of either the concerted or the stepwise path is described by the position of only one proton in the "junction" water molecule.
Parallel Algorithm for Generation of Test Recommended Path using CUDA
Lee-Sub Lee
2013-02-01
Full Text Available Software testing of an application makes the user to find defect. The users, called testers, should test the various situations with test cases. In order to make test cases, many states and events haveto be considered. It takes much time to create test cases with many states and events. Instead of using the common sequential algorithm, this paper proposes a parallel algorithm for generation of test cases. The proposed method achieves efficient performance using General- Purpose GPU (GPGPU, especially CUDA.
Chunxia Jia; Detong Zhu
2008-01-01
In this paper we propose an affine scaling interior algorithm via conjugate gradient path for solving nonlinear equality systems subject to bounds on variables.By employing the affine scaling conjugate gradient path search strategy,we obtain an iterative direction by solving the linearize model.By using the line search technique,we will find an acceptable trial step length along this direction which is strictly feasible and makes the objective function nonmonotonically decreasing.The global convergence and fast local convergence rate of the proposed algorithm are established under some reasonable conditions.Furthermore,the numerical results of the proposed algorithm indicate to be effective.
Brodal, G.S.; Fagerberg, R.; Meyer, U.;
2004-01-01
We present improved cache-oblivious data structures and algorithms for breadth-first search and the single-source shortest path problem on undirected graphs with non-negative edge weights. Our results removes the performance gap between the currently best cache-aware algorithms for these problems...... and their cache-oblivious counterparts. Our shortest-path algorithm relies on a new data structure, called bucket heap, which is the first cache-oblivious priority queue to efficiently support a weak DecreaseKey operation....
A branch-and-cut algorithm for the elementary shortest path problem with resource constraints
Jepsen, Mads Kehlet; Petersen, Bjørn; Spoorendonk, Simon
The elementary shortest path with resource constraints have commonly been solved with dynamic programming algorithms. Assuming an undirected graph, we present a compact formulation of this problem and a branch-and-cut algorithm to solve it. Two types of resources are discussed: a capacity...... and a fixed charge resource. The former is the subproblem of the capacitated vehicle routing problem and the latter is from the split delivery version. Computational results are presented and compared to dynamic programming algorithms....
A topology control algorithm for preserving minimum-energy paths in wireless ad hoc networks
SHEN Zhong; CHANG Yilin; CUI Can; ZHANG Xin
2007-01-01
In this Paper,a distributed topology control algorithm is proposed.By adjusting the transmission power of each node,this algorithm constructs a wireless network topology with minimum-energy property,i.e.,it preserves a minimum-energy path between every pair of nodes.Moreover,the proposed algorithm can be used in both homogenous and heterogeneous wireless networks.and it can also work without an explicit propagation channel model or the position information of nodes.Simulation results show that the proposed algorithm has advantages over the topology control algorithm based on direct-transmission region in terms of average node degree and power efficiency.
Continuous Genetic Algorithms for Collision-Free Cartesian Path Planning of Robot Manipulators
Za'er S. Abo-Hammour
2011-12-01
Full Text Available A novel continuous genetic algorithm (CGA along with distance algorithm for solving collisions‐free path planning problem for robot manipulators is presented in this paper. Given the desired Cartesian path to be followed by the manipulator, the robot configuration as described by the D‐H parameters, and the available stationary obstacles in the workspace of the manipulator, the proposed approach will autonomously select a collision free path for the manipulator that minimizes the deviation between the generated and the desired Cartesian path, satisfy the joints limits of the manipulator, and maximize the minimum distance between the manipulator links and the obstacles. One of the main features of the algorithm is that it avoids the manipulator kinematic singularities due to the inclusion of forward kinematics model in the calculations instead of the inverse kinematics. The new robot path planning approach has been applied to two different robot configurations; 2R and PUMA 560, as non‐ redundant manipulators. Simulation results show that the proposed CGA will always select the safest path avoiding obstacles within the manipulator workspace regardless of whether there is a unique feasible solution, in terms of joint limits, or there are multiple feasible solutions. In addition to that, the generated path in Cartesian space will be of very minimal deviation from the desired one.
Imen Châari
2014-07-01
Full Text Available Path planning is a fundamental optimization problem that is crucial for the navigation of a mobile robot. Among the vast array of optimization approaches, we focus in this paper on Ant Colony Optimization (ACO and Genetic Algorithms (GA for solving the global path planning problem in a static environment, considering their effectiveness in solving such a problem. Our objective is to design an efficient hybrid algorithm that takes profit of the advantages of both ACO and GA approaches for the sake of maximizing the chance to find the optimal path even under real-time constraints. In this paper, we present smartPATH, a new hybrid ACO-GA algorithm that relies on the combination of an improved ACO algorithm (IACO for efficient and fast path selection, and a modified crossover operator to reduce the risk of falling into a local minimum. We demonstrate through extensive simulations that smartPATH outperforms classical ACO (CACO, GA algorithms. It also outperforms the Dijkstra exact method in solving the path planning problem for large graph environments. It improves the solution quality up to 57% in comparison with CACO and reduces the execution time up to 83% as compared to Dijkstra for large and dense graphs. In addition, the experimental results on a real robot shows that smartPATH finds the optimal path with a probability up to 80% with a small gap not exceeding 1m in 98%.
Research and application of genetic algorithm in path planning of logistics distribution vehicle
Wang, Yong; Zhou, Heng; Wang, Ying
2017-08-01
The core of the logistics distribution system is the vehicle routing planning, research path planning problem, provide a better solution has become an important issue. In order to provide the decision support for logistics and distribution operations, this paper studies the problem of vehicle routing with capacity constraints (CVRP). By establishing a mathematical model, the genetic algorithm is used to plan the path of the logistics vehicle to meet the minimum logistics and transportation costs.
A Hybrid Metaheuristic DE/CS Algorithm for UCAV Three-Dimension Path Planning
Gaige Wang; Lihong Guo; Hong Duan; Heqi Wang; Luo Liu; Mingzhen Shao
2012-01-01
Three-dimension path planning for uninhabited combat air vehicle (UCAV) is a complicated high-dimension optimization problem, which primarily centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. A new hybrid metaheuristic differential evolution (DE) and cuckoo search (CS) algorithm is proposed to solve the UCAV three-dimension path planning problem. DE is applied to optimize the process of selecting cuckoos of th...
Path Optimization for Single and Multiple Searchers: Models and Algorithms
2008-09-01
in that cell during that time period given the target occupies cell c at time period t is described as 1− exp(−αc, tyc ,t) instead of 1− (1−g(c, t))yc,t...yc,t number of searchers in cell c in time period t Formulation min f(y) = ∑ ω∈Ω pω exp −∑ c,t αωc, tyc ,t s.t.∑ c′∈R(c) xc′,c,t−1 = ∑ c′∈F(c) xc...are ∂f(y) ∂yc,t = − ∑ ω∈Ω pωα ω c,t exp(− ∑ c,t αωc, tyc ,t). (IV.1) Since the formulation uses all possible target paths ω ∈ Ω, if the number of
A Simple Polynomial Algorithm for the Longest Path Problem on Cocomparability Graphs
Mertzios, George B
2010-01-01
Given a graph $G$, the longest path problem asks to compute a simple path of $G$ with the largest number of vertices. This problem is the most natural optimization version of the well known and well studied Hamiltonian path problem, and thus it is NP-hard on general graphs. However, in contrast to the Hamiltonian path problem, there are only few restricted graph families such as trees and some small graph classes where polynomial algorithms for the longest path problem have been found. Recently it has been shown that this problem can be solved in polynomial time on interval graphs by applying dynamic programming to a characterizing ordering of the vertices of the given graph \\cite{longest-int-algo}, thus answering an open question. In the present paper, we provide the first polynomial algorithm for the longest path problem on a much greater class, namely on cocomparability graphs. Our algorithm uses a similar - but essentially simpler - dynamic programming approach, which is applied to a Lexicographic Depth F...
A Scheduling Algorithm for Cloud Computing System Based on the Driver of Dynamic Essential Path.
Xie, Zhiqiang; Shao, Xia; Xin, Yu
2016-01-01
To solve the problem of task scheduling in the cloud computing system, this paper proposes a scheduling algorithm for cloud computing based on the driver of dynamic essential path (DDEP). This algorithm applies a predecessor-task layer priority strategy to solve the problem of constraint relations among task nodes. The strategy assigns different priority values to every task node based on the scheduling order of task node as affected by the constraint relations among task nodes, and the task node list is generated by the different priority value. To address the scheduling order problem in which task nodes have the same priority value, the dynamic essential long path strategy is proposed. This strategy computes the dynamic essential path of the pre-scheduling task nodes based on the actual computation cost and communication cost of task node in the scheduling process. The task node that has the longest dynamic essential path is scheduled first as the completion time of task graph is indirectly influenced by the finishing time of task nodes in the longest dynamic essential path. Finally, we demonstrate the proposed algorithm via simulation experiments using Matlab tools. The experimental results indicate that the proposed algorithm can effectively reduce the task Makespan in most cases and meet a high quality performance objective.
A shortest path algorithm for moving objects in spatial network databases
Xiaolan Yin; Zhiming Ding; Jing Li
2008-01-01
One of the most important kinds of queries in Spatial Network Databases (SNDB) to support location-based services (LBS) is the shortest path query. Given an object in a network, e.g. A location of a car on a road network, and a set of objects of interests, e.g. Hotels,gas station, and car, the shortest path query returns the shortest path from the query object to interested objects. The studies of shortest path query have two kinds of ways, online processing and preprocessing. The studies of preprocessing suppose that the interest objects are static. This paper proposes a shortest path algorithm with a set of index structures to support the situation of moving objects. This algorithm can transform a dynamic problem to a static problem. In this paper we focus on road networks. However, our algorithms do not use any domain specific information, and therefore can be applied to any network. This algorithm's complexity is O(klog2i), and traditional Dijkstra's complexity is O((I + k)2).
Application of ant colony algorithm in path planning of the data center room robot
Wang, Yong; Ma, Jianming; Wang, Ying
2017-05-01
According to the Internet Data Center (IDC) room patrol robot as the background, the robot in the search path of autonomous obstacle avoidance and path planning ability, worked out in advance of the robot room patrol mission. The simulation experimental results show that the improved ant colony algorithm for IDC room patrol robot obstacle avoidance planning, makes the robot along an optimal or suboptimal and safe obstacle avoidance path to reach the target point to complete the task. To prove the feasibility of the method.
A Hybrid Metaheuristic DE/CS Algorithm for UCAV Three-Dimension Path Planning
Gaige Wang
2012-01-01
Full Text Available Three-dimension path planning for uninhabited combat air vehicle (UCAV is a complicated high-dimension optimization problem, which primarily centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. A new hybrid metaheuristic differential evolution (DE and cuckoo search (CS algorithm is proposed to solve the UCAV three-dimension path planning problem. DE is applied to optimize the process of selecting cuckoos of the improved CS model during the process of cuckoo updating in nest. The cuckoos can act as an agent in searching the optimal UCAV path. And then, the UCAV can find the safe path by connecting the chosen nodes of the coordinates while avoiding the threat areas and costing minimum fuel. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic CS. The realization procedure for this hybrid metaheuristic approach DE/CS is also presented. In order to make the optimized UCAV path more feasible, the B-Spline curve is adopted for smoothing the path. To prove the performance of this proposed hybrid metaheuristic method, it is compared with basic CS algorithm. The experiment shows that the proposed approach is more effective and feasible in UCAV three-dimension path planning than the basic CS model.
A hybrid metaheuristic DE/CS algorithm for UCAV three-dimension path planning.
Wang, Gaige; Guo, Lihong; Duan, Hong; Wang, Heqi; Liu, Luo; Shao, Mingzhen
2012-01-01
Three-dimension path planning for uninhabited combat air vehicle (UCAV) is a complicated high-dimension optimization problem, which primarily centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. A new hybrid metaheuristic differential evolution (DE) and cuckoo search (CS) algorithm is proposed to solve the UCAV three-dimension path planning problem. DE is applied to optimize the process of selecting cuckoos of the improved CS model during the process of cuckoo updating in nest. The cuckoos can act as an agent in searching the optimal UCAV path. And then, the UCAV can find the safe path by connecting the chosen nodes of the coordinates while avoiding the threat areas and costing minimum fuel. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic CS. The realization procedure for this hybrid metaheuristic approach DE/CS is also presented. In order to make the optimized UCAV path more feasible, the B-Spline curve is adopted for smoothing the path. To prove the performance of this proposed hybrid metaheuristic method, it is compared with basic CS algorithm. The experiment shows that the proposed approach is more effective and feasible in UCAV three-dimension path planning than the basic CS model.
Ancient village fire escape path planning based on improved ant colony algorithm
Xia, Wei; Cao, Kang; Hu, QianChuan
2017-06-01
The roadways are narrow and perplexing in ancient villages, it brings challenges and difficulties for people to choose route to escape when a fire occurs. In this paper, a fire escape path planning method based on ant colony algorithm is presented according to the problem. The factors in the fire environment which influence the escape speed is introduced to improve the heuristic function of the algorithm, optimal transfer strategy, and adjustment pheromone volatile factor to improve pheromone update strategy adaptively, improve its dynamic search ability and search speed. Through simulation, the dynamic adjustment of the optimal escape path is obtained, and the method is proved to be feasible.
External Memory Algorithms for Diameter and All-Pair Shortest-Paths on Sparse Graphs
Arge, Lars; Meyer, Ulrich; Toma, Laura
2004-01-01
We present several new external-memory algorithms for finding all-pairs shortest paths in a V -node, Eedge undirected graph. For all-pairs shortest paths and diameter in unweighted undirected graphs we present cache-oblivious algorithms with O(V · E B logM B E B) I/Os, where B is the block......-size and M is the size of internal memory. For weighted undirected graphs we present a cache-aware APSP algorithm that performs O(V · ( V E B +E B log E B )) I/Os. We also present efficient cacheaware algorithms that find paths between all pairs of vertices in an unweighted graph with lengths within a small...... additive constant of the shortest path length. All of our results improve earlier results known for these problems. For approximate APSP we provide the first nontrivial results. Our diameter result uses O(V + E) extra space, and all of our other algorithms use O(V 2) space....
External Memory Algorithms for Diameter and All-Pair Shortest-Paths on Sparse Graphs
Arge, Lars; Meyer, Ulrich; Toma, Laura
2004-01-01
We present several new external-memory algorithms for finding all-pairs shortest paths in a V -node, Eedge undirected graph. For all-pairs shortest paths and diameter in unweighted undirected graphs we present cache-oblivious algorithms with O(V · E B logM B E B) I/Os, where B is the block......-size and M is the size of internal memory. For weighted undirected graphs we present a cache-aware APSP algorithm that performs O(V · ( V E B +E B log E B )) I/Os. We also present efficient cacheaware algorithms that find paths between all pairs of vertices in an unweighted graph with lengths within a small...... additive constant of the shortest path length. All of our results improve earlier results known for these problems. For approximate APSP we provide the first nontrivial results. Our diameter result uses O(V + E) extra space, and all of our other algorithms use O(V 2) space....
An Investigation of Using Parallel Genetic Algorithm for Solving the Shortest Path Routing Problem
Salman Yussof
2011-01-01
Full Text Available Problem statement: Shortest path routing is the type of routing widely used in computer network nowadays. Even though shortest path routing algorithms are well established, other alternative methods may have their own advantages. One such alternative is to use a GA-based routing algorithm. According to previous researches, GA-based routing algorithm has been found to be more scalable and insensitive to variations in network topologies. However, it is also known that GA-based routing algorithm is not fast enough for real-time computation. Approach: To improve the computation time of GA-based routing algorithm, this study proposes a coarse-grained parallel GA routing algorithm for solving the shortest path routing problem. The proposed algorithm is evaluated using simulation where the proposed algorithm is executed on networks with various topologies and sizes. The parallel computation is performed using an MPI cluster. Three different experiments were conducted to identify the best value for the migration rate, the accuracy and execution time with respect to the number of computing nodes and speedup achieved as compared to the serial version of the same algorithm. Results: The result of the simulation shows that the best result is achieved for a migration rate around 0.1 and 0.2. The experiments also show that with larger number of computing nodes, accuracy decreases linearly, but computation time decreases exponentially, which justifies the use parallel implementation of GA to improve the speed of GA-based routing algorithm. Finally, the experiments also show that the proposed algorithm is able to achieve a speedup of up to 818.11% on the MPI cluster used to run the simulation. Conclusion/Recommendations: We have successfully shown that the performance of GA-based shortest path routing algorithm can be improved by using a coarse-grained parallel GA implementation. Even though in this study the proposed algorithm is executed
Tien, Nguyen Xuan; Kim, Semog; Rhee, Jong Myung; Park, Sang Yoon
2017-07-25
Fault tolerance has long been a major concern for sensor communications in fault-tolerant cyber physical systems (CPSs). Network failure problems often occur in wireless sensor networks (WSNs) due to various factors such as the insufficient power of sensor nodes, the dislocation of sensor nodes, the unstable state of wireless links, and unpredictable environmental interference. Fault tolerance is thus one of the key requirements for data communications in WSN applications. This paper proposes a novel path redundancy-based algorithm, called dual separate paths (DSP), that provides fault-tolerant communication with the improvement of the network traffic performance for WSN applications, such as fault-tolerant CPSs. The proposed DSP algorithm establishes two separate paths between a source and a destination in a network based on the network topology information. These paths are node-disjoint paths and have optimal path distances. Unicast frames are delivered from the source to the destination in the network through the dual paths, providing fault-tolerant communication and reducing redundant unicast traffic for the network. The DSP algorithm can be applied to wired and wireless networks, such as WSNs, to provide seamless fault-tolerant communication for mission-critical and life-critical applications such as fault-tolerant CPSs. The analyzed and simulated results show that the DSP-based approach not only provides fault-tolerant communication, but also improves network traffic performance. For the case study in this paper, when the DSP algorithm was applied to high-availability seamless redundancy (HSR) networks, the proposed DSP-based approach reduced the network traffic by 80% to 88% compared with the standard HSR protocol, thus improving network traffic performance.
ESHOPPS: A COMPUTATIONAL TOOL TO AID THE TEACHING OF SHORTEST PATH ALGORITHMS
S. J. de A. LIMA
2015-07-01
Full Text Available The development of a computational tool called EShoPPS – Environment for Shortest Path Problem Solving, which is used to assist students in understanding the working of Dijkstra, Greedy search and A*(star algorithms is presented in this paper. Such algorithms are commonly taught in graduate and undergraduate courses of Engineering and Informatics and are used for solving many optimization problems that can be characterized as Shortest Path Problem. The EShoPPS is an interactive tool that allows students to create a graph representing the problem and also helps in developing their knowledge of each specific algorithm. Experiments performed with 155 students of undergraduate and graduate courses such as Industrial Engineering, Computer Science and Information Systems have shown that by using the EShoPPS tool students were able to improve their interpretation of investigated algorithms.
A new efficient optimal path planner for mobile robot based on Invasive Weed Optimization algorithm
Mohanty, Prases K.; Parhi, Dayal R.
2014-12-01
Planning of the shortest/optimal route is essential for efficient operation of autonomous mobile robot or vehicle. In this paper Invasive Weed Optimization (IWO), a new meta-heuristic algorithm, has been implemented for solving the path planning problem of mobile robot in partially or totally unknown environments. This meta-heuristic optimization is based on the colonizing property of weeds. First we have framed an objective function that satisfied the conditions of obstacle avoidance and target seeking behavior of robot in partially or completely unknown environments. Depending upon the value of objective function of each weed in colony, the robot avoids obstacles and proceeds towards destination. The optimal trajectory is generated with this navigational algorithm when robot reaches its destination. The effectiveness, feasibility, and robustness of the proposed algorithm has been demonstrated through series of simulation and experimental results. Finally, it has been found that the developed path planning algorithm can be effectively applied to any kinds of complex situation.
Identification of Optimal Path in Power System Network Using Bellman Ford Algorithm
S. Hemalatha
2012-01-01
Full Text Available Power system network can undergo outages during which there may be a partial or total blackout in the system. In that condition, transmission of power through the optimal path is an important problem in the process of reconfiguration of power system components. For a given set of generation, load pair, there could be many possible paths to transmit the power. The optimal path needs to consider the shortest path (minimum losses, capacity of the transmission line, voltage stability, priority of loads, and power balance between the generation and demand. In this paper, the Bellman Ford Algorithm (BFA is applied to find out the optimal path and also the several alternative paths by considering all the constraints. In order to demonstrate the capability of BFA, it has been applied to a practical 230 kV network. This restorative path search guidance tool is quite efficient in finding the optimal and also the alternate paths for transmitting the power from a generating station to demand.
A new chirp scaling algorithm of bistatic SAR with parallel flight paths
Li, Ning; Wang, Luping
2011-10-01
The precise point target reference spectrum of bistatic SAR has been a difficult problem for a long time. Many of the current available algorithms have approximation during deducing. This paper deduces the precise expression in Doppler- Frequency domain with the configuration of parallel flight paths and constant velocity of each platform. Then a new chirp scaling algorithm is put forward. At last, simulations are given to demonstrate the good focusing performance.
IMMUNE GENETIC ALGORITHM FOR THE PATH PLANNING OF TIGHTLY COORDINATED TWO-ROBOT MANIPULATORS
Gao Sheng; Zhao Jie; Cai Hegao
2004-01-01
A novel algorithm, the immune genetic algorithm based on multi-agent, is proposed for the path planning of tightly coordinated two-robot manipulators, which constructs mainly immune operators accomplished by three steps: defining strategies and methods of multi-agent, calculating virtual forces acting on an agent, and constructing immune operators and performing immunization during the evolutionary process. It is illustrated to be able to restrain the degenerate phenomenon effectively and improve the searching ability with high converging speed.
Topological studies on IRC paths of the isomerization reaction of silicon methyl- nitrene
石彦波; 郑世钧; 孟令鹏
1999-01-01
On the basis of kinetic study of isomerization reaction of H3Si-N, ab initio （RHF, UHF/6-31G） calculations on some points of the singlet and triplet reaction paths were carried out. The breakage and formation of chemical bond in the reaction are discussed. The calculated results show that there is a transitional structure of three-membered ring on each of reaction paths. A ’structural transition region’ and a ’structural transition state’ in both of studied reaction are found. Our previous conclusion that the structure transition state （STS） always appears before the energy transition state （ETS） in endothermic reaction and after ETS in exothermic reaction is further confirmed. The relationship between the change of spin density distribution and the structural transition state are investigated.
Interactive Learning Environment for Bio-Inspired Optimization Algorithms for UAV Path Planning
Duan, Haibin; Li, Pei; Shi, Yuhui; Zhang, Xiangyin; Sun, Changhao
2015-01-01
This paper describes the development of BOLE, a MATLAB-based interactive learning environment, that facilitates the process of learning bio-inspired optimization algorithms, and that is dedicated exclusively to unmanned aerial vehicle path planning. As a complement to conventional teaching methods, BOLE is designed to help students consolidate the…
Evolutionary algorithm based offline/online path planner for UAV navigation.
Nikolos, I K; Valavanis, K P; Tsourveloudis, N C; Kostaras, A N
2003-01-01
An evolutionary algorithm based framework, a combination of modified breeder genetic algorithms incorporating characteristics of classic genetic algorithms, is utilized to design an offline/online path planner for unmanned aerial vehicles (UAVs) autonomous navigation. The path planner calculates a curved path line with desired characteristics in a three-dimensional (3-D) rough terrain environment, represented using B-spline curves, with the coordinates of its control points being the evolutionary algorithm artificial chromosome genes. Given a 3-D rough environment and assuming flight envelope restrictions, two problems are solved: i) UAV navigation using an offline planner in a known environment, and, ii) UAV navigation using an online planner in a completely unknown environment. The offline planner produces a single B-Spline curve that connects the starting and target points with a predefined initial direction. The online planner, based on the offline one, is given on-board radar readings which gradually produces a smooth 3-D trajectory aiming at reaching a predetermined target in an unknown environment; the produced trajectory consists of smaller B-spline curves smoothly connected with each other. Both planners have been tested under different scenarios, and they have been proven effective in guiding an UAV to its final destination, providing near-optimal curved paths quickly and efficiently.
Energy optimization based path selection algorithm for IEEE 802.11s wireless mesh networks
Mhlanga, MM
2011-09-01
Full Text Available when the network is deployed in rural areas where electricity is a scarce resource. This research therefore presents an energy optimization based path selection algorithm for IEEE 802.11s WMNs which is aimed at addressing the above mentioned constrains...
An improved real-time endovascular guidewire position simulation using shortest path algorithm.
Qiu, Jianpeng; Qu, Zhiyi; Qiu, Haiquan; Zhang, Xiaomin
2016-09-01
In this study, we propose a new graph-theoretical method to simulate guidewire paths inside the carotid artery. The minimum energy guidewire path can be obtained by applying the shortest path algorithm, such as Dijkstra's algorithm for graphs, based on the principle of the minimal total energy. Compared to previous results, experiments of three phantoms were validated, revealing that the first and second phantoms overlap completely between simulated and real guidewires. In addition, 95 % of the third phantom overlaps completely, and the remaining 5 % closely coincides. The results demonstrate that our method achieves 87 and 80 % improvements for the first and third phantoms under the same conditions, respectively. Furthermore, 91 % improvements were obtained for the second phantom under the condition with reduced graph construction complexity.
A Minimum-energy Path-preserving Topology Control Algorithm for Wireless Sensor Networks
Jin-Zhao Lin; Xian Zhou; Yun Li
2009-01-01
The topology control strategies of wireless sensor networks are very important for reducing the energy consumption of sensor nodes and prolonging the life-span of networks. In this paper, we put forward a minimum-energy path-preserving topology control (MPTC) algorithm based on a concept of none k-redundant edges. MPTC not only resolves the problem of excessive energy consumption because of the unclosed region in small minimum-energy communication network (SMECN), but also preserves at least one minimum-energy path between every pair of nodes in a wireless sensor network. We also propose an energy-efficient reconfiguration protocol that maintains the minimum-energy path property in the case where the network topology changes dynamically. Finally, we demonstrate the performance improvements of our algorithm through simulation.
Rare events via multiple reaction channels sampled by path replica exchange
Bolhuis, P.G.
2008-01-01
Transition path sampling (TPS) was developed for studying activated processes in complex systems with unknown reaction coordinate. Transition interface sampling (TIS) allows efficient evaluation of the rate constants. However, when the transition can occur via more than one reaction channel separate
Liu, Wei; Ma, Shunjian; Sun, Mingwei; Yi, Haidong; Wang, Zenghui; Chen, Zengqiang
2016-08-01
Path planning plays an important role in aircraft guided systems. Multiple no-fly zones in the flight area make path planning a constrained nonlinear optimization problem. It is necessary to obtain a feasible optimal solution in real time. In this article, the flight path is specified to be composed of alternate line segments and circular arcs, in order to reformulate the problem into a static optimization one in terms of the waypoints. For the commonly used circular and polygonal no-fly zones, geometric conditions are established to determine whether or not the path intersects with them, and these can be readily programmed. Then, the original problem is transformed into a form that can be solved by the sequential quadratic programming method. The solution can be obtained quickly using the Sparse Nonlinear OPTimizer (SNOPT) package. Mathematical simulations are used to verify the effectiveness and rapidity of the proposed algorithm.
Plumlee, G. S.; Ridley, W. I.; Debraal, J. D.; Reed, M. H.
1993-01-01
Chemical reaction path calculations were used to model the minerals that might have formed at or near the Martian surface as a result of volcano or meteorite impact driven hydrothermal systems; weathering at the Martian surface during an early warm, wet climate; and near-zero or sub-zero C brine-regolith reactions in the current cold climate. Although the chemical reaction path calculations carried out do not define the exact mineralogical evolution of the Martian surface over time, they do place valuable geochemical constraints on the types of minerals that formed from an aqueous phase under various surficial and geochemically complex conditions.
Adaptive genetic algorithm for path planning of loosely coordinated multi-robot manipulators
高胜; 赵杰; 蔡鹤皋
2003-01-01
Adaptive genetic algorithm ASAGA, a novel algorithm, which can dynamically modify the parameters of Genetic Algorithms in terms of simulated annealing mechanism, is proposed for path planning of loosely coordinated multi-robot manipulators. Over the task space of a multi-robot, a strategy of decoupled planning is also applied to the evolutionary process, which enables a multi-robot to avoid falling into deadlock and calculating of composite C-space. Finally, two representative tests are given to validate ASA GA and the strategy of decoupled planning.
DFT study on adduct reaction paths of GaN MOCVD growth
SHI; JunCao; ZUO; Ran; MENG; SuCi
2013-01-01
The adduct reaction paths for GaN growth by metal organic chemical vapor deposition (MOCVD) were studied by quantum chemical calculations employing density functional theory (DFT). Five possible adduct reaction paths with or without the ex-cess NH3were proposed and the corresponding potential energy surfaces were calculated. From the calculation results, it is concluded that after the formation of DMGNH2from TMG:NH3, the further decomposition paths have very slim probability because of the high energy barriers; whereas the oligomerization pathway to form oligomers [DMGNH2]x(x=2, 3) is probable,because of zero energy barrier. Since the oligomers tend to further polymerize, the nanoparticles are easily formed through this path. When NH3is in excess, TMG:NH3 tends to combine with the second NH3to form two new complexes: the coordination-bonded compound H3N:TMG:NH3and the hydrogen-bonded compound TMG:NH3 NH3. The formation of hydrogen-bonded compound TMG:NH3 NH3 will be more probable because of the lower energy than H3N:TMG:NH3. By comparing the potential energy surfaces in five adduct reaction paths, we postulate that, under the growth conditions of GaN MOCVD, the formation of hydrogen-bonded compound TMG:NH3 NH3 followed by the reversible decomposition may be the main reaction path for GaN thin film growth; while the adduct oligomerization path to generate oligomers [DMGNH2]2 and [DMGNH2]3might be the main reaction path for nanoparticles formation.
All-pairs Shortest Path Algorithm based on MPI+CUDA Distributed Parallel Programming Model
Qingshuang Wu
2013-12-01
Full Text Available In view of the problem that computing shortest paths in a graph is a complex and time-consuming process, and the traditional algorithm that rely on the CPU as computing unit solely can't meet the demand of real-time processing, in this paper, we present an all-pairs shortest paths algorithm using MPI+CUDA hybrid programming model, which can take use of the overwhelming computing power of the GPU cluster to speed up the processing. This proposed algorithm can combine the advantages of MPI and CUDA programming model, and can realize two-level parallel computing. In the cluster-level, we take use of the MPI programming model to achieve a coarse-grained parallel computing between the computational nodes of the GPU cluster. In the node-level, we take use of the CUDA programming model to achieve a GPU-accelerated fine grit parallel computing in each computational node internal. The experimental results show that the MPI+CUDA-based parallel algorithm can take full advantage of the powerful computing capability of the GPU cluster, and can achieve about hundreds of time speedup; The whole algorithm has good computing performance, reliability and scalability, and it is able to meet the demand of real-time processing of massive spatial shortest path analysis
Zhou Feng
2013-09-01
Full Text Available A based on Rapidly-exploring Random Tree(RRT and Particle Swarm Optimizer (PSO for path planning of the robot is proposed.First the grid method is built to describe the working space of the mobile robot,then the Rapidly-exploring Random Tree algorithm is used to obtain the global navigation path,and the Particle Swarm Optimizer algorithm is adopted to get the better path.Computer experiment results demonstrate that this novel algorithm can plan an optimal path rapidly in a cluttered environment.The successful obstacle avoidance is achieved,and the model is robust and performs reliably.
Zheng, Jingjing; Truhlar, Donald G
2012-01-01
Complex molecules often have many structures (conformations) of the reactants and the transition states, and these structures may be connected by coupled-mode torsions and pseudorotations; some but not all structures may have hydrogen bonds in the transition state or reagents. A quantitative theory of the reaction rates of complex molecules must take account of these structures, their coupled-mode nature, their qualitatively different character, and the possibility of merging reaction paths at high temperature. We have recently developed a coupled-mode theory called multi-structural variational transition state theory (MS-VTST) and an extension, called multi-path variational transition state theory (MP-VTST), that includes a treatment of the differences in the multi-dimensional tunneling paths and their contributions to the reaction rate. The MP-VTST method was presented for unimolecular reactions in the original paper and has now been extended to bimolecular reactions. The MS-VTST and MP-VTST formulations of variational transition state theory include multi-faceted configuration-space dividing surfaces to define the variational transition state. They occupy an intermediate position between single-conformation variational transition state theory (VTST), which has been used successfully for small molecules, and ensemble-averaged variational transition state theory (EA-VTST), which has been used successfully for enzyme kinetics. The theories are illustrated and compared here by application to three thermal rate constants for reactions of ethanol with hydroxyl radical--reactions with 4, 6, and 14 saddle points.
a Modified Genetic Algorithm for Finding Fuzzy Shortest Paths in Uncertain Networks
Heidari, A. A.; Delavar, M. R.
2016-06-01
In realistic network analysis, there are several uncertainties in the measurements and computation of the arcs and vertices. These uncertainties should also be considered in realizing the shortest path problem (SPP) due to the inherent fuzziness in the body of expert's knowledge. In this paper, we investigated the SPP under uncertainty to evaluate our modified genetic strategy. We improved the performance of genetic algorithm (GA) to investigate a class of shortest path problems on networks with vague arc weights. The solutions of the uncertain SPP with considering fuzzy path lengths are examined and compared in detail. As a robust metaheuristic, GA algorithm is modified and evaluated to tackle the fuzzy SPP (FSPP) with uncertain arcs. For this purpose, first, a dynamic operation is implemented to enrich the exploration/exploitation patterns of the conventional procedure and mitigate the premature convergence of GA technique. Then, the modified GA (MGA) strategy is used to resolve the FSPP. The attained results of the proposed strategy are compared to those of GA with regard to the cost, quality of paths and CPU times. Numerical instances are provided to demonstrate the success of the proposed MGA-FSPP strategy in comparison with GA. The simulations affirm that not only the proposed technique can outperform GA, but also the qualities of the paths are effectively improved. The results clarify that the competence of the proposed GA is preferred in view of quality quantities. The results also demonstrate that the proposed method can efficiently be utilized to handle FSPP in uncertain networks.
Model Algorithm Research on Cooling Path Control of Hot-rolled Dual-phase Steel
Xiao-qing XU; Xiao-dong HAO; Shi-guang ZHOU; Chang-sheng LIU; Qi-fu ZHANG
2016-01-01
With the development of advanced high strength steel,especially for dual-phase steel,the model algorithm for cooling control after hot rolling has to achieve the targeted coiling temperature control at the location of downcoiler whilst maintaining the cooling path control based on strip microstructure along the whole cooling section.A cooling path control algorithm was proposed for the laminar cooling process as a solution to practical difficulties associated with the realization of the thermal cycle during cooling process.The heat conduction equation coupled with the carbon diffusion equation with moving boundary was employed in order to simulate temperature change and phase transfor-mation kinetics,making it possible to observe the temperature field and the phase fraction of the strip in real time. On this basis,an optimization method was utilized for valve settings to ensure the minimum deviations between the predicted and actual cooling path of the strip,taking into account the constraints of the cooling equipment′s specific capacity,cooling line length,etc.Results showed that the model algorithm was able to achieve the online cooling path control for dual-phase steel.
Rao, Akshay; Elara, Mohan Rajesh; Elangovan, Karthikeyan
This paper aims to develop a local path planning algorithm for a bio-inspired, reconfigurable crawling robot. A detailed description of the robotic platform is first provided, and the suitability for deployment of each of the current state-of-the-art local path planners is analyzed after an extensive literature review. The Enhanced Vector Polar Histogram algorithm is described and reformulated to better fit the requirements of the platform. The algorithm is deployed on the robotic platform in crawling configuration and favorably compared with other state-of-the-art local path planning algorithms.
Statistical reliability and path diversity based PageRank algorithm improvements
Hong, Dohy
2012-01-01
In this paper we present new improvement ideas of the original PageRank algorithm. The first idea is to introduce an evaluation of the statistical reliability of the ranking score of each node based on the local graph property and the second one is to introduce the notion of the path diversity. The path diversity can be exploited to dynamically modify the increment value of each node in the random surfer model or to dynamically adapt the damping factor. We illustrate the impact of such modifications through examples and simple simulations.
3D Environment Mapping Using the Kinect V2 and Path Planning Based on RRT Algorithms
Wilbert G. Aguilar
2016-10-01
Full Text Available This paper describes a 3D path planning system that is able to provide a solution trajectory for the automatic control of a robot. The proposed system uses a point cloud obtained from the robot workspace, with a Kinect V2 sensor to identify the interest regions and the obstacles of the environment. Our proposal includes a collision-free path planner based on the Rapidly-exploring Random Trees variant (RRT*, for a safe and optimal navigation of robots in 3D spaces. Results on RGB-D segmentation and recognition, point cloud processing, and comparisons between different RRT* algorithms, are presented.
Geochemical controls on shale groundwaters: Results of reaction path modeling
Von Damm, K.L.; VandenBrook, A.J.
1989-03-01
The EQ3NR/EQ6 geochemical modeling code was used to simulate the reaction of several shale mineralogies with different groundwater compositions in order to elucidate changes that may occur in both the groundwater compositions, and rock mineralogies and compositions under conditions which may be encountered in a high-level radioactive waste repository. Shales with primarily illitic or smectitic compositions were the focus of this study. The reactions were run at the ambient temperatures of the groundwaters and to temperatures as high as 250/degree/C, the approximate temperature maximum expected in a repository. All modeling assumed that equilibrium was achieved and treated the rock and water assemblage as a closed system. Graphite was used as a proxy mineral for organic matter in the shales. The results show that the presence of even a very small amount of reducing mineral has a large influence on the redox state of the groundwaters, and that either pyrite or graphite provides essentially the same results, with slight differences in dissolved C, Fe and S concentrations. The thermodynamic data base is inadequate at the present time to fully evaluate the speciation of dissolved carbon, due to the paucity of thermodynamic data for organic compounds. In the illitic cases the groundwaters resulting from interaction at elevated temperatures are acid, while the smectitic cases remain alkaline, although the final equilibrium mineral assemblages are quite similar. 10 refs., 8 figs., 15 tabs.
An Efficient Chemical Reaction Optimization Algorithm for Multiobjective Optimization.
Bechikh, Slim; Chaabani, Abir; Ben Said, Lamjed
2015-10-01
Recently, a new metaheuristic called chemical reaction optimization was proposed. This search algorithm, inspired by chemical reactions launched during collisions, inherits several features from other metaheuristics such as simulated annealing and particle swarm optimization. This fact has made it, nowadays, one of the most powerful search algorithms in solving mono-objective optimization problems. In this paper, we propose a multiobjective variant of chemical reaction optimization, called nondominated sorting chemical reaction optimization, in an attempt to exploit chemical reaction optimization features in tackling problems involving multiple conflicting criteria. Since our approach is based on nondominated sorting, one of the main contributions of this paper is the proposal of a new quasi-linear average time complexity quick nondominated sorting algorithm; thereby making our multiobjective algorithm efficient from a computational cost viewpoint. The experimental comparisons against several other multiobjective algorithms on a variety of benchmark problems involving various difficulties show the effectiveness and the efficiency of this multiobjective version in providing a well-converged and well-diversified approximation of the Pareto front.
Adjoint LMS (ALMS Algorithm Based Active Noise Control with Feedback Path Modeling
U Ramachandraiah,
2010-12-01
Full Text Available In active noise control (ANC systems, there exists an inherent feedback from the loudspeaker to the primary microphone. Adjoint least mean square (ALMS algorithm is known to be an alternative to the widely used filtered x LMS (FxLMS for reducing the computational complexity and memory requirements, especially in the case of multi-channel systems. Further FxLMS algorithm is based on the assumptionthat the order of the weighing filter and secondary path can be commuted which is not always true in practice. Though ALMS do not make such an assumption, neither FxLMS nor the ALMS algorithms onsider the feedback path effect that is inherent in ANC systems.We propose a feedback ANC system based on ALMS algorithm which is analogous to the system based on FxLMS. Detailed computational complexity analysis for addition and multiplication requirements ispresented and are compared with those of its counterpart to establish its usefulness. Simulation results show the convergence characteristics of the ALMS based ANC with feedback path modeling is on par with that based on FxLMS.
Speed-up hyperspheres homotopic path tracking algorithm for PWL circuits simulations.
Ramirez-Pinero, A; Vazquez-Leal, H; Jimenez-Fernandez, V M; Sedighi, H M; Rashidi, M M; Filobello-Nino, U; Castaneda-Sheissa, R; Huerta-Chua, J; Sarmiento-Reyes, L A; Laguna-Camacho, J R; Castro-Gonzalez, F
2016-01-01
In the present work, we introduce an improved version of the hyperspheres path tracking method adapted for piecewise linear (PWL) circuits. This enhanced version takes advantage of the PWL characteristics from the homotopic curve, achieving faster path tracking and improving the performance of the homotopy continuation method (HCM). Faster computing time allows the study of complex circuits with higher complexity; the proposed method also decrease, significantly, the probability of having a diverging problem when using the Newton-Raphson method because it is applied just twice per linear region on the homotopic path. Equilibrium equations of the studied circuits are obtained applying the modified nodal analysis; this method allows to propose an algorithm for nonlinear circuit analysis. Besides, a starting point criteria is proposed to obtain better performance of the HCM and a technique for avoiding the reversion phenomenon is also proposed. To prove the efficiency of the path tracking method, several cases study with bipolar (BJT) and CMOS transistors are provided. Simulation results show that the proposed approach can be up to twelve times faster than the original path tracking method and also helps to avoid several reversion cases that appears when original hyperspheres path tracking scheme was employed.
Optimal Path Planning Program for Autonomous Speed Sprayer in Orchard Using Order-Picking Algorithm
Park, T. S.; Park, S. J.; Hwang, K. Y.; Cho, S. I.
This study was conducted to develop a software program which computes optimal path for autonomous navigation in orchard, especially for speed sprayer. Possibilities of autonomous navigation in orchard were shown by other researches which have minimized distance error between planned path and performed path. But, research of planning an optimal path for speed sprayer in orchard is hardly founded. In this study, a digital map and a database for orchard which contains GPS coordinate information (coordinates of trees and boundary of orchard) and entity information (heights and widths of trees, radius of main stem of trees, disease of trees) was designed. An orderpicking algorithm which has been used for management of warehouse was used to calculate optimum path based on the digital map. Database for digital map was created by using Microsoft Access and graphic interface for database was made by using Microsoft Visual C++ 6.0. It was possible to search and display information about boundary of an orchard, locations of trees, daily plan for scattering chemicals and plan optimal path on different orchard based on digital map, on each circumstance (starting speed sprayer in different location, scattering chemicals for only selected trees).
Calibration of neural networks using genetic algorithms, with application to optimal path planning
Smith, Terence R.; Pitney, Gilbert A.; Greenwood, Daniel
1987-01-01
Genetic algorithms (GA) are used to search the synaptic weight space of artificial neural systems (ANS) for weight vectors that optimize some network performance function. GAs do not suffer from some of the architectural constraints involved with other techniques and it is straightforward to incorporate terms into the performance function concerning the metastructure of the ANS. Hence GAs offer a remarkably general approach to calibrating ANS. GAs are applied to the problem of calibrating an ANS that finds optimal paths over a given surface. This problem involves training an ANS on a relatively small set of paths and then examining whether the calibrated ANS is able to find good paths between arbitrary start and end points on the surface.
Multi-robot path planning in a dynamic environment using improved gravitational search algorithm
P.K. Das
2016-09-01
Full Text Available This paper proposes a new methodology to optimize trajectory of the path for multi-robots using improved gravitational search algorithm (IGSA in a dynamic environment. GSA is improved based on memory information, social, cognitive factor of PSO (particle swarm optimization and then, population for next generation is decided by the greedy strategy. A path planning scheme has been developed using IGSA to optimally obtain the succeeding positions of the robots from the existing position. Finally, the analytical and experimental results of the multi-robot path planning have been compared with those obtained by IGSA, GSA and PSO in a similar environment. The simulation and the Khepera environmental results outperform IGSA as compared to GSA and PSO with respect to performance matrix.
WANG Weizhong; ZHAO Jie; GAO Yongsheng; CAI Hegao
2006-01-01
A novel approach for collision-free path planning of a multiple degree-of-freedom (DOF)articulated robot in a complex environment is proposed. Firstly, based on visual neighbor point (VNP), a numerical artificial potential field is constructed in Cartesian space, which provides the heuristic information, effective distance to the goal and the motion direction for the motion of the robot joints. Secondly, a genetic algorithm, combined with the heuristic rules, is used in joint space to determine a series of contiguous configurations piecewise fiom initial configuration until the goal configuration is attained. A simulation shows that the method can not only handle issues on path planning of the articulated robots in environment with complex obstacles, but also improve the efficiency and quality of path planning.
无人机航路规划算法研究%Path Planning Algorithm for UAV
叶文; 廉华耕; 漆云海; 陈海生; 赵方义
2011-01-01
It was proposed to use cellular ant algorithm in path planning of Unmanned Aerial Vehicle (UAV). A series of improvements were made in cellular ant algorithm on the basis of the basic ant colony algorithm. Then the improved ant colony algorithm was used together with evolutionary rule of cellular in cellular space. The simulation results showed that the cellular ant algorithm could help the solutions to escape from their local optimum and could find a better path at higher convergence speed and with a higher precision. Therefore, the cellular ant algorithm is an effective method for such kind of multi-objective optimization problems with multiple constraints as UAV path planning under complex environment.%针对无人机航路规划问题,研究了一种基于元胞蚂蚁算法的无人机航路规划方法.元胞蚂蚁算法对基本蚁群算法进行了系列改进,并将元胞邻居演化和改进后的蚂蚁寻优相结合,有效地克服了基本蚁群算法的收敛速度慢、易于过早陷入局部最优的缺点,提高了算法的运算精度,从而为解决复杂战场环境下无人机航路规划这一多约束多目标优化问题提供了一条可行的途径.
Cutting path as a Rural Postman Problem: solutions by Memetic Algorithms
Ana Maria Rodrigues
2012-01-01
Full Text Available The Rural Postman Problem (RPP is a particular Arc Routing Problem (ARP which consists of determining a minimum cost circuit on a graph so that a given subset of required edges is traversed. The RPP is an NP-hard problem with significant real-life applications. This paper introduces an original approach based on Memetic Algorithms - the MARP algorithm - to solve the RPP and, also deals with an interesting Industrial Application, which focuses on the path optimization for component cutting operations. Memetic Algorithms are a class of Metaheuristics which may be seen as a population strategy that involves cooperation and competition processes between population elements and integrates “social knowledge”, using a local search procedure. The MARP algorithm is tested with different groups of instances and the results are compared with those gathered from other publications. MARP is also used in the context of various real-life applications.
Zhao, Tuo; Liu, Han
2016-01-01
We propose an accelerated path-following iterative shrinkage thresholding algorithm (APISTA) for solving high dimensional sparse nonconvex learning problems. The main difference between APISTA and the path-following iterative shrinkage thresholding algorithm (PISTA) is that APISTA exploits an additional coordinate descent subroutine to boost the computational performance. Such a modification, though simple, has profound impact: APISTA not only enjoys the same theoretical guarantee as that of PISTA, i.e., APISTA attains a linear rate of convergence to a unique sparse local optimum with good statistical properties, but also significantly outperforms PISTA in empirical benchmarks. As an application, we apply APISTA to solve a family of nonconvex optimization problems motivated by estimating sparse semiparametric graphical models. APISTA allows us to obtain new statistical recovery results which do not exist in the existing literature. Thorough numerical results are provided to back up our theory. PMID:28133430
Finding Community Structure in Networks Using a Shortest-Path-Based k-Means Algorithm
Jinglu GAO
2013-01-01
We consider the problem of detecting the community structure in a complex network,groups of nodes with a higher-than-average density of edges connecting them.In this paper we use the simulated annealing strategy to maximize the modularity,which has been indicated as a robust benefit function,associating with a shortest-path-based k-means iterative procedure for network partition.The proposed algorithm can not only find the communities,but also identify the nodes which occupy central positions under the metric of the shortest path within the communities to which they belong.The optimal number of communities can be automatically determined without any prior knowledge about the network structure.The applications to both artificial and real-world networks demonstrate the effectiveness of our algorithm.
A genetic algorithm for the pareto optimal solution set of multi-objective shortest path problem
HU Shi-cheng; XU Xiao-fei; ZHAN De-chen
2005-01-01
Unlike the shortest path problem that has only one optimal solution and can be solved in polynomial time, the multi-objective shortest path problem (MSPP) has a set of pareto optimal solutions and cannot be solved in polynomial time. The present algorithms focused mainly on how to obtain a precisely pareto optimal solution for MSPP resulting in a long time to obtain multiple pareto optimal solutions with them. In order to obtain a set of satisfied solutions for MSPP in reasonable time to meet the demand of a decision maker, a genetic algorithm MSPP-GA is presented to solve the MSPP with typically competing objectives, cost and time, in this paper. The encoding of the solution and the operators such as crossover, mutation and selection are developed.The algorithm introduced pareto domination tournament and sharing based selection operator, which can not only directly search the pareto optimal frontier but also maintain the diversity of populations in the process of evolutionary computation. Experimental results show that MSPP-GA can obtain most efficient solutions distributed all along the pareto frontier in less time than an exact algorithm. The algorithm proposed in this paper provides a new and effective method of how to obtain the set of pareto optimal solutions for other multiple objective optimization problems in a short time.
Reaction paths of the water-assisted solvolysis of N,N-dimethylformamide.
Tsuchida, Noriko; Satou, Harumi; Yamabe, Shinichi
2007-07-19
Density functional theory calculations were conducted on the title reactions with explicit inclusion of a variety of water molecules, H-CO-NMe2+MeOH+(H2O)n-->H-CO-OMe+HNMe2+(H2O)n. Geometries of transition states, reactant-like complexes and product-like ones were determined by the use of RB3LYP/6-31G(d) SCRF=dipole. Concerted paths were examined with n=0-3. Their Gibbs activation energies are larger than the experimental value. Stepwise paths were also investigated with n=2-4. The n=4 model has the energy close to the experimental value. However, when the catalytic water molecules were added to the n=4 one, the stepwise path was switched to the concerted one. A systematic comparison of the concerted path with n=2+1, 2+2, 2+3, 2+4, 2+5, 2+4+4, and 2+5+5 models was made, and the water-dimer based reaction path was found to be most favorable. The contrast between the concerted path of the amide solvolysis (and hydrolysis) and the stepwise one of the ester hydrolysis was discussed in terms of the frontier-orbital theory.
Gorbenko, Anna; Popov, Vladimir
2017-07-01
Different planning problems for robotic remote laser welding are of considerable interest. In this paper, we consider the problem of integrated task sequencing and path planning for robotic remote laser welding. We propose an efficient approach to solve the problem. In particular, we consider an explicit reduction from the decision version of the problem to the satisfiability problem. We present the results of computational experiments for different satisfiability algorithms.
Path planning algorithms for a multi-robot framework on an agricultural environment
Hameed, Ibrahim
2016-01-01
the fertility of the soil. This is a significant threat to soil in Europe. Compacted soils require more than a decade of expensive treatment to recover its fertility. The problem can be solved by replacing heavy tractors with a number of smaller vehicles which can treat crop fields just as well and without...... Control Center and Intelligent Coverage Path Planning algorithms to enable team members to communicate and cooperate, and solve a range of agricultural tasks in a safe and efficient way....
Minyaev, Ruslan M.; Quapp, Wolfgang; Schmidt, Benjamin; Getmanskii, Ilya V.; Koval, Vitaliy V.
2013-11-01
Quantum chemical (CCSD(full)/6-311++G(3df,3pd), CCSD(T)(full)/6-311++G(3df,3pd)) and density function theory (B3LYP/6-311++G(3df,3pd)) calculations were performed for the SN2 nucleophile substitution reactions CH4 + H- → CH4 + H- and CH4 + F- → CH3F + H-. The calculated gradient reaction pathways for both reactions have an unusual behavior. An unusual stationary point of index 2 lies on the gradient reaction path. Using Newton trajectories for the reaction path, we can detect VRI point at which the reaction path branches.
The Exact Euclidean Distance Transform: A New Algorithm for Universal Path Planning
Juan Carlos Elizondo-Leal
2013-06-01
Full Text Available The Path‐Planning problem is a basic issue in mobile robotics, in order to allow the robots to solve more complex tasks, for example, an exploration assignment in which the distance given by the planner is taken as a utility measure. Among the different proposed approaches, algorithms based on an exact cell decomposition of the environment are very popular. In this paper, we present a new algorithm for universal path planning in cell decomposition, using a raster scan method for computing the Exact Euclidean Distance Transform (EEDT for each cell in the map. Our algorithm computes, for every cell in the map, the point sequence to the goal. For each sequence, the sub‐goals are selected near to the vertices of the obstacles, reducing the total distance to the goal without post processing. At the end, we obtain a smooth path up to the goal without the need for post‐processing. The paths are computed by visibility verification among the cells, exploiting the processing performed in the neighbouring cells.
An efficient algorithm for the vertex-disjoint paths problem in random graphs
Broder, A.Z. [Digital Systems Research Center, Palo Alto, CA (United States); Frieze, A.M.; Suen, S. [Carnegie-Mellon Univ., Pittsburgh, PA (United States); Upfal, E. [IBM Almaden Research Center, San Jose, CA (United States)
1996-12-31
Given a graph G = (V, E) and a set of pairs of vertices in V, we are interested in finding for each pair (a{sub i}, b{sub i}) a path connecting a{sub i} to b{sub i}, such that the set of paths so found is vertex-disjoint. (The problem is NP-complete for general graphs as well as for planar graphs. It is in P if the number of pairs is fixed.) Our model is that the graph is chosen first, then an adversary chooses the pairs of endpoints, subject only to obvious feasibility constraints, namely, all pairs must be disjoint, no more than a constant fraction of the vertices could be required for the paths, and not {open_quotes}too many{close_quotes} neighbors of a vertex can be endpoints. We present a randomized polynomial time algorithm that works for almost all graphs; more precisely in the G{sub n,m} or G{sub n,p} models, the algorithm succeeds with high probability for all edge densities above the connectivity threshold. The set of pairs that can be accommodated is optimal up to constant factors. Although the analysis is intricate, the algorithm itself is quite simple and suggests a practical heuristic. We include two applications of the main result, one in the context of circuit switching communication, the other in the context of topological embeddings of graphs.
An efficient algorithm for finding the minimum energy path for cation migration in ionic materials.
Rong, Ziqin; Kitchaev, Daniil; Canepa, Pieremanuele; Huang, Wenxuan; Ceder, Gerbrand
2016-08-21
The Nudged Elastic Band (NEB) is an established method for finding minimum-energy paths and energy barriers of ion migration in materials, but has been hampered in its general application by its significant computational expense when coupled with density functional theory (DFT) calculations. Typically, an NEB calculation is initialized from a linear interpolation of successive intermediate structures (also known as images) between known initial and final states. However, the linear interpolation introduces two problems: (1) slow convergence of the calculation, particularly in cases where the final path exhibits notable curvature; (2) divergence of the NEB calculations if any intermediate image comes too close to a non-diffusing species, causing instabilities in the ensuing calculation. In this work, we propose a new scheme to accelerate NEB calculations through an improved path initialization and associated energy estimation workflow. We demonstrate that for cation migration in an ionic framework, initializing the diffusion path as the minimum energy path through a static potential built upon the DFT charge density reproduces the true NEB path within a 0.2 Å deviation and yields up to a 25% improvement in typical NEB runtimes. Furthermore, we find that the locally relaxed energy barrier derived from this initialization yields a good approximation of the NEB barrier, with errors within 20 meV of the true NEB value, while reducing computational expense by up to a factor of 5. Finally, and of critical importance for the automation of migration path calculations in high-throughput studies, we find that the new approach significantly enhances the stability of the calculation by avoiding unphysical image initialization. Our algorithm promises to enable efficient calculations of diffusion pathways, resolving a long-standing obstacle to the computational screening of intercalation compounds for Li-ion and multivalent batteries.
An efficient algorithm for finding the minimum energy path for cation migration in ionic materials
Rong, Ziqin; Kitchaev, Daniil; Canepa, Pieremanuele; Huang, Wenxuan; Ceder, Gerbrand
2016-08-01
The Nudged Elastic Band (NEB) is an established method for finding minimum-energy paths and energy barriers of ion migration in materials, but has been hampered in its general application by its significant computational expense when coupled with density functional theory (DFT) calculations. Typically, an NEB calculation is initialized from a linear interpolation of successive intermediate structures (also known as images) between known initial and final states. However, the linear interpolation introduces two problems: (1) slow convergence of the calculation, particularly in cases where the final path exhibits notable curvature; (2) divergence of the NEB calculations if any intermediate image comes too close to a non-diffusing species, causing instabilities in the ensuing calculation. In this work, we propose a new scheme to accelerate NEB calculations through an improved path initialization and associated energy estimation workflow. We demonstrate that for cation migration in an ionic framework, initializing the diffusion path as the minimum energy path through a static potential built upon the DFT charge density reproduces the true NEB path within a 0.2 Å deviation and yields up to a 25% improvement in typical NEB runtimes. Furthermore, we find that the locally relaxed energy barrier derived from this initialization yields a good approximation of the NEB barrier, with errors within 20 meV of the true NEB value, while reducing computational expense by up to a factor of 5. Finally, and of critical importance for the automation of migration path calculations in high-throughput studies, we find that the new approach significantly enhances the stability of the calculation by avoiding unphysical image initialization. Our algorithm promises to enable efficient calculations of diffusion pathways, resolving a long-standing obstacle to the computational screening of intercalation compounds for Li-ion and multivalent batteries.
A Distributed Mincut/Maxflow Algorithm Combining Path Augmentation and Push-Relabel
Shekhovtsov, Alexander
2011-01-01
We develop a novel distributed algorithm for the minimum cut problem. We primarily aim at solving large sparse problems. Assuming vertices of the graph are partitioned into several regions, the algorithm performs path augmentations inside the regions and updates of the push-relabel style between the regions. The interaction between regions is considered expensive (regions are loaded into the memory one-by-one or located on separate machines in a network). The algorithm works in sweeps - passes over all regions. Let $B$ be the set of vertices incident to inter-region edges of the graph. We present a sequential and parallel versions of the algorithm which terminate in at most $2|B|^2+1$ sweeps. The competing algorithm by Delong and Boykov uses push-relabel updates inside regions. In the case of a fixed partition we prove that this algorithm has a tight $O(n^2)$ bound on the number of sweeps, where $n$ is the number of vertices. We tested sequential versions of the algorithms on instances of maxflow problems in ...
An algorithm for Path planning with polygon obstacles avoidance based on the virtual circle tangents
Zahraa Y. Ibrahim
2016-12-01
Full Text Available In this paper, a new algorithm called the virtual circle tangents is introduced for mobile robot navigation in an environment with polygonal shape obstacles. The algorithm relies on representing the polygonal shape obstacles by virtual circles, and then all the possible trajectories from source to target is constructed by computing the visible tangents between the robot and the virtual circle obstacles. A new method for searching the shortest path from source to target is suggested. Two states of the simulation are suggested, the first one is the off-line state and the other is the on-line state. The introduced method is compared with two other algorithms to study its performance.
Uncertainty-Based Map Matching: The Space-Time Prism and k-Shortest Path Algorithm
Bart Kuijpers
2016-11-01
Full Text Available Location-aware devices can be used to record the positions of moving objects for further spatio-temporal data analysis. For instance, we can analyze the routes followed by a person or a group of people, to discover hidden patterns in trajectory data. Typically, the positions of moving objects are registered by GPS devices, and most of the time, the recorded positions do not match the road actually followed by the object carrying the device, due to different sources of errors. Thus, matching the moving object’s actual position to a location on a digital map is required. The problem of matching GPS-recorded positions to a road network is called map matching (MM. Although many algorithms have been proposed to solve this problem, few of them consider the uncertainty caused by the absence of information about the moving object’s position in-between consecutive recorded locations. In this paper, we study the relationship between map matching and uncertainty, and we propose a novel MM algorithm that uses space-time prisms in combination with weighted k-shortest path algorithms. We applied our algorithm to real-world cases and to computer-generated trajectory samples with a variety of properties. We compare our results against a number of well-known algorithms that we have also implemented and show that it outperforms existing algorithms, allowing us to obtain better matches, with a negligible loss in performance. In addition, we propose a novel accuracy measure that allows a better comparison between different MM algorithms. We applied this novel measure to compare our algorithm against existing algorithms.
Protein-fold recognition using an improved single-source K diverse shortest paths algorithm.
Lhota, John; Xie, Lei
2016-04-01
Protein structure prediction, when construed as a fold recognition problem, is one of the most important applications of similarity search in bioinformatics. A new protein-fold recognition method is reported which combines a single-source K diverse shortest path (SSKDSP) algorithm with Enrichment of Network Topological Similarity (ENTS) algorithm to search a graphic feature space generated using sequence similarity and structural similarity metrics. A modified, more efficient SSKDSP algorithm is developed to improve the performance of graph searching. The new implementation of the SSKDSP algorithm empirically requires 82% less memory and 61% less time than the current implementation, allowing for the analysis of larger, denser graphs. Furthermore, the statistical significance of fold ranking generated from SSKDSP is assessed using ENTS. The reported ENTS-SSKDSP algorithm outperforms original ENTS that uses random walk with restart for the graph search as well as other state-of-the-art protein structure prediction algorithms HHSearch and Sparks-X, as evaluated by a benchmark of 600 query proteins. The reported methods may easily be extended to other similarity search problems in bioinformatics and chemoinformatics. The SSKDSP software is available at http://compsci.hunter.cuny.edu/~leixie/sskdsp.html.
Optimization of the transition path of the head hardening with using the genetic algorithms
Wróbel, Joanna; Kulawik, Adam
2016-06-01
An automated method of choice of the transition path of the head hardening in heat treatment process for the plane steel element is proposed in this communication. This method determines the points on the path of moving heat source using the genetic algorithms. The fitness function of the used algorithm is determined on the basis of effective stresses and yield point depending on the phase composition. The path of the hardening tool and also the area of the heat affected zone is determined on the basis of obtained points. A numerical model of thermal phenomena, phase transformations in the solid state and mechanical phenomena for the hardening process is implemented in order to verify the presented method. A finite element method (FEM) was used for solving the heat transfer equation and getting required temperature fields. The moving heat source is modeled with a Gaussian distribution and the water cooling is also included. The macroscopic model based on the analysis of the CCT and CHT diagrams of the medium-carbon steel is used to determine the phase transformations in the solid state. A finite element method is also used for solving the equilibrium equations giving us the stress field. The thermal and structural strains are taken into account in the constitutive relations.
Self-consistent collective coordinate for reaction path and inertial mass
Wen, Kai
2016-01-01
We propose a numerical method to determine the optimal collective reaction path for the nucleus-nucleus collision, based on the adiabatic self-consistent collective coordinate (ASCC) method. We use an iterative method combining the imaginary-time evolution and the finite amplitude method, for the solution of the ASCC coupled equations. It is applied to the simplest case, the $\\alpha-\\alpha$ scattering. We determine the collective path, the potential, and the inertial mass. The results are compared with other methods, such as the constrained Hartree-Fock method, the Inglis's cranking formula, and the adiabatic time-dependent Hartree-Fock (ATDHF) method.
A Multiobjective Optimization Algorithm for QoS-Aware Path Selection in DiffServ and MPLS Networks
无
2006-01-01
A multiobjective quality of service (QoS) routing algorithm was proposed and used as the QoS-aware path selection approach in differentiated services and multi-protocol label switching (DiffServ-MPLS) networks. It simultaneously optimizes multiple QoS objectives by a genetic algorithm in conjunction with concept of Pareto dominance. The simulation demonstrates that the proposed algorithm is capable of discovering a set of QoS-based near optimal paths within in a few iterations. In addition, the simulation results also show the scalability of the algorithm with increasing number of network nodes.
Jafarizadeh, Saber
2010-01-01
Providing an analytical solution for the problem of finding Fastest Distributed Consensus (FDC) is one of the challenging problems in the field of sensor networks. Most of the methods proposed so far deal with the FDC averaging algorithm problem by numerical convex optimization methods and in general no closed-form solution for finding FDC has been offered up to now except in [3] where the conjectured answer for path has been proved. Here in this work we present an analytical solution for the problem of Fastest Distributed Consensus for the Path network using semidefinite programming particularly solving the slackness conditions, where the optimal weights are obtained by inductive comparing of the characteristic polynomials initiated by slackness conditions.
EZDCP:A new static task scheduling algorithm with edge-zeroing based on dynamic critical paths
陈志刚; 华强胜
2003-01-01
A new static task scheduling algorithm named edge-zeroing based on dynamic critical paths is proposed.The main ideas of the algorithm are as follows: firstly suppose that all of the tasks are in different clusters; secondly, select one of the critical paths of the partially clustered directed acyclic graph; thirdly, try to zero one of graph communication edges; fourthly, repeat above three processes until all edges are zeroed; finally, check the generated clusters to see if some of them can be further merged without increasing the parallel time. Comparisons of the previous algorithms with edge-zeroing based on dynamic critical paths show that the new algorithm has not only a low complexity but also a desired performance comparable or even better on average to much higher complexity heuristic algorithms.
王国仁; 于戈
2002-01-01
With the emerging of new applications, especially in Web, such asCommerce,Digital Library and DNA Bank, object database systems show their stronger functions than other kinds of database systems due to their powerful representation ability on complex semantics and relationship. One distinguished feature of object databasesystems is path expression,and most queries on an objectdatabase are based on path expression because it is the most natural and convenient way to access the object database, for example, to navigate the hyperlinks in a webased database.The execution of path expression is usually extremely expensive on a very large database.Therefore,the improvement of path expression execution efficiency is criticlfor the performance of object databases. As an important approach realizing highperformance query processing,theparallel processing of path expression on distributed object databases is explored in this paper. Up to now, some algorithms about how to compute path expressions and how to optimize path expression processing havebeenproposedforcentralized environments.But,few approaches have beenpresented for computing path expressionsi parallel.Inthispaper,anewparallelalgoritm for computing path expression named Parallel Cascade Semijoin (PCS J) is proposed.Moreover,a new scheduling strategy called right-deep zigzag tree is designed to further improve the performance of the PCSJalgorithm. The experiments have been implemented in an NOW distributed and parallel environment. The results show that the PCSJ algorithm outperforms the other two parallel algorithms (the parallel version of forward pointer chasing algorithm(PFPC) and the index splitting parallel algorithm (IndexSplit)) when computing path expressions with restrictive predicates and that the rightdeep zigzag tree scheduling strategy has better performance than the rightdeep tree scheduling strategy.
A Path Select Algorithm with Error Control Schemes and Energy Efficient Wireless Sensor Networks
Sandeep Dahiya
2012-04-01
Full Text Available A wireless sensor network consists of a large number of sensor nodes that are spread densely to observe the phenomenon. The whole network lifetime relies on the lifetime of the each sensor node. If one node dies, it could lead to a separation of the sensor network. Also a multi hop structure and broadcast channel of wireless sensornecessitate error control scheme to achieve reliable data transmission. Automatic repeat request (ARQ and forward error correction (FEC are the key error control strategies in wire sensor network. In this paper we propose a path selection algorithm with error control schemes using energy efficient analysis.
The Forward-Reverse Algorithm for Stochastic Reaction Networks
Bayer, Christian
2015-01-07
In this work, we present an extension of the forward-reverse algorithm by Bayer and Schoenmakers [2] to the context of stochastic reaction networks (SRNs). We then apply this bridge-generation technique to the statistical inference problem of approximating the reaction coefficients based on discretely observed data. To this end, we introduce a two-phase iterative inference method in which we solve a set of deterministic optimization problems where the SRNs are replaced by the classical ODE rates; then, during the second phase, the Monte Carlo version of the EM algorithm is applied starting from the output of the previous phase. Starting from a set of over-dispersed seeds, the output of our two-phase method is a cluster of maximum likelihood estimates obtained by using convergence assessment techniques from the theory of Markov chain Monte Carlo.
Multiscale Reaction-Diffusion Algorithms: PDE-Assisted Brownian Dynamics
Franz, Benjamin
2013-06-19
Two algorithms that combine Brownian dynami cs (BD) simulations with mean-field partial differential equations (PDEs) are presented. This PDE-assisted Brownian dynamics (PBD) methodology provides exact particle tracking data in parts of the domain, whilst making use of a mean-field reaction-diffusion PDE description elsewhere. The first PBD algorithm couples BD simulations with PDEs by randomly creating new particles close to the interface, which partitions the domain, and by reincorporating particles into the continuum PDE-description when they cross the interface. The second PBD algorithm introduces an overlap region, where both descriptions exist in parallel. It is shown that the overlap region is required to accurately compute variances using PBD simulations. Advantages of both PBD approaches are discussed and illustrative numerical examples are presented. © 2013 Society for Industrial and Applied Mathematics.
Multiscale reaction-diffusion algorithms: PDE-assisted Brownian dynamics
Franz, Benjamin; Chapman, S Jonathan; Erban, Radek
2012-01-01
Two algorithms that combine Brownian dynamics (BD) simulations with mean-field partial differential equations (PDEs) are presented. This PDE-assisted Brownian dynamics (PBD) methodology provides exact particle tracking data in parts of the domain, whilst making use of a mean-field reaction-diffusion PDE description elsewhere. The first PBD algorithm couples BD simulations with PDEs by randomly creating new particles close to the interface which partitions the domain and by reincorporating particles into the continuum PDE-description when they cross the interface. The second PBD algorithm introduces an overlap region, where both descriptions exist in parallel. It is shown that to accurately compute variances using the PBD simulation requires the overlap region. Advantages of both PBD approaches are discussed and illustrative numerical examples are presented.
Exact and Heuristic Algorithms for Routing AGV on Path with Precedence Constraints
Liang Xu
2016-01-01
Full Text Available A new problem arises when an automated guided vehicle (AGV is dispatched to visit a set of customers, which are usually located along a fixed wire transmitting signal to navigate the AGV. An optimal visiting sequence is desired with the objective of minimizing the total travelling distance (or time. When precedence constraints are restricted on customers, the problem is referred to as traveling salesman problem on path with precedence constraints (TSPP-PC. Whether or not it is NP-complete has no answer in the literature. In this paper, we design dynamic programming for the TSPP-PC, which is the first polynomial-time exact algorithm when the number of precedence constraints is a constant. For the problem with number of precedence constraints, part of the input can be arbitrarily large, so we provide an efficient heuristic based on the exact algorithm.
APF-guided adaptive immune network algorithm for robot path planning
Mingxin YUAN; Sunan WANG; Canyang WU; Kunpeng LI
2009-01-01
Inspired by the mechanism of Jerne's idiotypic network hypothesis, a new adaptive immune network algorithm (AINA) is presented through the stimulation and suppression between the antigen and antibody by taking the environment and robot behavior as antigen and antibody respectively. A guiding weight is defined based on the artificial potential field (APF) method, and the guiding weight is combined with antibody vitality to construct a new antibody selection operator, which improves the searching efficiency. In addition, an updating operator of antibody vi-tality is provided based on the Baldwin effect, which results in a positive feedback mechanism of search and accelerates the convergence of the immune network. The simulation and experimental results show that the proposed algorithm is characterized by high searching speed, good convergence performance and strong planning ability, which solves the path planning well in complicated environments.
A heuristic path-estimating algorithm for large-scale real-time traffic information calculating
2008-01-01
As the original Global Position System (GPS) data in Floating Car Data have the accuracy problem,this paper proposes a heuristic path-estimating algorithm for large-scale real-time traffic information calculating. It uses the heuristic search method,imports the restriction with geometric operation,and makes comparison between the vectors composed of the vehicular GPS points and the special road network model to search the set of vehicular traveling route candidates. Finally,it chooses the most optimal one according to weight. Experimental results indicate that the algorithm has considerable efficiency in accuracy (over 92.7%) and com-putational speed (max 8000 GPS records per second) when handling the GPS tracking data whose sampling rate is larger than 1 min even under complex road network conditions.
Dynamic path bifurcation in the Beckmann reaction: support from kinetic analyses.
Yamamoto, Yutaro; Hasegawa, Hiroto; Yamataka, Hiroshi
2011-06-03
The reactions of oximes to amides, known as the Beckmann rearrangement, may undergo fragmentation to form carbocations + nitriles when the migrating groups have reasonable stability as cations. The reactions of oxime sulfonates of 1-substituted-phenyl-2-propanone derivatives (7-X) and related substrates (8-X, 9a-X) in aqueous CH(3)CN gave both rearrangement products (amides) and fragmentation products (alcohols), the ratio of which depends on the system; the reactions of 7-X gave amides predominantly, whereas 9a-X yielded alcohols as the major product. The logk-logk plots between the systems gave excellent linear correlations with slopes of near unity. The results support the occurrence of path bifurcation after the rate-determining TS of the Beckmann rearrangement/fragmentation reaction, which has previously been proposed on the basis of molecular dynamics simulations. It was concluded that path-bifurcation phenomenon could be more common than thought and that a reactivity-selectivity argument based on the traditional TS theory may not always be applicable even to a well-known textbook organic reaction.
Yang Liu
2016-01-01
Full Text Available This paper proposes a potential odor intensity grid based optimization approach for unmanned aerial vehicle (UAV path planning with particle swarm optimization (PSO technique. Odor intensity is created to color the area in the searching space with highest probability where candidate particles may locate. A potential grid construction operator is designed for standard PSO based on different levels of odor intensity. The potential grid construction operator generates two potential location grids with highest odor intensity. Then the middle point will be seen as the final position in current particle dimension. The global optimum solution will be solved as the average. In addition, solution boundaries of searching space in each particle dimension are restricted based on properties of threats in the flying field to avoid prematurity. Objective function is redesigned by taking minimum direction angle to destination into account and a sampling method is introduced. A paired samples t-test is made and an index called straight line rate (SLR is used to evaluate the length of planned path. Experiments are made with other three heuristic evolutionary algorithms. The results demonstrate that the proposed method is capable of generating higher quality paths efficiently for UAV than any other tested optimization techniques.
Optimal Path Design of Geared 5-bar mechanism using Differential Evolution Algorithm
Ali Aliniay Saghalaksari
2016-06-01
Full Text Available Five-bar linkage mechanisms with two degrees of freedom (DOF are more capable in generating coupler path than four-bar mechanisms with one DOF. The DOF of these mechanisms is reduced to one and they will have constant ratio of binary input when they are equipped by gear. Therefore, besides keeping the simple structure, it is possible to employ them to generate a more accurate path than that generated by four-bar mechanisms using only one input. In this study, using such mechanism for the considered paths, which are used for the comparison purpose, a singleobjective design is performed to optimize the length of mechanism links and revolution ratio of gears by considering the necessary constraints. The error function of square deviation of positions is considered as the objective function and the differential evolution algorithm is utilized in order to solve the considered optimization problems, which are Triangle Curve with 22 Discrete Points and Asteroid Curve with 41 Discrete Points. Compared with the main reference [9], the final results revealed a significant improvement.
TRAFFIC SENSITIVE AND TRAFFIC LOAD AWARE PATH SELECTION ALGORITHM FOR MMR WIMAX NETWORKS
Sandhya Kulkarni
2011-08-01
Full Text Available The recent developments in the broadband wireless access (BWA communication systems haveintroduced several major changes to the existing systems. Legacy IEEE 802.16j is one such amendment tothe existing IEEE 802.16 WiMAX family. The key modification introduced by 802.16j system is theconcept of relay station (RS, which may be used to enhance the system coverage or to make systemthroughput optimal. The end terminals, subscriber stations (SS are unchanged in the standard. Theoverall change pertinent to the system has raised many unresolved issues related to RS and multi-hoprelay base station (MR-BS. The selection of path from a SS to MR-BS via a RS is also one of the issues,need to be addressed. The path selection of a SS in both uplink and downlink directions is left open in thestandard. It is very significant to satisfy the traffics of stringent quality of service (QoS requirements andto appropriately manage the resources of a cell under different circumstances. This paper proposes apath selection algorithm to achieve the aforementioned qualities in the network. The path selectionmetrics include traffic load of the transparent relay station and traffic sensitivity factor of the SS. Anextensive simulation work discusses the performance evaluation of the proposed work using QualNetsimulator.
ReactionMap: an efficient atom-mapping algorithm for chemical reactions.
Fooshee, David; Andronico, Alessio; Baldi, Pierre
2013-11-25
Large databases of chemical reactions provide new data-mining opportunities and challenges. Key challenges result from the imperfect quality of the data and the fact that many of these reactions are not properly balanced or atom-mapped. Here, we describe ReactionMap, an efficient atom-mapping algorithm. Our approach uses a combination of maximum common chemical subgraph search and minimization of an assignment cost function derived empirically from training data. We use a set of over 259,000 balanced atom-mapped reactions from the SPRESI commercial database to train the system, and we validate it on random sets of 1000 and 17,996 reactions sampled from this pool. These large test sets represent a broad range of chemical reaction types, and ReactionMap correctly maps about 99% of the atoms and about 96% of the reactions, with a mean time per mapping of 2 s. Most correctly mapped reactions are mapped with high confidence. Mapping accuracy compares favorably with ChemAxon's AutoMapper, versions 5 and 6.1, and the DREAM Web tool. These approaches correctly map 60.7%, 86.5%, and 90.3% of the reactions, respectively, on the same data set. A ReactionMap server is available on the ChemDB Web portal at http://cdb.ics.uci.edu .
IPED: Inheritance Path-based Pedigree Reconstruction Algorithm Using Genotype Data
Wang, Zhanyong; Han, Buhm; Parida, Laxmi; Eskin, Eleazar
2013-01-01
Abstract The problem of inference of family trees, or pedigree reconstruction, for a group of individuals is a fundamental problem in genetics. Various methods have been proposed to automate the process of pedigree reconstruction given the genotypes or haplotypes of a set of individuals. Current methods, unfortunately, are very time-consuming and inaccurate for complicated pedigrees, such as pedigrees with inbreeding. In this work, we propose an efficient algorithm that is able to reconstruct large pedigrees with reasonable accuracy. Our algorithm reconstructs the pedigrees generation by generation, backward in time from the extant generation. We predict the relationships between individuals in the same generation using an inheritance path-based approach implemented with an efficient dynamic programming algorithm. Experiments show that our algorithm runs in linear time with respect to the number of reconstructed generations, and therefore, it can reconstruct pedigrees that have a large number of generations. Indeed it is the first practical method for reconstruction of large pedigrees from genotype data. PMID:24093229
Xie, XianMing; Li, YingHui
2014-06-20
This paper presents an enhanced phase unwrapping algorithm by combining an unscented Kalman filter, an enhanced local phase gradient estimator based on an amended matrix pencil model, and a path-following strategy. This technology is able to accurately unwrap seriously noisy wrapped phase images by applying the unscented Kalman filter to simultaneously perform noise suppression and phase unwrapping along the path from the high-quality region to the low-quality region of the wrapped phase images. Results obtained with synthetic data and real data validate the effectiveness of the proposed method and show improved performance of this new algorithm with respect to some of the most used algorithms.
Ting Kuo
2015-05-01
Full Text Available We propose a linear time algorithm, called G2DLP, for generating 2D lattice L(n1, n2 paths, equivalent to two-item multiset permutations, with a given number of turns. The usage of turn has three meanings: in the context of multiset permutations, it means that two consecutive elements of a permutation belong to two different items; in lattice path enumerations, it means that the path changes its direction, either from eastward to northward or from northward to eastward; in open shop scheduling, it means that we transfer a job from one type of machine to another. The strategy of G2DLP is divide-and-combine; the division is based on the enumeration results of a previous study and is achieved by aid of an integer partition algorithm and a multiset permutation algorithm; the combination is accomplished by a concatenation algorithm that constructs the paths we require. The advantage of G2DLP is twofold. First, it is optimal in the sense that it directly generates all feasible paths without visiting an infeasible one. Second, it can generate all paths in any specified order of turns, for example, a decreasing order or an increasing order. In practice, two applications, scheduling and cryptography, are discussed.
Gao, Ming-ke; Chen, Yi-min; Liu, Quan; Huang, Chen; Li, Ze-yu; Zhang, Dian-hua
2015-11-01
Preoperative path planning plays a critical role in vascular access surgery. Vascular access surgery has superior difficulties and requires long training periods as well as precise operation. Yet doctors are on different leves, thus bulky size of blood vessels is usually chosen to undergo surgery and other possible optimal path is not considered. Moreover, patients and surgeons will suffer from X-ray radiation during the surgical procedure. The study proposed an improved ant colony algorithm to plan a vascular optimal three-dimensional path with overall consideration of factors such as catheter diameter, vascular length, diameter as well as the curvature and torsion. To protect the doctor and patient from exposing to X-ray long-term, the paper adopted augmented reality technology to register the reconstructed vascular model and physical model meanwhile, locate catheter by the electromagnetic tracking system and used Head Mounted Display to show the planning path in real time and monitor catheter push procedure. The experiment manifests reasonableness of preoperative path planning and proves the reliability of the algorithm. The augmented reality experiment real time and accurately displays the vascular phantom model, planning path and the catheter trajectory and proves the feasibility of this method. The paper presented a useful and feasible surgical scheme which was based on the improved ant colony algorithm to plan vascular three-dimensional path in augmented reality. The study possessed practical guiding significance in preoperative path planning, intraoperative catheter guiding and surgical training, which provided a theoretical method of path planning for vascular access surgery. It was a safe and reliable path planning approach and possessed practical reference value.
Transition Path Sampling Study of the Reaction Catalyzed by Purine Nucleoside Phosphorylase
Saen-oon, Suwipa; Schramm, Vern L.; Schwartz, Steven D.
2010-01-01
The Transition Path Sampling (TPS) method is a powerful technique for studying rare events in complex systems, that allows description of reactive events in atomic detail without prior knowledge of reaction coordinates and transition states. We have applied TPS in combination with a hybrid Quantum Mechanical/Molecular Mechanical (QM/MM) method to study the enzyme human purine nucleoside phosphorylase (hPNP). This enzyme catalyzes the reversible phosphorolysis of 6-oxypurine (deoxy)nucleosides to generate the corresponding purine base and (deoxy)ribose 1-phosphate. Hundreds of reactive trajectories were generated. Analysis of this transition path ensembles provides insight into the detailed mechanistic dynamics of reaction in the enzyme. Our studies have indicated a reaction mechanism involving the cleavage of the N-ribosidic bond to form transition states with substantial ribooxacarbenium ion character, that is then followed by conformational changes in the enzyme and the ribosyl group leading to migration of the anomeric carbon of the ribosyl group toward phosphate to form the product ribose 1-phosphate. This latter process is crucial in PNP, because several strong H-bonds form between active site residues in order to capture and align the phosphate nucleophile. Calculations of the commitment probability along reactive paths demonstrated the presence of a broad energy barrier at the transition state. Analysis of these transition state structures showed that bond-breaking and bond-forming distances are not a good choice for the reaction coordinate, but that the pseudorotational phase of the ribose ring is also a significant variable. PMID:20664707
Walch, Stephen P.; Taylor, Peter R.
1995-01-01
The reaction of vinylidene (CH2C) with acetylene may be an initiating reaction in soot formation. We report minimum energy paths and accurate energetics for a pathway leading to vinylacetylene and for a number of isomers Of C4H4. The calculations use complete active space self-consistent field (CASSCF) derivative methods to characterize the stationary points and internally contacted configuration interaction (ICCI) and/or coupled cluster singles and doubles with a perturbational estimate of triple excitations (CCSD(T)) to determine the energetics. We find an entrance channel barrier of about 5 kcal/mol for the addition of vinylidene to acetylene, but no barriers above reactants for the reaction pathway leading to vinylacetylene.
An improved particle filtering algorithm for aircraft engine gas-path fault diagnosis
Qihang Wang
2016-07-01
Full Text Available In this article, an improved particle filter with electromagnetism-like mechanism algorithm is proposed for aircraft engine gas-path component abrupt fault diagnosis. In order to avoid the particle degeneracy and sample impoverishment of normal particle filter, the electromagnetism-like mechanism optimization algorithm is introduced into resampling procedure, which adjusts the position of the particles through simulating attraction–repulsion mechanism between charged particles of the electromagnetism theory. The improved particle filter can solve the particle degradation problem and ensure the diversity of the particle set. Meanwhile, it enhances the ability of tracking abrupt fault due to considering the latest measurement information. Comparison of the proposed method with three different filter algorithms is carried out on a univariate nonstationary growth model. Simulations on a turbofan engine model indicate that compared to the normal particle filter, the improved particle filter can ensure the completion of the fault diagnosis within less sampling period and the root mean square error of parameters estimation is reduced.
Application of GA, PSO, and ACO Algorithms to Path Planning of Autonomous Underwater Vehicles
Mohammad Pourmahmood Aghababa; Mohammad Hossein Amrollahi; Mehdi Borjkhani
2012-01-01
In this paper,an underwater vehicle was modeled with six dimensional nonlinear equations of motion,controlled by DC motors in all degrees of freedom.Near-optimal trajectories in an energetic environment for underwater vehicles were computed using a numerical solution of a nonlinear optimal control problem (NOCP).An energy performance index as a cost function,which should be minimized,was defined.The resulting problem was a two-point boundary value problem (TPBVP).A genetic algorithm (GA),particle swarm optimization (PSO),and ant colony optimization (ACO) algorithms were applied to solve the resulting TPBVP.Applying an Euler-Lagrange equation to the NOCE a conjugate gradient penalty method was also adopted to solve the TPBVP.The problem of energetic environments,involving some energy sources,was discussed.Some near-optimal paths were found using a GA,PSO,and ACO algorithms.Finally,the problem of collision avoidance in an energetic environment was also taken into account.
Bai Li
2014-01-01
Full Text Available Unmanned combat aerial vehicles (UCAVs have been of great interest to military organizations throughout the world due to their outstanding capabilities to operate in dangerous or hazardous environments. UCAV path planning aims to obtain an optimal flight route with the threats and constraints in the combat field well considered. In this work, a novel artificial bee colony (ABC algorithm improved by a balance-evolution strategy (BES is applied in this optimization scheme. In this new algorithm, convergence information during the iteration is fully utilized to manipulate the exploration/exploitation accuracy and to pursue a balance between local exploitation and global exploration capabilities. Simulation results confirm that BE-ABC algorithm is more competent for the UCAV path planning scheme than the conventional ABC algorithm and two other state-of-the-art modified ABC algorithms.
Li, Bai; Gong, Li-gang; Yang, Wen-lun
2014-01-01
Unmanned combat aerial vehicles (UCAVs) have been of great interest to military organizations throughout the world due to their outstanding capabilities to operate in dangerous or hazardous environments. UCAV path planning aims to obtain an optimal flight route with the threats and constraints in the combat field well considered. In this work, a novel artificial bee colony (ABC) algorithm improved by a balance-evolution strategy (BES) is applied in this optimization scheme. In this new algorithm, convergence information during the iteration is fully utilized to manipulate the exploration/exploitation accuracy and to pursue a balance between local exploitation and global exploration capabilities. Simulation results confirm that BE-ABC algorithm is more competent for the UCAV path planning scheme than the conventional ABC algorithm and two other state-of-the-art modified ABC algorithms.
安华良; 张丽丽; 苑保国; 赵新强; 王延吉
2014-01-01
Methyl N-phenyl carbamate (MPC), an important organic chemical, can be synthesized from aniline, CO2 and methanol. Catalyst Cu-Fe/ZrO2-SiO2 was first prepared and its catalytic performance for MPC synthesis was evaluated. Then the influence of solvent on the reaction path of MPC synthesis was investigated. It is found that the reaction intermediate is different with acetonitrile or methanol as a solvent. With acetonitrile as a solvent, the synthesis of MPC follows the reaction path with diphenyl urea as the intermediate, while with methanol as a solvent the reaction occurs via the reaction path with dimethyl carbonate as the intermediate. The catalytic mecha-nism of cooperative catalysis comprising metal sites, Lewis acid sites and Lewis base sites is proposed according to different reaction intermediates.
Xiang Gao; Yangwang Fang; Youli Wu
2013-01-01
The problem of passive detection discussed in this paper involves searching and locating an aerial emitter by dual-aircraft using passive radars. In order to improve the detection probability and accuracy, a fuzzy Q learning algorithm for dual-aircraft flight path planning is proposed. The passive detection task model of the dual-aircraft is set up based on the partition of the target active radar’s radiation area. The problem is formulated as a Markov decision process (MDP) by using the fuzzy theory to make a generalization of the state space and defining the transition functions, action space and reward function properly. Details of the path planning algorithm are presented. Simulation results indicate that the algorithm can provide adaptive strategies for dual-aircraft to control their flight paths to detect a non-maneuvering or maneu-vering target.
Nair, T R Gopalakrishnan; Yashoda, M B
2011-01-01
In Internet Routing, the static shortest path (SP) problem has been addressed using well known intelligent optimization techniques like artificial neural networks, genetic algorithms (GAs) and particle swarm optimization. Advancement in wireless communication lead more and more mobile wireless networks, such as mobile networks [mobile ad hoc networks (MANETs)] and wireless sensor networks. Dynamic nature of the network is the main characteristic of MANET. Therefore, the SP routing problem in MANET turns into dynamic optimization problem (DOP). Here the nodes ae made aware of the environmental condition, thereby making it intelligent, which goes as the input for GA. The implementation then uses GAs with immigrants and memory schemes to solve the dynamic SP routing problem (DSPRP) in MANETS. In our paper, once the network topology changes, the optimal solutions in the new environment can be searched using the new immigrants or the useful information stored in the memory. Results shows GA with new immigrants sho...
Syed Bilal Hussain Shah
2017-01-01
Full Text Available In Wireless Sensors Networks (WSNs, researcher’s main focus is on energy preservation and prolonging network lifetime. More energy resources are required in case of remote applications of WSNs, where some of the nodes die early that shorten the lifetime and decrease the stability of the network. It is mainly caused due to the non-optimal Cluster Heads (CHs selection based on single criterion and uneven distribution of energy. We propose a new clustering protocol for both homogeneous and heterogeneous environments, named as Optimized Path planning algorithm with Energy efficiency and Extending Network lifetime in WSN (OPEN. In the proposed protocol, timer value concept is used for CH selection based on multiple criteria. Simulation results prove that OPEN performs better than the existing protocols in terms of the network lifetime, throughput and stability. The results explicitly explain the cluster head selection of OPEN protocol and efficient solution of uneven energy distribution problem.
Study on an urban transportation optimal path algorithm%城市交通最优路径算法
陈亮; 何为; 韩力群
2012-01-01
城市智能交通系统中,最优路径算法及其优化是研究热点之一,是整个交通系统较为核心的部分.结合图论中最短路径算法,研究了城市交通可达路径算法,并对其进行了有效优化,通过图论中的路径代价函数,提出了城市最优路径算法,在此基础上,通过优化搜索区域、可达路径的搜索方向以及路网分层搜索等优化策略,达到了优化城市最优路径算法的目的,提出的城市最优路径及其优化算法能够给出行者提供多条参考的时间最优路线,方便出行者选择.通过算法的应用实例,验证了城市最优路径及其优化算法的有效性与实时性.%In urban intelligent transportation systems, the optimal path algorithm and its optimization are hot topic and the core of the whole transportation system. By introducing the shortest path algorithm in graph theory, this paper first researched the accessible paths for the urban transportation along with an optimization algorithm. Next, by using the path cost function, an optimal path algorithm for urban transportation was proposed. On this basis, by optimizing the search area, the search direction for accessible paths, and the road network hierarchical search optimization strategy, the goal of optimizing urban paths was attained. The proposed optimal urban path and its optimization algorithm were able to provide several time-optimal pedestrian paths for references. Through practical applications, the validity and real-time characteristics of the proposed urban optimal path and its optimization algorithm were verified.
Dmitrii D. Lozovanu
2005-10-01
Full Text Available We study the max-min paths problem, which represents a game version of the shortest and the longest paths problem in a weighted directed graph. In this problem the vertex set V of the weighted directed graph G=(V,E is divided into two disjoint subsets VA and VB which are regarded as positional sets of two players. The players are seeking for a directed path from the given starting position ν 0 to the final position ν f , where the first player intends to maximize the integral cost of the path while the second one has aim to minimize it. Polynomial-time algorithm for determining max-min path in networks is proposed and its application for solving zero value cyclic games is developed. Mathematics Subject Classification 2000: 90B10, 90C35, 90C27.
A Neural Network based Path Planning Algorithm for Extinguishing Forest Fires
M.P.Sivaram Kumar
2012-03-01
Full Text Available In this work an algorithm for automatic detection and suppression of Forest fires is proposed. The algorithm is implemented using parallel distributed model of neural network with three activation functions to determine the next consecutive moves to the cells for the actor. The algorithm uses reinforcement learning with weights determined dynamically in each iteration. The Entire forest is decomposed into grid of square cells with initial position of the Actor is assumed to be the cell 1 and the goal cell is the cell where the fire has occurred. The neural network model uses starting cell, goal cell and number of cells in each row or column and three activation functions to determine the next consecutive cells in which the robot has to travel. It uses only three movements LEFT, DIAGONAL and UP to reach the target cell. After calculating next cell, the check will be made for presence of obstacles in that cell. If there is any obstacle in that cell, then one cell from other two cells obtained using other two movements, which is free from obstacle will be chosen for next move. Then the cell number is stored in memory. This process is repeated till the next cell computed is same as the goal cell. The Actor will begin to move from start cell and reach the goal cell using the cell numbers available in the memory to extinguish Forest fire. This algorithm is designed keeping in mind only static obstacles and hence it works well for Forest environment with static obstacles. Computer simulation results show that path has been found successfully without collision with obstacles.
Minary, Peter; Martyna, Glenn J.; Tuckerman, Mark E.
2003-02-01
In this paper (Paper I) and a companion paper (Paper II), novel new algorithms and applications of the isokinetic ensemble as generated by Gauss' principle of least constraint, pioneered for use with molecular dynamics 20 years ago, are presented for biophysical, path integral, and Car-Parrinello based ab initio molecular dynamics. In Paper I, a new "extended system" version of the isokinetic equations of motion that overcomes the ergodicity problems inherent in the standard approach, is developed using a new theory of non-Hamiltonian phase space analysis [M. E. Tuckerman et al., Europhys. Lett. 45, 149 (1999); J. Chem. Phys. 115, 1678 (2001)]. Reversible multiple time step integrations schemes for the isokinetic methods, first presented by Zhang [J. Chem. Phys. 106, 6102 (1997)] are reviewed. Next, holonomic constraints are incorporated into the isokinetic methodology for use in fast efficient biomolecular simulation studies. Model and realistic examples are presented in order to evaluate, critically, the performance of the new isokinetic molecular dynamic schemes. Comparisons are made to the, now standard, canonical dynamics method, Nosé-Hoover chain dynamics [G. J. Martyna et al., J. Chem. Phys. 97, 2635 (1992)]. The new isokinetic techniques are found to yield more efficient sampling than the Nosé-Hoover chain method in both path integral molecular dynamics and biophysical molecular dynamics calculations. In Paper II, the use of isokinetic methods in Car-Parrinello based ab initio molecular dynamics calculations is presented.
Efficient algorithms for the reverse shortest path problem on trees under the hamming distance
Tayyebi Javad
2017-01-01
Full Text Available Given a network G(V,A,c and a collection of origin-destination pairs with prescribed values, the reverse shortest path problem is to modify the arc length vector c as little as possible under some bound constraints such that the shortest distance between each origin-destination pair is upper bounded by the corresponding prescribed value. It is known that the reverse shortest path problem is NP-hard even on trees when the arc length modifications are measured by the weighted sum-type Hamming distance. In this paper, we consider two special cases of this problem which are polynomially solvable. The first is the case with uniform lengths. It is shown that this case transforms to a minimum cost flow problem on an auxiliary network. An efficient algorithm is also proposed for solving this case under the unit sum-type Hamming distance. The second case considered is the problem without bound constraints. It is shown that this case is reduced to a minimum cut problem on a tree-like network. Therefore, both cases studied can be solved in strongly polynomial time.
Automated Prediction of Catalytic Mechanism and Rate Law Using Graph-Based Reaction Path Sampling.
Habershon, Scott
2016-04-12
In a recent article [ J. Chem. Phys. 2015 , 143 , 094106 ], we introduced a novel graph-based sampling scheme which can be used to generate chemical reaction paths in many-atom systems in an efficient and highly automated manner. The main goal of this work is to demonstrate how this approach, when combined with direct kinetic modeling, can be used to determine the mechanism and phenomenological rate law of a complex catalytic cycle, namely cobalt-catalyzed hydroformylation of ethene. Our graph-based sampling scheme generates 31 unique chemical products and 32 unique chemical reaction pathways; these sampled structures and reaction paths enable automated construction of a kinetic network model of the catalytic system when combined with density functional theory (DFT) calculations of free energies and resultant transition-state theory rate constants. Direct simulations of this kinetic network across a range of initial reactant concentrations enables determination of both the reaction mechanism and the associated rate law in an automated fashion, without the need for either presupposing a mechanism or making steady-state approximations in kinetic analysis. Most importantly, we find that the reaction mechanism which emerges from these simulations is exactly that originally proposed by Heck and Breslow; furthermore, the simulated rate law is also consistent with previous experimental and computational studies, exhibiting a complex dependence on carbon monoxide pressure. While the inherent errors of using DFT simulations to model chemical reactivity limit the quantitative accuracy of our calculated rates, this work confirms that our automated simulation strategy enables direct analysis of catalytic mechanisms from first principles.
Deng Lei Lei
2016-01-01
Full Text Available To realize the management and control of the water-saving irrigation of the path pipeline distribution in field plots, get the terrain information through remote sensing technology and analyze the path and the amount of the water in the field plots by the ant colony algorithm according to the matter of the low generality in most parts in China. The result shows that the rules were put forward with shorter path, smaller cost and the most utilization of water eventually. It can be widely used in most areas which is lack of water and scientific technology.
Cassini Thruster Calibration Algorithm Using Reaction Wheel Biasing Data
Rizvi, Farheen
2012-01-01
Thrust force estimates for the reaction control thrusters on-board Cassini spacecraft are presented in this paper. Cassini consists of two thruster branches (A and B) each with eight thrusters. The four Z-thrusters control the X and Y-axes, while the four Y-thrusters control the Z-axis. It is important to track the thrust force estimates in order to detect any thruster degradation and for supporting various activities in spacecraft operations (Titan flyby, spacecraft maneuvers). The Euler equation, which describes the rotational motion of the spacecraft during a reaction wheel bias event, is used to develop the algorithm. The thrust estimates are obtained from the pseudo inverse solution using flight telemetry during the bias. Results show that the A-branch Z3A and Z4A thrusters exhibited degraded thrust in November 2008. Due to the degraded thrust performance of Z3A and Z4A, A-branch usage was discontinued and prime branch was swapped to B-branch in March 2009. The thrust estimates from the B-branch do not show any degradation to date. The algorithm is used to trend the B-branch thrust force estimates as the mission continues.
Lavrenov Roman
2017-01-01
Full Text Available Our research focuses on operation of a heterogeneous robotic group that carries out point-to point navigation in GPS-denied dynamic environment, applying a combined local and global planning approach. In this paper, we introduce a homotopy-based high-level planner, which uses a modified splinebased path-planning algorithm. The algorithm utilizes Voronoi graph for global planning and a set of optimization criteria for local improvements of selected paths. The simulation was implemented in Matlab environment.
Utkarsh Gautam
2015-05-01
Full Text Available Addressing the need for exploration of benthic zones utilising autonomous underwater vehicles, this paper presents a simulation for an optimised path planning from the source node to the destination node of the autonomous underwater vehicle SLOCUM Glider in near-bottom ocean environment. Near-bottom ocean current data from the Bedford Institute of Oceanography, Canada, have been used for this simulation. A cost function is formulated to describe the dynamics of the autonomous underwater vehicle in near-bottom ocean currents. This cost function is then optimised using various biologically-inspired algorithms such as genetic algorithm, Ant Colony optimisation algorithm and particle swarm optimisation algorithm. The simulation of path planning is also performed using Q-learning technique and the results are compared with the biologically-inspired algorithms. The results clearly show that the Q-learning algorithm is better in computational complexity than the biologically-inspired algorithms. The ease of simulating the environment is also more in the case of Q-learning techniques. Hence this paper presents an effective path planning technique, which has been tested for the SLOCUM glider and it may be extended for use in any standard autonomous underwater vehicle.Defence Science Journal, Vol. 65, No. 3, May 2015, pp.220-225, DOI: http://dx.doi.org/10.14429/dsj.65.7855
Kudi: A free open-source python library for the analysis of properties along reaction paths.
Vogt-Geisse, Stefan
2016-05-01
With increasing computational capabilities, an ever growing amount of data is generated in computational chemistry that contains a vast amount of chemically relevant information. It is therefore imperative to create new computational tools in order to process and extract this data in a sensible way. Kudi is an open source library that aids in the extraction of chemical properties from reaction paths. The straightforward structure of Kudi makes it easy to use for users and allows for effortless implementation of new capabilities, and extension to any quantum chemistry package. A use case for Kudi is shown for the tautomerization reaction of formic acid. Kudi is available free of charge at www.github.com/stvogt/kudi.
Coupling sample paths to the partial thermodynamic limit in stochastic chemical reaction networks
Levien, Ethan
2016-01-01
We present a new technique for reducing the variance in Monte Carlo estimators of stochastic chemical reaction networks. Our method makes use of the fact that many stochastic reaction networks converge to piecewise deterministic Markov processes in the large system-size limit. The statistics of the piecewise deterministic process can be obtained much more efficiently than those of the exact process. By coupling sample paths of the exact model to the piecewise deterministic process we are able to reduce the variance, and hence the computational complexity of the Monte Carlo estimator. In addition to rigorous results concerning the asymptotic behavior of our method, numerical simulations are performed on some simple biological models suggesting that significant computational gains are made for even moderate system-sizes.
Wang, Liangbing; Zhang, Wenbo; Wang, Shenpeng; Gao, Zehua; Luo, Zhiheng; Wang, Xu; Zeng, Rui; Li, Aowen; Li, Hongliang; Wang, Menglin; Zheng, Xusheng; Zhu, Junfa; Zhang, Wenhua; Ma, Chao; Si, Rui; Zeng, Jie
2016-12-22
Rh-based heterogeneous catalysts generally have limited selectivity relative to their homogeneous counterparts in hydroformylation reactions despite of the convenience of catalyst separation in heterogeneous catalysis. Here, we develop CoO-supported Rh single-atom catalysts (Rh/CoO) with remarkable activity and selectivity towards propene hydroformylation. By increasing Rh mass loading, isolated Rh atoms switch to aggregated clusters of different atomicity. During the hydroformylation, Rh/CoO achieves the optimal selectivity of 94.4% for butyraldehyde and the highest turnover frequency number of 2,065 h(-1) among the obtained atomic-scale Rh-based catalysts. Mechanistic studies reveal that a structural reconstruction of Rh single atoms in Rh/CoO occurs during the catalytic process, facilitating the adsorption and activation of reactants. In kinetic view, linear products are determined as the dominating products by analysing reaction paths deriving from the two most stable co-adsorbed configurations. As a bridge of homogeneous and heterogeneous catalysis, single-atom catalysts can be potentially applied in other industrial reactions.
Wang, Liangbing; Zhang, Wenbo; Wang, Shenpeng; Gao, Zehua; Luo, Zhiheng; Wang, Xu; Zeng, Rui; Li, Aowen; Li, Hongliang; Wang, Menglin; Zheng, Xusheng; Zhu, Junfa; Zhang, Wenhua; Ma, Chao; Si, Rui; Zeng, Jie
2016-12-01
Rh-based heterogeneous catalysts generally have limited selectivity relative to their homogeneous counterparts in hydroformylation reactions despite of the convenience of catalyst separation in heterogeneous catalysis. Here, we develop CoO-supported Rh single-atom catalysts (Rh/CoO) with remarkable activity and selectivity towards propene hydroformylation. By increasing Rh mass loading, isolated Rh atoms switch to aggregated clusters of different atomicity. During the hydroformylation, Rh/CoO achieves the optimal selectivity of 94.4% for butyraldehyde and the highest turnover frequency number of 2,065 h-1 among the obtained atomic-scale Rh-based catalysts. Mechanistic studies reveal that a structural reconstruction of Rh single atoms in Rh/CoO occurs during the catalytic process, facilitating the adsorption and activation of reactants. In kinetic view, linear products are determined as the dominating products by analysing reaction paths deriving from the two most stable co-adsorbed configurations. As a bridge of homogeneous and heterogeneous catalysis, single-atom catalysts can be potentially applied in other industrial reactions.
Lim, Chong Wee
CaF2-structure CoSi2 layers were formed on Si(001) by reactive deposition epitaxy (RDE) and compared with CoSi2 layers obtained by conventional solid phase growth (SPG). In the case of RDE, CoSi 2 formation occurred during Co deposition at elevated temperature while for SPG, Co was deposited at 25°C and silicidation took place during subsequent annealing. My results demonstrate that RDE CoSi2 layers are epitaxial with a cube-on-cube relationship, 001CoSi2 ‖001Si and 100CoSi2 ‖100 Si . In contrast, SPG films are polycrystalline with a mixed 111/002/022/112 orientation. I attribute the striking difference to rapid Co diffusion during RDE for which the high Co/Si reactivity gives rise to a flux-limited reaction resulting in the direct formation of the disilicide phase. Initial formation of CoSi2(001) follows the Volmer-Weber mode with two families of island shapes: inverse pyramids and platelets. The rectangular-based pyramidal islands extend along orthogonal directions, bounded by four {111} CoSi2/Si interfaces, and grow with a cube-on-cube orientation with respect to Si(001). Platelet-shaped islands are bounded across their long directions by {111} twin planes and their narrow directions by 511CoSi2 ‖111Si interfaces. The top and bottom surfaces are {22¯1}, with 22¯1 CoSi2‖001 Si , and {1¯1¯1}, with 1¯1¯ 1CoSi2‖ 11¯1Si , respectively. The early stages of film growth (tCo ≤ 13 A) are dominated by the twinned platelets due to a combination of higher nucleation rates and rapid elongation along preferred directions. However, at tCo ≥ 13 A, island coalescence becomes significant as orthogonal platelets intersect and block elongation along fast growth directions. Further island growth becomes dominated by the untwinned islands. I show that high-flux low-energy Ar+ ion irradiation during RDE growth dramatically increases the area fraction of untwinned regions from 0.17 in films grown under standard magnetically balanced conditions in which the ratio
Reliability assessment of power distribution systems using disjoint path-set algorithm
Bourezg, Abdrabbi; Meglouli, H.
2015-10-01
Finding the reliability expression of different substation configurations can help design a distribution system with the best overall reliability. This paper presents a computerized a nd implemented algorithm, based on Disjoint Sum of Product (DSOP) algorithm. The algorithm was synthesized and applied for the first time to the determination of reliability expression of a substation to determine reliability indices and costs of different substation arrangements. It deals with the implementation and synthesis of a new designed algorithm for DSOP implemented using C/C++, incorporating parallel problem solving capability and overcoming the disadvantage of Monte Carlo simulation which is the lengthy computational time to achieve satisfactory statistical convergence of reliability index values. The major highlight of this research being that the time consuming procedures of the DSOP solution generated for different substation arrangements using the proposed method is found to be significantly lower in comparison with the time consuming procedures of Monte Carlo-simulation solution or any other method used for the reliability evaluation of substations in the existing literature such as meta-heuristic and soft computing algorithms. This implementation gives the possibility of RBD simulation for different substation configurations in C/C++ using their path-set Boolean expressions mapped to probabilistic domain and result in simplest Sum of Disjoint Product which is on a one-to-one correspondence with reliability expression. This software tool is capable of handling and modeling a large, repairable system. Additionally, through its intuitive interface it can be easily used for industrial and commercial power systems. With simple Boolean expression for a configuration's RBD inputted, users can define a power system utilizing a RBD and, through a fast and efficient built-in simulation engine, the required reliability expressions and indices can be obtained. Two case studies
Transition path sampling with quantum/classical mechanics for reaction rates.
Gräter, Frauke; Li, Wenjin
2015-01-01
Predicting rates of biochemical reactions through molecular simulations poses a particular challenge for two reasons. First, the process involves bond formation and/or cleavage and thus requires a quantum mechanical (QM) treatment of the reaction center, which can be combined with a more efficient molecular mechanical (MM) description for the remainder of the system, resulting in a QM/MM approach. Second, reaction time scales are typically many orders of magnitude larger than the (sub-)nanosecond scale accessible by QM/MM simulations. Transition path sampling (TPS) allows to efficiently sample the space of dynamic trajectories from the reactant to the product state without an additional biasing potential. We outline here the application of TPS and QM/MM to calculate rates for biochemical reactions, by means of a simple toy system. In a step-by-step protocol, we specifically refer to our implementation within the MD suite Gromacs, which we have made available to the research community, and include practical advice on the choice of parameters.
An algorithm for sequential tail value at risk for path-independent payoffs in a binomial tree
Roorda, Berend
2010-01-01
We present an algorithm that determines Sequential Tail Value at Risk (STVaR) for path-independent payoffs in a binomial tree. STVaR is a dynamic version of Tail-Value-at-Risk (TVaR) characterized by the property that risk levels at any moment must be in the range of risk levels later on. The algori
Meenakshi R Patel
2012-03-01
Full Text Available ACO algorithms for datagram networks was given by Di Caro Dorigo, in year 1996. Basic mechanisms in typical ACO routing algorithms is Ant-like agents are proactively generated at the nodes to find/check paths toward assigned destinations Ants move hop-by-hop according to a exploratory routing policy based on the local routing .After reaching their destination, ants retrace their path and update nodes routing information according to the quality of the path. Routing information is statistical estimates of the time-to-go to the destination maintained in pheromone arrays. Data are probabilistically spread over the paths according to their estimated quality as stored in the pheromone variables. AntNet algorithms may cause the network congestion and stagnation as the routing table converges. In this paper we perform a survey on modified AntNet routing algorithm using Multiple Ant-Colony Optimization. Multiple ant colonies with different pheromone updating mechanism have different searching traits. By leveraging this feature, much of work is done by designing a set of adaptive rules to facilitate the collaboration between these colonies. This approach can balance the diversity and convergence of solutions generated by different ant colonies and also overcome the problem of Stagnation.
Subbaraj Potti
2011-01-01
Full Text Available Problem statement: A new multi-objective approach, Strength Pareto Evolutionary Algorithm (SPEA, is presented in this paper to solve the shortest path routing problem. The routing problem is formulated as a multi-objective mathematical programming problem which attempts to minimize both cost and delay objectives simultaneously. Approach: SPEA handles the shortest path routing problem as a true multi-objective optimization problem with competing and noncommensurable objectives. Results: SPEA combines several features of previous multi-objective evolutionary algorithms in a unique manner. SPEA stores nondominated solutions externally in another continuously-updated population and uses a hierarchical clustering algorithm to provide the decision maker with a manageable pareto-optimal set. SPEA is applied to a 20 node network as well as to large size networks ranging from 50-200 nodes. Conclusion: The results demonstrate the capabilities of the proposed approach to generate true and well distributed pareto-optimal nondominated solutions.
Investigation at the atomic level of homologous enzymes reveals distinct reaction paths
Zoi, Ioanna; Schwartz, Steven D.
2015-03-01
Bacterial enzymes Escherichia coli and Vibrio cholerae 5' -Methylthioadenosine nucleosidases (MTANs) have different binding affinities for the same transition state analogue. This was surprising as these enzymes share 60% sequence identity, have almost identical active sites and act under the same mechanism. We performed Transition Path Sampling simulations of both enzymes to reveal the atomic details of the catalytic chemical step, to explain the inhibitor affinity differences. Unlike EcMTAN, VcMTAN has multiple distinct transition states, which is an indication that multiple sets of coordinated protein motions can reach a transition state. We also identified the important residues that participate in each enzyme's reaction coordinate and explained their contribution. Subtle dynamic differences manifest in difference of reaction coordinate and transition state structure and also suggest that MTANs differ from most ribosyl transferases. As experimental approaches report averages regarding reaction coordinate information, this study offers, previously unavailable, detailed knowledge to the explanation of bacterial MTANs catalytic mechanism, and could have a significant impact on pharmaceutical design. We acknowledge the support of the National Institutes of Health through Grant GM068036.
Mixed quantum-classical reaction path dynamics of C2H5F --> C2H4 + HF.
Stopera, Christopher J; Bladow, Landon L; Thweatt, W David; Page, Michael
2008-11-20
A mixed quantum-classical method for calculating product energy partitioning based on a reaction path Hamiltonian is presented and applied to HF elimination from fluoroethane. The goal is to describe the effect of the potential energy release on the product energies using a simple model of quantized transverse vibrational modes coupled to a classical reaction path via the path curvature. Calculations of the minimum energy path were done at the B3LYP/6-311++G(2d,2p) and MP2/6-311++G** levels of theory, followed by energy-partitioning dynamics calculations. The results for the final HF vibrational state distribution were found to be in good qualitative agreement with both experimental studies and quasiclassical trajectory simulations.
Parallel Critical Path Tracing—— A Fault Simulation Algorithm for Combinational Circuits
魏道政
1990-01-01
Critical path tracing,a fault simulation method for gate-level combinational circuits,is extended to the parallel critical path tracing for functional block-level combinational circuits.If the word length of the host computer is m,then the parallel critical path tracing will be approximately m times faster than the original one.
Chemical reaction path modeling of hydrothermal processes on Mars: Preliminary results
Plumlee, Geoffrey S.; Ridley, W. Ian
1992-01-01
Hydrothermal processes are thought to have had significant roles in the development of surficial mineralogies and morphological features on Mars. For example, a significant proportion of the Martian soil could consist of the erosional products of hydrothermally altered impact melt sheets. In this model, impact-driven, vapor-dominated hydrothermal systems hydrothermally altered the surrounding rocks and transported volatiles such as S and Cl to the surface. Further support for impact-driven hydrothermal alteration on Mars was provided by studies of the Ries crater, Germany, where suevite deposits were extensively altered to montmorillonite clays by inferred low-temperature (100-130 C) hydrothermal fluids. It was also suggested that surface outflow from both impact-driven and volcano-driven hydrothermal systems could generate the valley networks, thereby eliminating the need for an early warm wet climate. We use computer-driven chemical reaction path calculation to model chemical processes which were likely associated with postulated Martian hydrothermal systems.
Energy-Efficient Shortest Path Algorithms for Convergecast in Sensor Networks
Augustine, John; Loden, Philip; Lodha, Sachin; Roy, Sasanka
2009-01-01
We introduce a variant of the capacitated vehicle routing problem that is encountered in sensor networks for scientific data collection. Consider an undirected graph $G=(V \\cup \\{\\mathbf{sink}\\},E)$. Each vertex $v \\in V$ holds a constant-sized reading normalized to 1 byte that needs to be communicated to the $\\mathbf{sink}$. The communication protocol is defined such that readings travel in packets. The packets have a capacity of $k$ bytes. We define a {\\em packet hop} to be the communication of a packet from a vertex to its neighbor. Each packet hop drains one unit of energy and therefore, we need to communicate the readings to the $\\mathbf{sink}$ with the fewest number of hops. We show this problem to be NP-hard and counter it with a simple distributed $(2-\\frac{3}{2k})$-approximation algorithm called {\\tt SPT} that uses the shortest path tree rooted at the $\\mathbf{sink}$. We also show that {\\tt SPT} is absolutely optimal when $G$ is a tree and asymptotically optimal when $G$ is a grid. Furthermore, {\\tt ...
Zhang Xing; Chen Jie; Xin Bin; Peng Zhihong
2014-01-01
The problem of generating optimal paths for curvature-constrained unmanned aerial vehicles (UAVs) performing surveillance of multiple ground targets is addressed in this paper. UAVs are modeled as Dubins vehicles so that the constraints of UAVs’ minimal turning radius can be taken into account. In view of the effective surveillance range of the sensors equipped on UAVs, the problem is formulated as a Dubins traveling salesman problem with neighborhood (DTSPN). Considering its prohibitively high computational complexity, the Dubins paths in the sense of terminal heading relaxation are introduced to simplify the calculation of the Dubins distance, and a boundary-based encoding scheme is proposed to determine the visiting point of every target neighborhood. Then, an evolutionary algorithm is used to derive the optimal Dubins tour. To further enhance the quality of the solutions, a local search strategy based on approximate gradient is employed to improve the visiting points of target neighborhoods. Finally, by a minor modification to the individual encoding, the algorithm is easily extended to deal with other two more sophisticated DTSPN variants (multi-UAV scenario and multiple groups of targets scenario). The performance of the algorithm is demonstrated through comparative experiments with other two state-of-the-art DTSPN algorithms identified in literature. Numerical simulations exhibit that the algorithm proposed in this paper can find high-quality solutions to the DTSPN with lower computational cost and produce significantly improved performance over the other algorithms.
Zhang Xing
2014-06-01
Full Text Available The problem of generating optimal paths for curvature-constrained unmanned aerial vehicles (UAVs performing surveillance of multiple ground targets is addressed in this paper. UAVs are modeled as Dubins vehicles so that the constraints of UAVs’ minimal turning radius can be taken into account. In view of the effective surveillance range of the sensors equipped on UAVs, the problem is formulated as a Dubins traveling salesman problem with neighborhood (DTSPN. Considering its prohibitively high computational complexity, the Dubins paths in the sense of terminal heading relaxation are introduced to simplify the calculation of the Dubins distance, and a boundary-based encoding scheme is proposed to determine the visiting point of every target neighborhood. Then, an evolutionary algorithm is used to derive the optimal Dubins tour. To further enhance the quality of the solutions, a local search strategy based on approximate gradient is employed to improve the visiting points of target neighborhoods. Finally, by a minor modification to the individual encoding, the algorithm is easily extended to deal with other two more sophisticated DTSPN variants (multi-UAV scenario and multiple groups of targets scenario. The performance of the algorithm is demonstrated through comparative experiments with other two state-of-the-art DTSPN algorithms identified in literature. Numerical simulations exhibit that the algorithm proposed in this paper can find high-quality solutions to the DTSPN with lower computational cost and produce significantly improved performance over the other algorithms.
David S. Hardin
2013-04-01
Full Text Available As Graphics Processing Units (GPUs have gained in capability and GPU development environments have matured, developers are increasingly turning to the GPU to off-load the main host CPU of numerically-intensive, parallelizable computations. Modern GPUs feature hundreds of cores, and offer programming niceties such as double-precision floating point, and even limited recursion. This shift from CPU to GPU, however, raises the question: how do we know that these new GPU-based algorithms are correct? In order to explore this new verification frontier, we formalized a parallelizable all-pairs shortest path (APSP algorithm for weighted graphs, originally coded in NVIDIA's CUDA language, in ACL2. The ACL2 specification is written using a single-threaded object (stobj and tail recursion, as the stobj/tail recursion combination yields the most straightforward translation from imperative programming languages, as well as efficient, scalable executable specifications within ACL2 itself. The ACL2 version of the APSP algorithm can process millions of vertices and edges with little to no garbage generation, and executes at one-sixth the speed of a host-based version of APSP coded in C – a very respectable result for a theorem prover. In addition to formalizing the APSP algorithm (which uses Dijkstra's shortest path algorithm at its core, we have also provided capability that the original APSP code lacked, namely shortest path recovery. Path recovery is accomplished using a secondary ACL2 stobj implementing a LIFO stack, which is proven correct. To conclude the experiment, we ported the ACL2 version of the APSP kernels back to C, resulting in a less than 5% slowdown, and also performed a partial back-port to CUDA, which, surprisingly, yielded a slight performance increase.
A Control Algorithm for UAV Path Planning%无人机路径规划的控制算法
柳传武; 张奇
2016-01-01
Real time control is almost impossible for traditional unmanned aircraft continuous path algo-rithm due to the deferred response because of the time spent on flight path calculation.Using the Bessel curve to calculate flight path can simplify the process,but it is still very difficult to generate the desired flight path. In this paper,the linear and circular interpolation technology of numerical control system is applied to control the turning path of aircraft,which can achieve real time response to system and accurate control of the flight path,thus a turning path control algorithm is designed by relating to UAV flight altitude,speed and angle of attack.The results show that the algorithm is simple with accurate path control,and its rationality is verified through flight test.%传统的无人机连续路径算法，因计算飞行路径需要一定的时间而延迟响应，很难实时控制。采用贝塞尔曲线来计算飞行路径，过程会简化很多，但要产生预期的飞行路径仍然很难实现。现将数值控制系统的直线和圆弧插补技术用于飞机转弯路径控制算法，实现实时响应，精确控制飞行路径，再结合无人机飞行高度、速度和迎角，设计了一种实现转弯路径控制算法。研究结果表明该算法简单，路径控制准确，并通过飞行测试验证了设计的合理性。
Mazyar Seraj
2014-10-01
Full Text Available This paper describes an experimental study of learning Dijkstra’s shortest path algorithm on mobile devices. The aim of the study is to investigate and compare the impacts of two different mobile screen user interfaces on students’ satisfaction for learning the technical subject. A mobile learning prototype was developed for learning Dijkstra’s shortest path algorithm on Apple iPhone 4 operated on iPhone operating system (iOS, and Acer Inconia Tab operated on an Android operating system. Thirty students, who are either currently studying or had previously studied Computer Networks, were recruited for the usability trial. At the end of each single session, students’ satisfaction interacting with the two mobile devices was measured using QUIS questionnaire. Although there is no significant difference in students’ satisfaction between the two different mobile screen interfaces, the subjective findings indicate that Acer Inconia Tab gained higher scores as compared to Apple iPhone 4.
Wong, Kin-Yiu; Xu, Yuqing; Xu, Liang
2015-11-01
Enzymatic reactions are integral components in many biological functions and malfunctions. The iconic structure of each reaction path for elucidating the reaction mechanism in details is the molecular structure of the rate-limiting transition state (RLTS). But RLTS is very hard to get caught or to get visualized by experimentalists. In spite of the lack of explicit molecular structure of the RLTS in experiment, we still can trace out the RLTS unique "fingerprints" by measuring the isotope effects on the reaction rate. This set of "fingerprints" is considered as a most direct probe of RLTS. By contrast, for computer simulations, oftentimes molecular structures of a number of TS can be precisely visualized on computer screen, however, theoreticians are not sure which TS is the actual rate-limiting one. As a result, this is an excellent stage setting for a perfect "marriage" between experiment and theory for determining the structure of RLTS, along with the reaction mechanism, i.e., experimentalists are responsible for "fingerprinting", whereas theoreticians are responsible for providing candidates that match the "fingerprints". In this Review, the origin of isotope effects on a chemical reaction is discussed from the perspectives of classical and quantum worlds, respectively (e.g., the origins of the inverse kinetic isotope effects and all the equilibrium isotope effects are purely from quantum). The conventional Bigeleisen equation for isotope effect calculations, as well as its refined version in the framework of Feynman's path integral and Kleinert's variational perturbation (KP) theory for systematically incorporating anharmonicity and (non-parabolic) quantum tunneling, are also presented. In addition, the outstanding interplay between theory and experiment for successfully deducing the RLTS structures and the reaction mechanisms is demonstrated by applications on biochemical reactions, namely models of bacterial squalene-to-hopene polycyclization and RNA 2'-O
Siddhartha Sankar Biswas
2014-01-01
Full Text Available The networks of the present day communication systems, be it a public road transportation system or a MANET or an Adhoc Network, frequently face a lot of uncertainties in particular regarding traffic jam, flood or water logging or PWD maintenance work (in case of public road network, attack or damage from internal or external agents, sudden failure of one or few nodes. Consequently, at a real instant of time, the existing links/arcs of a given network (graph are not always in their original/excellent condition physically or logically, rather in a weaker condition, or even sometimes disabled or blocked temporarily and waiting for maintenance/repair; and hence ultimately causing delay in communication or transportation. We do not take any special consideration if few of the links be in a better condition at the real time of communication, we consider only such cases where few links are in inferior condition (partially or fully damaged. The classical Dijkstra’s algorithm to find the shortest path in graphs is applicable only if we assume that all the links of the concerned graph are available at their original (ideal condition at that real time of communication, but at real time scenario it is not the case. Consequently, the mathematically calculated shortest path extracted by using Dijkstra’s algorithm may become costlier (even in-feasible in some cases in terms of time and/or in terms of other overhead costs; whereas some other path may be the most efficient or most optimal. Many real life situations of communication network or transportation network cannot be modeled into graphs, but can be well modeled into multigraphs because of the scope of dealing with multiple links (or arcs connecting a pair of nodes. The classical Dijkstra’s algorithm to find the shortest path in graphs is not applicable to multigraphs. In this study the authors make a refinement of the classical Dijkstra’s algorithm to make it applicable to directed multigraphs
YANG,En-Cui(杨恩翠); ZHAO,Xiao-Jun(赵小军); TIAN,Peng(田鹏); HAO,Jin-Ku(郝金库)
2004-01-01
The two possible reaction paths of producing ethane on coupling reaction of methane through plasma were theoretically investigated by B3LYP and MP2 methods with 6-311G* respectively and further compared with the previous results calculated from B3LYP/6-31G*.The new investigated results consistently confirmed the previous conclusion.And the influences of the calculation methods and basis sets on the calculated results were also discussed.
A constant-factor approximation algorithm for unsplittable flow on paths
Bonsma, Paul; Schulz, Jens; Wiese, Andreas
2014-01-01
In the unsplittable flow problem on a path, we are given a capacitated path $P$ and $n$ tasks, each task having a demand, a profit, and start and end vertices. The goal is to compute a maximum profit set of tasks such that, for each edge $e$ of $P$, the total demand of selected tasks that use $e$ do
Yu, Pengfei; Wang, Hailong; Chen, Jianyong; Shen, Shengping
2017-07-01
In this study, the conservation laws οf dissipative mechanical-diffusion-electrochemical reaction system are systematically obtained based on Noether's theorem. According to linear, irreversible thermodynamics, dissipative phenomena can be described by an irreversible force and an irreversible flow. Additionally, the Lagrange function, L and the generalized Hamilton least-action principle are proposed to be used to obtain the conservation integrals. A group of these integrals, including the J-, M-, and L-integrals, can be then obtained using the classical Noether approach for dissipative processes. The relation between the J-integral and the energy release rate is illustrated. The path-independence of the J-integral is then proven. The J-integral, derived based on Noether's theorem, is a line integral, contrary to the propositions of existing published works that describe it both as a line and an area integral. Herein, we prove that the outcomes are identical, and identify the physical meaning of the area integral, a concept that was not explained previously. To show that the J-integral can dominate the distribution of the corresponding field quantities, an example of a partial, stress-diffusion coupling process is disscussed.
The solubility of (Ba,Sr)SO 4 precipitates: Thermodynamic equilibrium and reaction path analysis
Felmy, Andrew R.; Rai, Dhanpat; Moore, Dean A.
1993-09-01
The solubility of (Ba,Sr)SO 4 precipitates, varying in SrSO 4 mole fraction from 0.05-0.90, was investigated at room temperature with an equilibration period extending to almost three years. The data show that on or before 315 days of equilibration the precipitates reach a reversible equilibrium with the aqueous solution. The reversibility of this equilibrium was verified both by the attainment of steady-state concentrations with time and by heating the samples to perturb the equilibrium and then observing the slow return to the initial equilibrium state. The dissolution of the (Ba,Sr)SO 4 precipitates does not, in general, follow limiting reaction paths as defined by the Lippmann solutus or stoichiometric dissolution curves. In addition, activity coefficient calculations for the BaSO 4 and SrSO 4 components of the solid phase, using either total bulk analysis or near-surface analysis of the component mole fractions, do not satisfy the Gibbs-Duhem equation, demonstrating that a single solid-solution phase does not control both the aqueous Ba and Sr concentrations. Instead, our long-term equilibration data can be explained by the unavoidable formation of small amounts of barite and substitution of Sr into a solid-solution phase with the BaSO 4 component of the solid-solution phase never reaching thermodynamic equilibrium with the aqueous phase.
An algorithm for determination of geodetic path for application in long-range acoustic propagation
Murty, T.V.R.; Sivakholundu, K.M.; Navelkar, G.S.; Somayajulu, Y.K.; Murty, C.S.
A computer program has been developed for the construction of geodetic path between two points on the spheroidal surface for application in long range acoustic propagation in the ocean. Geodetic equations have integrated numerically upto...
Chen, Jun; Luo, Chaomin; Krishnan, Mohan; Paulik, Mark; Tang, Yipeng
2010-01-01
An enhanced dynamic Delaunay Triangulation-based (DT) path planning approach is proposed for mobile robots to plan and navigate a path successfully in the context of the Autonomous Challenge of the Intelligent Ground Vehicle Competition (www.igvc.org). The Autonomous Challenge course requires the application of vision techniques since it involves path-based navigation in the presence of a tightly clustered obstacle field. Course artifacts such as switchbacks, ramps, dashed lane lines, trap etc. are present which could turn the robot around or cause it to exit the lane. The main contribution of this work is a navigation scheme based on dynamic Delaunay Triangulation (DDT) that is heuristically enhanced on the basis of a sense of general lane direction. The latter is computed through a "GPS (Global Positioning System) tail" vector obtained from the immediate path history of the robot. Using processed data from a LADAR, camera, compass and GPS unit, a composite local map containing both obstacles and lane line segments is built up and Delaunay Triangulation is continuously run to plan a path. This path is heuristically corrected, when necessary, by taking into account the "GPS tail" . With the enhancement of the Delaunay Triangulation by using the "GPS tail", goal selection is successfully achieved in a majority of situations. The robot appears to follow a very stable path while navigating through switchbacks and dashed lane line situations. The proposed enhanced path planning and GPS tail technique has been successfully demonstrated in a Player/Stage simulation environment. In addition, tests on an actual course are very promising and reveal the potential for stable forward navigation.
Tian, Jun-Long; Li, Xian; Yan, Shi-Wei; Wu, Xi-Zhen; Li, Zhu-Xia
2009-08-01
the collision of very heavy nuclei 197Au+197Au at 15 A MeV has been studied within the improved quantum molecular dynamics model. A class of ternary events satisfying nearly complete balance of mass numbers is selected. The experimental mass distributions for the system 197Au+197Au ternary fission fragments, the heaviest (A1), the intermediate (A2) and the lightest (A3), are reproduced well. The mean free path of nucleons in the reaction system is studied and the shorter mean free path is responsible for the ternary fission with three mass comparable fragments, in which the two-body dissipation mechanism plays a dominant role.
An improved stochastic algorithm for temperature-dependent homogeneous gas phase reactions
Kraft, M
2003-01-01
We propose an improved stochastic algorithm for temperature-dependent homogeneous gas phase reactions. By combining forward and reverse reaction rates, a significant gain in computational efficiency is achieved. Two modifications of modelling the temperature dependence (with and without conservation of enthalpy) are introduced and studied quantitatively. The algorithm is tested for the combustion of n-heptane, which is a reference fuel component for internal combustion engines. The convergence of the algorithm is studied by a series of numerical experiments and the computational cost of the stochastic algorithm is compared with the DAE code DASSL. If less accuracy is needed the stochastic algorithm is faster on short simulation time intervals. The new stochastic algorithm is significantly faster than the original direct simulation algorithm in all cases considered.
Cotter, Simon L.
2016-10-01
Efficient analysis and simulation of multiscale stochastic systems of chemical kinetics is an ongoing area for research, and is the source of many theoretical and computational challenges. In this paper, we present a significant improvement to the constrained approach, which is a method for computing effective dynamics of slowly changing quantities in these systems, but which does not rely on the quasi-steady-state assumption (QSSA). The QSSA can cause errors in the estimation of effective dynamics for systems where the difference in timescales between the "fast" and "slow" variables is not so pronounced. This new application of the constrained approach allows us to compute the effective generator of the slow variables, without the need for expensive stochastic simulations. This is achieved by finding the null space of the generator of the constrained system. For complex systems where this is not possible, or where the constrained subsystem is itself multiscale, the constrained approach can then be applied iteratively. This results in breaking the problem down into finding the solutions to many small eigenvalue problems, which can be efficiently solved using standard methods. Since this methodology does not rely on the quasi steady-state assumption, the effective dynamics that are approximated are highly accurate, and in the case of systems with only monomolecular reactions, are exact. We will demonstrate this with some numerics, and also use the effective generators to sample paths of the slow variables which are conditioned on their endpoints, a task which would be computationally intractable for the generator of the full system.
Reaction paths and equilibrium end-points in solid-solution aqueous-solution systems
Glynn, P.D.; Reardon, E.J.; Plummer, L.N.; Busenberg, E.
1990-01-01
Equations are presented describing equilibrium in binary solid-solution aqueous-solution (SSAS) systems after a dissolution, precipitation, or recrystallization process, as a function of the composition and relative proportion of the initial phases. Equilibrium phase diagrams incorporating the concept of stoichiometric saturation are used to interpret possible reaction paths and to demonstrate relations between stoichiometric saturation, primary saturation, and thermodynamic equilibrium states. The concept of stoichiometric saturation is found useful in interpreting and putting limits on dissolution pathways, but there currently is no basis for possible application of this concept to the prediction and/ or understanding of precipitation processes. Previously published dissolution experiments for (Ba, Sr)SO4 and (Sr, Ca)C??O3orth. solids are interpreted using equilibrium phase diagrams. These studies show that stoichiometric saturation can control, or at least influence, initial congruent dissolution pathways. The results for (Sr, Ca)CO3orth. solids reveal that stoichiometric saturation can also control the initial stages of incongruent dissolution, despite the intrinsic instability of some of the initial solids. In contrast, recrystallisation experiments in the highly soluble KCl-KBr-H2O system demonstrate equilibrium. The excess free energy of mixing calculated for K(Cl, Br) solids is closely modeled by the relation GE = ??KBr??KClRT[a0 + a1(2??KBr-1)], where a0 is 1.40 ?? 0.02, a1, is -0.08 ?? 0.03 at 25??C, and ??KBr and ??KCl are the mole fractions of KBr and KCl in the solids. The phase diagram constructed using this fit reveals an alyotropic maximum located at ??KBr = 0.676 and at a total solubility product, ???? = [K+]([Cl-] + [Br-]) = 15.35. ?? 1990.
Maldonado Puente, Bryan Patricio
2014-01-01
The inner detector of the ATLAS experiment has two types of silicon detectors used for tracking: Pixel Detector and SCT (semiconductor tracker). Once a proton-proton collision occurs, the result- ing particles pass through these detectors and these are recorded as hits on the detector surfaces. A medium to high energy particle passes through seven different surfaces of the two detectors, leaving seven hits, while lower energy particles can leave many more hits as they circle through the detector. For a typical event during the expected operational conditions, there are 30 000 hits in average recorded by the sensors. Only high energy particles are of interest for physics analysis and are taken into account for the path reconstruction; thus, a filtering process helps to discard the low energy particles produced in the collision. The following report presents a solution for increasing the speed of the filtering process in the path reconstruction algorithm.
Path Planning Algorithm for Autonomous Vehicle%自主车辆路径规划算法研究
张艳溶; 马戎; 吕文杰
2011-01-01
ath planning of autonomous vehicles through a specific point of whether the actual situation of two, which proposed the respective solution: a certain point without the need for global planning, conditions of heuristic, compared with traditional A * algorithm, is equaled with euclidean distance, and add a weight which reducing the importance of heuristic relatively. In the other opposite planning , the hopfiled neural network is adopted in order to achieve the desired path planning. The simulations show that the improved algorithm enhances the performance of path planning, and proved the validity of the algorithm.%在自主车辆的路径规划是否经过特定点的两种实际情况下,提出了不同的解决方案.当车辆不需要经过特定点时,引入A*算法,较传统算法将启发函数改为欧几里得函数(Euclidean Distance),并引入一个权值以降低启发函数的权重.当车辆需要经过特定点时,应用Hopfield神经网络思想优化算法,以达到理想的路径规划.仿真实验表明,改进后的算法使得路径规划寻优得到明显提高,并验证了算法的有效性.
Simulation of biochemical reactions with time-dependent rates by the rejection-based algorithm
Thanh, Vo Hong, E-mail: vo@cosbi.eu [The Microsoft Research - University of Trento Centre for Computational and Systems Biology, Piazza Manifattura 1, Rovereto 38068 (Italy); Priami, Corrado, E-mail: priami@cosbi.eu [The Microsoft Research - University of Trento Centre for Computational and Systems Biology, Piazza Manifattura 1, Rovereto 38068 (Italy); Department of Mathematics, University of Trento, Trento (Italy)
2015-08-07
We address the problem of simulating biochemical reaction networks with time-dependent rates and propose a new algorithm based on our rejection-based stochastic simulation algorithm (RSSA) [Thanh et al., J. Chem. Phys. 141(13), 134116 (2014)]. The computation for selecting next reaction firings by our time-dependent RSSA (tRSSA) is computationally efficient. Furthermore, the generated trajectory is exact by exploiting the rejection-based mechanism. We benchmark tRSSA on different biological systems with varying forms of reaction rates to demonstrate its applicability and efficiency. We reveal that for nontrivial cases, the selection of reaction firings in existing algorithms introduces approximations because the integration of reaction rates is very computationally demanding and simplifying assumptions are introduced. The selection of the next reaction firing by our approach is easier while preserving the exactness.
Lin, Ping; Yang, Weitao; Pedersen, Lars C.; Negishi, Masa; Pedersen, Lee G.
The enzymatic transfer of a sulfuryl group from the ubiquitous biological source of sulfate 3?-phosphoadenosine 5?-phosphosulfate (PAPS) to estrogen is investigated by the pseudo-bond quantum mechanical/molecular mechanical method (QM/MM) method. Calculations of the reaction path are performed starting with models based on two crystal structures, which differ in information about the cofactor and substrates. In addition, a subsequent relaxation of the enzyme was performed with the found transition state frozen, followed by redetermination of the path. An activation barrier of 22 kcal/mol is estimated. The reaction mechanism features a proton transfer from the estrogen to a catalytic histidine followed by the rate determining SO3 transfer. The mechanism found is largely dissociative.
Mattson, Earl [Idaho National Lab. (INL), Idaho Falls, ID (United States); Smith, Robert [Idaho National Lab. (INL), Idaho Falls, ID (United States); Fujita, Yoshiko [Idaho National Lab. (INL), Idaho Falls, ID (United States); McLing, Travis [Idaho National Lab. (INL), Idaho Falls, ID (United States); Neupane, Ghanashyam [Idaho National Lab. (INL), Idaho Falls, ID (United States); Palmer, Carl [Idaho National Lab. (INL), Idaho Falls, ID (United States); Reed, David [Idaho National Lab. (INL), Idaho Falls, ID (United States); Thompson, Vicki [Idaho National Lab. (INL), Idaho Falls, ID (United States)
2015-03-01
The project was aimed at demonstrating that the geothermometric predictions can be improved through the application of multi-element reaction path modeling that accounts for lithologic and tectonic settings, while also accounting for biological influences on geochemical temperature indicators. The limited utilization of chemical signatures by individual traditional geothermometer in the development of reservoir temperature estimates may have been constraining their reliability for evaluation of potential geothermal resources. This project, however, was intended to build a geothermometry tool which can integrate multi-component reaction path modeling with process-optimization capability that can be applied to dilute, low-temperature water samples to consistently predict reservoir temperature within ±30 °C. The project was also intended to evaluate the extent to which microbiological processes can modulate the geochemical signals in some thermal waters and influence the geothermometric predictions.
Tran, Huu-Khoa; Chiou, Juing -Shian; Peng, Shou-Tao
2016-01-01
In this paper, the feasibility of a Genetic Algorithm Optimization (GAO) education software based Fuzzy Logic Controller (GAO-FLC) for simulating the flight motion control of Unmanned Aerial Vehicles (UAVs) is designed. The generated flight trajectories integrate the optimized Scaling Factors (SF) fuzzy controller gains by using GAO algorithm. The…
Tran, Huu-Khoa; Chiou, Juing -Shian; Peng, Shou-Tao
2016-01-01
In this paper, the feasibility of a Genetic Algorithm Optimization (GAO) education software based Fuzzy Logic Controller (GAO-FLC) for simulating the flight motion control of Unmanned Aerial Vehicles (UAVs) is designed. The generated flight trajectories integrate the optimized Scaling Factors (SF) fuzzy controller gains by using GAO algorithm. The…
A. A. Heidari
Full Text Available An essential task of UAV autonomy is automatic path planning. There are many evolutionary planners for Unmanned Aerial Vehicles (UAVs that have been developed UAV community. In this paper a comparative study about performance of effective trajectory plan ...
ESTIMATION OF OPTIMAL PATH ON URBAN ROAD NETWORKS USING AHP ALGORITHM
Surendra Kukadapwar
2016-03-01
Full Text Available This paper describes to develop a multi criteria decision based methodology to find optimal path in real urban road network. Over the year several studies were conducted but most of which rely on single variable like travel distance or travel time as cost function. In this study, seven different attributes influencing the traffic network i.e. distance, time, traffic volume, road width, no. of intersection, parking and encroachment on road are used to define cost function using multi criterion decision making approach. These variables are combined using a Multi-Dimensional Cost Model (MDCM using the Analytical Hierarchical Process (AHP. The models developed were implemented and closely evaluated in Nagpur city of India. Model is considered for determining optimal path between various Origins and Destinations in real urban traffic network. Composite weighted AHP scored were used to generate AHP decision surface. Finally, the best decision was proposed by generating the least cost path which is considered as optimal path. The resulting routes showed to be more accurate than those obtained utilizing one-dimensional cost functions and AHP is found to be effective tool to deal with optimal route selection problem.
D-leaping: Accelerating stochastic simulation algorithms for reactions with delays
Bayati, Basil; Chatelain, Philippe; Koumoutsakos, Petros
2009-09-01
We propose a novel, accelerated algorithm for the approximate stochastic simulation of biochemical systems with delays. The present work extends existing accelerated algorithms by distributing, in a time adaptive fashion, the delayed reactions so as to minimize the computational effort while preserving their accuracy. The accuracy of the present algorithm is assessed by comparing its results to those of the corresponding delay differential equations for a representative biochemical system. In addition, the fluctuations produced from the present algorithm are comparable to those from an exact stochastic simulation with delays. The algorithm is used to simulate biochemical systems that model oscillatory gene expression. The results indicate that the present algorithm is competitive with existing works for several benchmark problems while it is orders of magnitude faster for certain systems of biochemical reactions.
Convergence analysis of filtered-X LMS algorithm with secondary path modeling error
SUN Xu; CHEN Duanshi
2003-01-01
A more relaxed sufficient condition for the convergence of filtered-X LMS (FXLMS)algorithm is presented. It is pointed out that if some positive real condition for secondary pathtransfer function and its estimates is satisfied within all the frequency bands, FXLMS algorithmconverges whatever the reference signal is like. But if the above positive real condition is satisfiedonly within some frequency bands, the convergence of FXLMS algorithm is dependent on thedistribution of power spectral density of the reference signal, and the convergence step size isdetermined by the distribution of some specific correlation matrix eigenvalues.Applying the conclusion above to the Delayed LMS (DLMS) algorithm, it is shown thatDLMS algorithm with some error of time delay estimation converges in certain discrete fre-quency bands, and the width of which are determined only by the "time-delay estimation errorfrequency" which is equal to one fourth of the inverse of estimated error of the time delay.
DING Yingqiang; DU Liufeng; YANG Ting; SUN Yugeng
2009-01-01
Sensor localization is crucial for the configuration and applications of wireless sensor network (WSN). A novel distributed localization algorithm, MDS-DC was proposed for wireless sensor network based on multidi-mensional scaling (MDS) and the shortest path distance correction. In MDS-DC, several local positioning regions with reasonable distribution were firstly constructed by an adaptive search algorithm, which ensures the mergence between the local relative maps of the adjacent local position regions and can reduce the number of common nodes in the network. Then, based on the relationships between the estimated distances and actual distances of anchors, the distance estimation vectors of sensors around anchors were corrected in each local positioning region. During the computations of the local relative coordinates, an iterative process, which is the combination of classical MDS algorithm and SMACOF algorithm, was applied. Finally, the global relative positions or absolute positions of sen-sors were obtained through merging the relative maps of all local positioning regions. Simulation results show that MDS-DC has better performances in positioning precision, energy efficiency and robustness to range error, which can meet the requirements of applications for sensor localization in WSN.
Wen-Xiang Wu
2014-01-01
Full Text Available The cost-based system optimum problem in networks with continuously distributed value of time is formulated as a path-based form, which cannot be solved by the Frank-Wolfe algorithm. In light of magnitude improvement in the availability of computer memory in recent years, path-based algorithms have been regarded as a viable approach for traffic assignment problems with reasonably large network sizes. We develop a path-based gradient projection algorithm for solving the cost-based system optimum model, based on Goldstein-Levitin-Polyak method which has been successfully applied to solve standard user equilibrium and system optimum problems. The Sioux Falls network tested is used to verify the effectiveness of the algorithm.
An Efficient Forward-Reverse EM Algorithm for Statistical Inference in Stochastic Reaction Networks
Bayer, Christian
2016-01-06
In this work [1], we present an extension of the forward-reverse algorithm by Bayer and Schoenmakers [2] to the context of stochastic reaction networks (SRNs). We then apply this bridge-generation technique to the statistical inference problem of approximating the reaction coefficients based on discretely observed data. To this end, we introduce an efficient two-phase algorithm in which the first phase is deterministic and it is intended to provide a starting point for the second phase which is the Monte Carlo EM Algorithm.
A Hybrid Mutation Chemical Reaction Optimization Algorithm for Global Numerical Optimization
Ransikarn Ngambusabongsopa
2015-01-01
Full Text Available This paper proposes a hybrid metaheuristic approach that improves global numerical optimization by increasing optimal quality and accelerating convergence. This algorithm involves a recently developed process for chemical reaction optimization and two adjustment operators (turning and mutation operators. Three types of mutation operators (uniform, nonuniform, and polynomial were combined with chemical reaction optimization and turning operator to find the most appropriate framework. The best solution among these three options was selected to be a hybrid mutation chemical reaction optimization algorithm for global numerical optimization. The optimal quality, convergence speed, and statistical hypothesis testing of our algorithm are superior to those previous high performance algorithms such as RCCRO, HP-CRO2, and OCRO.
R-leaping: Accelerating the stochastic simulation algorithm by reaction leaps
Auger, Anne; Chatelain, Philippe; Koumoutsakos, Petros
2006-08-01
A novel algorithm is proposed for the acceleration of the exact stochastic simulation algorithm by a predefined number of reaction firings (R-leaping) that may occur across several reaction channels. In the present approach, the numbers of reaction firings are correlated binomial distributions and the sampling procedure is independent of any permutation of the reaction channels. This enables the algorithm to efficiently handle large systems with disparate rates, providing substantial computational savings in certain cases. Several mechanisms for controlling the accuracy and the appearance of negative species are described. The advantages and drawbacks of R-leaping are assessed by simulations on a number of benchmark problems and the results are discussed in comparison with established methods.
A Tool Path Re-generation Algorithm for Die & Mold Machining
L; P; Zhang; J; Y; H; Fuh; A; Y; C; Nee
2002-01-01
Facing the challenges of a shorter product design a nd manufacturing lead-time, many mold companies are using 3-D CAD/CAM software s ystems in design and manufacturing. A new product file is often issued to the mo ld design department before it is completely finalized and the design may have t o be iterated many times during the mold design and making processes. In practic e, if a mold has been modified, all the tool paths that cover the modified regio n must be re-generated, no matter how small the modifi...
Frauzem, Rebecca; Kongpanna, Pichayapan; Roh, Kosan
carbonate (DMC) [2]. In this work, through a computer-aided framework for process network synthesis-design, a network of conversion processes that all use emitted CO2 is investigated. CO2 is emitted into the environment from various sources: power generation, industrial processes, transportation...... and commercial processes. Within these there are high-purity emissions and low-purity emissions. Rather than sending these to the atmosphere, it is possible to collect them and use them for other purposes. Targeting some of the largest contributors: power generation, manufacturing, chemical industry...... through the reactions. Studies and detailed simulations have been performed on CO2 conversion to methanol, synthesis gas processes, dimethyl carbonate production, and other processes. The detailed simulations are performed on the paths that are selected based on basic calculations on each path. Then...
Gonzalez, Carlos A; Squitieri, Emilio; Franco, Hector J; Rincon, Luis C
2017-01-26
The Kohn-Sham density functional theory (DFT) formalism has been used to investigate the influence of the stationary behavior of the electron density (ρ(r⃗;s)) along a minimum energy path on the corresponding stationary conditions observed in the total potential energy of the reactive system, information theory measures (Shannon information entropy and Onicescu information energy), and chemical reactivity indexes (the chemical hardness). The theoretical treatment presented in this work, combined with DFT calculations on 3 different test reactions: Ḣ' + H2, Ḣ' + CH4 and H(-) + CH4, suggest that for any reactive system, properties that can be cast as a functional of the electron density, must exhibit stationary points along the IRC path modulated by the corresponding stationary behavior of the electron density.
Path Planning Algorithm based on Arnold Cat Map for Surveillance UAVs
Daniel-Ioan Curiac
2015-11-01
Full Text Available During their task accomplishment, autonomous unmanned aerial vehicles are facing more and more threats coming from both ground and air. In such adversarial environments, with no a priori information about the threats, a flying robot in charge with surveilling a specified 3D sector must perform its tasks by evolving on misleading and unpredictable trajectories to cope with enemy entities. In our view, the chaotic dynamics can be the cornerstone in designing unpredictable paths for such missions, even though this solution was not exploited until now by researchers in the 3D context. This paper addresses the flight path-planning issue for surveilling a given volume in adversarial conditions by proposing a proficient approach that uses the chaotic behaviour exhibited by the 3D Arnold’s cat map. By knowing the exact location of the volume under surveillance before take-off, the flying robot will generate the successive chaotic waypoints only with onboard resources, in an efficient manner. The method is validated by simulation in a realistic scenario using a detailed Simulink model for the X-4 Flyer quadcopter.
Xianrui XU; Xiaojie LI; Yujie HU; Zhongren PENG
2012-01-01
In recent years,the increasing development of traffic information collection technology based on floating car data has been recognized,which gives rise to the establishment of real-time traffic information dissemination system in many cities.However,the recent massive construction of urban elevated roads hinders the processing of corresponding GPS data and further extraction of traffic information (e.g.,identifying the real travel path),as a result of the frequent transfer of vehicles between ground and elevated road travel.Consequently,an algorithm for identifying the travel road type (i.e.,elevated or ground road) of vehicles is designed based on the vehicle traveling features,geometric and topological characteristics of the elevated road network,and a trajectory model proposed in the present study.To be specific,the proposed algorithm can detect the places where a vehicle enters,leaves or crosses under elevated roads.An experiment of 10 sample taxis in Shanghai,China was conducted,and the comparison of our results and results that are obtained from visual interpretation validates the proposed algorithm.
Van Nguyen; Javaid, Abdul Q; Weitnauer, Mary Ann
2014-01-01
We introduce the Spectrum-averaged Harmonic Path (SHAPA) algorithm for estimation of heart rate (HR) and respiration rate (RR) with Impulse Radio Ultrawideband (IR-UWB) radar. Periodic movement of human torso caused by respiration and heart beat induces fundamental frequencies and their harmonics at the respiration and heart rates. IR-UWB enables capture of these spectral components and frequency domain processing enables a low cost implementation. Most existing methods of identifying the fundamental component either in frequency or time domain to estimate the HR and/or RR lead to significant error if the fundamental is distorted or cancelled by interference. The SHAPA algorithm (1) takes advantage of the HR harmonics, where there is less interference, and (2) exploits the information in previous spectra to achieve more reliable and robust estimation of the fundamental frequency in the spectrum under consideration. Example experimental results for HR estimation demonstrate how our algorithm eliminates errors caused by interference and produces 16% to 60% more valid estimates.
An Algorithm for Odd Graceful Labeling of the Union of Paths and Cycles
M. Ibrahim Moussa
2010-03-01
Full Text Available In 1991, Gnanajothi [4] proved that the path graph Pn with n vertex and n -1edge is odd graceful, andthe cycle graph Cm with m vertex and m edges is odd graceful if and only if m even, she proved thecycle graph is not graceful if m odd. In this paper, firstly, we studied the graph m n C ÈP when m = 4, 6,8,10and then we proved that the graph m n C ÈP is odd graceful if m is even. Finally, we described analgorithm to label the vertices and the edges of the vertex set ( V CmÈPn and the edge set ( E CmÈPn .
Reconciling transition path time and rate measurements in reactions with large entropic barriers
Makarov, Dmitrii E.
2017-02-01
Recent experiments and simulation studies showed that protein/DNA folding barriers inferred from folding rates or from potentials of mean force are often much higher than the barriers estimated from the distributions of transition path times. Here a toy model is used to explain a possible origin of this effect: It is shown that when the transition in question involves an entropic barrier, the one-dimensional Langevin model commonly used to interpret experimental data, while adequately predicting the transition rate, fails to describe the properties of the subset of the trajectories that form the transition path ensemble; the latter may still be describable in terms of a one-dimensional model, but with a different potential, just as observed experimentally.
Badin, E. J.; Calvin, M.
1950-02-01
A comparison of the rates of fixation of Carbon 14 dioxide in algae for the processes of photosynthesis, photoreduction and the hydrogen-oxygen-carbon dioxide dark reaction has been made. For the same series of experiments, rates of incorporation of tracer carbon into the separate soluble components using the radiogram method have been determined. The mechanism of carbon dioxide uptake has been shown to occur via two distinct paths. In all cases studied, essentially the same compounds appear radioactive. The distribution with time, however, differs markedly.
Walch, Stephen P.; Rohlfing, Celeste Mcmichael; Melius, Carl F.; Bauschlicher, Charles W., Jr.
1988-01-01
The potential energy surface for the H + O2 to HO2(asterisk) to HO + O reaction has been investigated in the region of the minimum energy path using CASSCF/contracted CI (CCI) calculations with a large basis set. The results show no barrier for the addition of an H atom to O2, in agreement with previous studies. A crossing between the surface for electrostatic (OH dipole-O quadrupole) interaction and that for the formation of an O-O chemical bond, at r(infinity) of about 5.5 a(0), results in a small (about 0.5 kcal/mol) barrier.
Badin, Elmer J.; Calvin, Melvin
1950-02-01
A comparison of the rates of fixation of Carbon 14 dioxide in algae for the processes of photosynthesis, photoreduction and the hydrogen-oxygen-carbon dioxide dark reaction has been made. For the same series of experiments, rates of incorporation of tracer carbon into the separate soluble components using the radiogram method have been determined. The mechanism of carbon dioxide uptake has been shown to occur via two distinct paths. In all cases studied, essentially the same compounds appear radioactive. The distribution with time, however, differs markedly.
Chen Kaiyan; Si Junhong; Zhou Fubao; Zhang Renwei; Shao He; Zhao Hongmei
2015-01-01
In mine ventilation networks, the reasonable airflow distribution is very important for the production safety and economy. Three basic problems of the natural, full-controlled and semi-controlled splitting were reviewed in the paper. Aiming at the high difficulty semi-controlled splitting problem, the general nonlinear multi-objectives optimization mathematical model with constraints was established based on the theory of mine ventilation networks. A new algorithm, which combined the improved differential evaluation and the critical path method (CPM) based on the multivariable separate solution strategy, was put forward to search for the global optimal solution more efficiently. In each step of evolution, the feasible solutions of air quantity distribution are firstly produced by the improved differential evolu-tion algorithm, and then the optimal solutions of regulator pressure drop are obtained by the CPM. Through finite steps iterations, the optimal solution can be given. In this new algorithm, the population of feasible solutions were sorted and grouped for enhancing the global search ability and the individuals in general group were randomly initialized for keeping diversity. Meanwhile, the individual neighbor-hood in the fine group which may be closely to the optimal solutions were searched locally and slightly for achieving a balance between global searching and local searching, thus improving the convergence rate. The computer program was developed based on this method. Finally, the two ventilation networks with single-fan and multi-fans were solved. The results show that this algorithm has advantages of high effectiveness, fast convergence, good robustness and flexibility. This computer program could be used to solve large-scale generalized ventilation networks optimization problem in the future.
Hardware Genetic Algorithm Optimization by Critical Path Analysis using a Custom VLSI Architecture
Farouk Smith
2015-07-01
Full Text Available This paper propose a Virtual-Field Programmable Gate Array (V-FPGA architecture that allows direct access to its configuration bits to facilitate hardware evolution, thereby allowing any combinational or sequential digital circuit to be realized. By using the V-FPGA, this paper investigates two possible ways of making evolutionary hardware systems more scalable: by optimizing the system’s genetic algorithm (GA; and by decomposing the solution circuit into smaller, evolvable sub-circuits. GA optimization is done by: omitting a canonical GA’s crossover operator (i.e. by using a 1+λ algorithm; applying evolution constraints; and optimizing the fitness function. A noteworthy contribution this research has made is the in-depth analysis of the phenotypes’ CPs. Through analyzing the CPs, it has been shown that a great amount of insight can be gained into a phenotype’s fitness. We found that as the number of columns in the Cartesian Genetic Programming array increases, so the likelihood of an external output being placed in the column decreases. Furthermore, the number of used LEs per column also substantially decreases per added column. Finally, we demonstrated the evolution of a state-decomposed control circuit. It was shown that the evolution of each state’s sub-circuit was possible, and suggest that modular evolution can be a successful tool when dealing with scalability.
A cellular automata algorithm of finding critical path%求解关键路径的元胞自动机算法
钱鑫; 吴晓军; 张甜甜; 易宇
2009-01-01
A new algorithm is put forward according to the characteristics of parallel calculation and local space-time of cellular automata model. In the algorithm, the critical path will develop with the evolvement of cells by selecting cells and setting corresponding rules. The experimental results indicate that this algorithm can he used to solve the critical path searching problem in multi-source-point and multi-collecting-point AOE network, eliminate the linear procedure of traditional algorithm based on topological sort and reverse topological scan, and also unify the algorithms of shortest path searching and critical path searching problems.%利用元胞自动机的离散空间与并行计算特性,通过对元胞的抽象和局部规则的设计,借助于元胞状态的动态演化,解决了AOE网络(Activity on edge network)中多源点多汇点关键路径的求解,消除了基于拓扑排序和逆拓扑扫描的传统算法的线性化过程,并从算法上实现了AOE网最短路径与关键路径求解的统一.
Planeta, David S
2007-01-01
In this paper I present general outlook on questions relevant to the basic graph algorithms; Finding the Shortest Path with Positive Weights and Minimum Spanning Tree. I will show so far known solution set of basic graph problems and present my own. My solutions to graph problems are characterized by their linear worst-case time complexity. It should be noticed that the algorithms which compute the Shortest Path and Minimum Spanning Tree problems not only analyze the weight of arcs (which is the main and often the only criterion of solution hitherto known algorithms) but also in case of identical path weights they select this path which walks through as few vertices as possible. I have presented algorithms which use priority queue based on multilevel prefix tree -- PTrie. PTrie is a clever combination of the idea of prefix tree -- Trie, the structure of logarithmic time complexity for insert and remove operations, doubly linked list and queues. In C++ I will implement linear worst-case time algorithm computin...
Mireille Bousquet-Mélou
2008-04-01
Full Text Available Let a and b be two positive integers. A culminating path is a path of ℤ 2 that starts from (0,0, consists of steps (1,a and (1,-b, stays above the x-axis and ends at the highest ordinate it ever reaches. These paths were first encountered in bioinformatics, in the analysis of similarity search algorithms. They are also related to certain models of Lorentzian gravity in theoretical physics. We first show that the language on a two letter alphabet that naturally encodes culminating paths is not context-free. Then, we focus on the enumeration of culminating paths. A step by step approach, combined with the kernel method, provides a closed form expression for the generating function of culminating paths ending at a (generic height k. In the case a = b, we derive from this expression the asymptotic behaviour of the number of culminating paths of length n. When a > b, we obtain the asymptotic behaviour by a simpler argument. When a < b, we only determine the exponential growth of the number of culminating paths. Finally, we study the uniform random generation of culminating paths via various methods. The rejection approach, coupled with a symmetry argument, gives an algorithm that is linear when a ≥ b, with no precomputation stage nor non-linear storage required. The choice of the best algorithm is not as clear when a < b. An elementary recursive approach yields a linear algorithm after a precomputation stage involving O (n 3 arithmetic operations, but we also present some alternatives that may be more efficient in practice.
Atomic-scale study of transformation paths in unmixing and ordering reactions
Blavette, D.; Pareige-Schmuck, C.; Danoix, F. [CNRS, Mont Saint Aignan (France). Fac. des Sci. de Rouen; Stiller, K.
1997-06-01
The tomographic atom-probe (TAP) is a new high resolution nanoanalytical microscope, which provides three-dimensional maps of chemical heterogeneities in a metallic material on a near-atomic scale. Application of the TAP to unmixing and ordering in metallic alloys is discussed and illustrated through various examples (spinodal decomposition in FeCr ferritic phases, nucleation and growth of LI{sub 2} ordered precipitates in nickel based alloys, precipitation in maraging steels). The role of the TAP in the investigation of transformation paths in these systems is discussed. (orig.). 17 refs.
2012-09-13
Matrix produced by Wimer’s Algorithm # of Arcs j 1 2 3 . . . q 2 P1(2) P2(2) P3 (2) . . . Pq(2) 3 P1(3) P2(3) P3 (3) Pq(3) Node # u 4 P1(4) P2(4) P3 (4...Pq(4) ... ... . . . ... N P1(N) P2(N) P3 (N) . . . Pq(N) Assign another matrix Z, call each of its elements Zj(u), where each element is 25 Table 5...chooses ”contract” car- riers for long-term partnerships ; thus the need to model schedules is negated. Look at [10] for one detailed model of
Research on Auto Flight Path Planning Algorithm of Multiple Unmanned Air Vehicles%多无人机飞行路径自动规划算法研究
马传焱
2015-01-01
The path planning plays an important role in the reconnaissance task of unmanned air vehicle(UAV).Aiming at auto flight path planning algorithm of multi⁃UAV,this paper analyzes the key technologies of modeling and algorithm design.The algorithm uses Voronoi diagram for path planning. Based on the constructed battlefield environment V diagram, the Dijkstra algorithm in graph theory is used for initial path search and optimization.The simulation results show that this algorithm can be used to plan flight path for a typical multi⁃UAV flight task,and adapt to multiple constraint conditions.At last,it is shown that reasonable results of path planning are obtained.%路径规划对无人机完成其侦察作战任务具有重要意义。针对多无人机飞行路径自动规划算法，从模型建立和算法设计2个方面对规划过程中的关键技术进行了详细分析。算法采用构造Voronoi多边形图的方法来进行路径规划。基于构建的战场环境V图，采用图论中的Dijkstra 算法，对V图进行搜索得到初始航路并进行优化。经过分析仿真结果证明，该算法能对典型的多无人机飞行任务进行路径规划，并能满足多种约束条件，获取合理的规划结果。
移动机器人全局路径规划算法的研究%Research on Global Path Planning Algorithm of Mobile Robot
黄静; 陈汉伟
2014-01-01
Path planning is an important problem of mobile robots,and a better path planning algorithm can search the effec-tive paths quickly, enhance the intelligence of mobile robot and enhance interaction experience of users.This paper studied the A* algorithm and genetic algorithm and applied these algorithms in path planning of mobile robot based on Unity engine.Path plan-ning module for virtual mobile robot was implemented using the A*algorithm.The path search efficiency is increased and the mo-bile robots are more intelligent and authentic.%全局路径规划是移动机器人要解决的重要问题，较好的路径搜索算法可以迅速搜索有效路径，提升移动机器人的智能性，提升用户体验。针对目前移动机器人行为决策能力较弱的问题，着重研究移动机器人的全局路径规划问题，通过研究盲目式搜索算法、A*算法和遗传算法，分析了3种算法在解决路径规划问题中的优劣，使用A*算法在Unity平台上虚拟移动机器人的全局路径规划模块，并且使用贪婪平滑算法优化A*算法产生的多余路径，路径搜索的效率较高，移动机器人的智能性和真实感较好。
Chenel, A. [Laboratoire de Chimie Physique, UMR 8000 and CNRS, Université Paris-Sud, F-91405 Orsay (France); Meier, C. [Laboratoire Collisions, Agrégats, Réactivité, UMR 5589, IRSAMC, Université Paul Sabatier, F-31062 Toulouse (France); Dive, G. [Centre d’Ingéniérie des Protéines, Université de Liège, Sart Tilman, B6, B-4000 Liège (Belgium); Desouter-Lecomte, M. [Laboratoire de Chimie Physique, UMR 8000 and CNRS, Université Paris-Sud, F-91405 Orsay (France); Département de Chimie, Université de Liège, Bât B6c, Sart Tilman, B4000 Liège (Belgium)
2015-01-14
We compare the strategy found by the optimal control theory in a complex molecular system according to the active subspace coupled to the field. The model is the isomerization during a Cope rearrangement of Thiele’s ester that is the most stable dimer obtained by the dimerization of methyl-cyclopentadienenylcarboxylate. The crudest partitioning consists in retaining in the active space only the reaction coordinate, coupled to a dissipative bath of harmonic oscillators which are not coupled to the field. The control then fights against dissipation by accelerating the passage across the transition region which is very wide and flat in a Cope reaction. This mechanism has been observed in our previous simulations [Chenel et al., J. Phys. Chem. A 116, 11273 (2012)]. We compare here, the response of the control field when the reaction path is coupled to a second active mode. Constraints on the integrated intensity and on the maximum amplitude of the fields are imposed limiting the control landscape. Then, optimum field from one-dimensional simulation cannot provide a very high yield. Better guess fields based on the two-dimensional model allow the control to exploit different mechanisms providing a high control yield. By coupling the reaction surface to a bath, we confirm the link between the robustness of the field against dissipation and the time spent in the delocalized states above the transition barrier.
Collins, Peter; Ezra, Gregory S; Wiggins, Stephen
2013-01-01
We study reaction dynamics on a model potential energy surface exhibiting post-transition state bifurcation in the vicinity of a valley ridge inflection point. We compute fractional yields of products reached after the VRI region is traversed, both with and without dissipation. It is found that apparently minor variations in the potential lead to significant changes in the reaction dynamics. Moreover, when dissipative effects are incorporated, the product ratio depends in a complicated and highly non-monotonic fashion on the dissipation parameter. Dynamics in the vicinity of the VRI point itself play essentially no role in determining the product ratio, except in the highly dissipative regime.
Joshi, Neeraj Kumar; Fuyuki, Masanori; Wada, Akihide
2014-02-20
Spectral and kinetic behavior of thermal cis-to-trans isomerization of 4-aminoazobenzene (AAB) is examined in various solvents of different polarities. In contrast to azobenzene (AB), it is found the rate of thermal isomerization of AAB is highly dependent on solvent polarity. Accelerated rates are observed in polar solvents as compared to nonpolar solvents. Moreover, a decrease in the barrier height with an increase in medium polarity is observed. Our observations suggest that inversion is the preferred pathway in cis-to-trans thermal isomerization in a nonpolar medium; however, in a polar medium, the isomerization path deviates from the inversion route and rotational behavior is incorporated. Differences in the kinetics and in mechanisms of isomerization in different media are rationalized in terms of modulation in barrier height by polarity of the medium and solute-solvent interaction. It is found that kinetics as well as the mechanism of thermal isomerization in AAB is controlled by the polarity of the medium.
K. Duraiswamy
2012-01-01
Full Text Available The moving object or vehicle location prediction based on their spatial and temporal information is an important task in many applications. Different methods were utilized for performing the vehicle movement detection and prediction process. In such works, there is a lack of analysis in predicting the vehicles location in current as well as in future. Moreover, such methods compute the vehicles movement by finding the topological relationships among trajectories and locations, whereas the representative GPS points are determined by the 30 m circular window. Due to this process, the performance of the method is degraded because such 30 m circular window is selected by calculating the error range in the given input image and such error range may vary from image to image. To reduce the drawback presented in the existing method, in this study a heuristic moving vehicle location prediction algorithm is proposed. The proposed heuristic algorithm mainly comprises two techniques namely, optimization GA algorithm and FFBNN. In this proposed technique, initially the vehicles frequent paths are collected by monitoring all the vehicles movement in a specific period. Among the frequent paths, the vehicles optimal paths are computed by the GA algorithm. The selected optimal paths for each vehicle are utilized to train the FFBNN. The well trained FFBNN is then utilized to find the vehicle movement from the current location. By combining the proposed heuristic algorithm with GA and FFBNN, the vehicles location is predicted efficiently. The implementation result shows the effectiveness of the proposed heuristic algorithm in predicting the vehicles future location from the current location. The performance of the heuristic algorithm is evaluated by comparing the result with the RBF classifier. The comparison result shows our proposed technique acquires an accurate vehicle location prediction ratio than the RBF prediction ratio, in terms of accuracy.
基于EMRP算法的多UAV协同航迹规划%Cooperative Path Planning Based on EMRP Algorithm for Multi-UAVs
张亮; 鲁艺; 徐安; 胡智先; 周帅; 何海波
2011-01-01
A path planning method based on the hierarchical decomposition strategy was proposed for multi-UAV cooperative path planning in the battle field. First, the planning space was obtained by means of skeletonization algorithm, and K backup paths were generated for each UAV based on Evolutionary Multiple Route Planner (EMRP) algorithm. The EMRP algorithm was used together with mathematical morphology for solving the problem of multi-UAV cooperative path planning. The initial paths generated were smoothed,and the feasible paths that satisfied the maneuvering requirement of the UAV was obtained. Then a cooperative planning model was established, which could plan a feasible path for each UAV, which meeted both the requirements of time-coordination and the minimum cost. The simulation shows that this method is viable.%为解决作战环境中的多无人机协同航迹规划问题,提出一种基于层次分解策略的航迹规划方法.通过骨架化算法生成规划空间,利用基于进化计算的多航迹规划(EMRP)算法为各UAV找到K条备用航迹,实现了利用EMRP算法与数学形态学相结合解决多UAV协同航迹规划问题,并对生成的初始航迹进行平滑处理,得到满足UAV机动要求的可行航迹.然后建立协同模型,为各无人机规划出既能满足时间协同要求,又能满足整体代价最优的可行航迹.仿真袁明了该种方法的可行性.
适应性学习路径推荐算法及应用研究%Recommendation Algorithm and Application of Adaptive Learning Path
赵呈领; 陈智慧; 黄志芳
2015-01-01
In the adaptive learning path recommendation, the recommendation algorithm plays a vital role. From the perspective of the nature of algorithm, the recommendation algorithm in learning path recommendation system are grouped into three categories:swarm intelligence optimization algorithm, data mining algorithms and knowledge-based recommendation algorithm. Combined with the developed recommendation system, the paper compared and analyzed from three aspects including performance of the algorithm, the parameter settings in the learning path recommendation and the application. the paper summarized the application strategies of relevant algorithm in the learning path recommendation, as well as the strengths and weaknesses in the application, and discussed the practical application value of learning path recommendation to provide valuable information and reference for research in the ifeld of adaptive learning path recommendation.%在适应性学习路径推荐中，推荐算法起着至关重要的作用。本研究从算法性质的角度归类，将学习路径推荐系统中的推荐算法归为三大类：智能优化算法、数据挖掘算法以及基于知识的推荐算法。结合已开发的学习路径推荐系统，本文从算法性能、学习路径推荐中考虑的因素及算法应用三方面进行比较与分析，总结出上述推荐算法在学习路径推荐中的应用策略和应用中的优势及不足，最后探讨了学习路径推荐的实践应用价值，以期为适应性学习路径推荐领域的研究提供有价值的参考与借鉴。
Dynamic Adaptive RRT Path Planning Algorithm%动态自适应快速扩展树航迹规划算法研究
潘广贞; 秦帆; 张文斌
2013-01-01
快速扩展随机树(RRT)是航迹规划的重要算法,针对其难以直接应用于无人机航迹规划的问题,提出了动态自适应RRT算法.动态自适应RRT算法在随机点产生过程中加入无人机转弯角约束,使航迹更适合无人机直接跟踪；同时引入动态调节因子,根据环境中障碍密集程度调整规划步长,有效避免各类障碍.计算机实验结果表明动态自适应RRT算法在单航迹规划和多航迹规划中明显优于基本RRT算法和其它改进RRT算法,更适用于无人机航迹规划.%RRT is the important path planning algorithm. In view of its difficult to directly apply in UAVS path planning, this paper puts forwards the dynamic adaptive RRT algorithm. Adding turn corner constraints in the process of random point produce in order to make track for UAVS tracking more directly. At the same time, introduce dynamic adjustment factor, according to the environment of intensive degree to adjust the planning step length and avoid all kinds of barriers effectively. The computer experimental results show that the dynamic adaptive RRT algorithm in single path planning and more significantly than the basic path planning algorithm and other improvements RRT RRT algorithm, more applicable for UAVS path planning.
Daschakraborty, Snehasis; Kiefer, Philip M; Miller, Yifat; Motro, Yair; Pines, Dina; Pines, Ehud; Hynes, James T
2016-03-10
The protonation of methylamine base CH3NH2 by carbonic acid H2CO3 within a hydrogen (H)-bonded complex in aqueous solution was studied via Car-Parrinello dynamics in the preceding paper (Daschakraborty, S.; Kiefer, P. M.; Miller, Y.; Motro, Y.; Pines, D.; Pines, E.; Hynes, J. T. J. Phys. Chem. B 2016, DOI: 10.1021/acs.jpcb.5b12742). Here some important further details of the reaction path are presented, with specific emphasis on the water solvent's role. The overall reaction is barrierless and very rapid, on an ∼100 fs time scale, with the proton transfer (PT) event itself being very sudden (water solvent changes little until the actual PT occurrence; this results from the very strong driving force for the reaction, as indicated by the very favorable acid-protonated base ΔpKa difference. Further solvent rearrangement follows immediately the sudden PT's production of an incipient contact ion pair, stabilizing it by establishment of equilibrium solvation. The solvent water's short time scale ∼120 fs response to the incipient ion pair formation is primarily associated with librational modes and H-bond compression of water molecules around the carboxylate anion and the protonated base. This is consistent with this stabilization involving significant increase in H-bonding of hydration shell waters to the negatively charged carboxylate group oxygens' (especially the former H2CO3 donor oxygen) and the nitrogen of the positively charged protonated base's NH3(+).
Reaction phases and diffusion paths in SiC/metal systems
Naka, M.; Fukai, T. [Osaka Univ., Osaka (Japan); Schuster, J.C. [Vienna Univ., Vienna (Austria)
2004-07-01
The interface structures between SiC and metal are reviewed at SiC/metal systems. Metal groups are divided to carbide forming metals and non-carbide forming metals. Carbide forming metals form metal carbide granular or zone at metal side, and metal silicide zone at SiC side. The further diffusion of Si and C from SiC causes the formation of T ternary phase depending metal. Non-carbide forming metals form silicide zone containing graphite or the layered structure of metal silicide and metal silicide containing graphite. The diffusion path between SiC and metal are formed along tie-lines connecting SiC and metal on the corresponding ternary Si-C-M system. The reactivity of metals is dominated by the forming ability of carbide or silicide. Te reactivity tendency of elements are discussed on the periodical table of elements, and Ti among elements shows the highest reactivity among carbide forming metals. For non-carbide forming metals the reactivity sequence of metals is Fe>Ni>Co. (orig.)
Sikora, Jacqueline R; Rauzan, Brittany; Stegemann, Rachel; Deckert, Alice
2013-08-01
Evidence for unexpected off-path intermediates to DNA duplex formation is presented. These off-path intermediates are shown to involve unimolecular and, in one case, bimolecular structure in one of the single strands of complementary DNA. Three models are developed to account for the observed single-stranded structures that are formed in parallel with duplex formation. These models are applied to the analysis of stopped-flow data for eight different nonself-complementary duplex formation reactions in order to extract the elementary rate constant for formation of the duplex from the complementary random coil single-stranded DNA. The free energy of activation (at 25 °C) for the denaturation of each duplex is calculated from these data and is shown to have a linear correlation to the overall standard free energy for duplex formation (also at 25 °C). Duplexes that contain mismatches obey a parallel linear free-energy (LFE) relationship with a y-intercept that is greater than that of duplexes without mismatches. Slopes near unity for the LFE relationships indicate that all duplexes go through an early, unstructured transition state.
Blaschke, D.; Ebert, D.
2017-08-01
For the investigation of back-reactions of composite mesons in the NJL model, a variational path-integral treatment is formulated which yields an effective action Aeff [Dσ ,Dπ ; S ], depending on the propagators Dσ, Dπ of σ- and π-mesons and on the full quark propagator S. The stationarity conditions δAeff / δS = 0, δAeff / δDσ = 0, δAeff / δDπ = 0, then lead to coupled Schwinger-Dyson (SD) equations for the quark self-energy and the meson polarization functions. These results reproduce and extend results of the so-called ;Φ-derivable; approach and provide a functional formulation for diagrammatic resummations of 1 /Nc -corrections in the NJL model. Finally, we perform a low-momentum estimate of the quark and meson loop contributions to the polarization function of the pion and on this basis discuss the Goldstone theorem.
谭冠政; 贺欢; SLOMAN Aaron
2007-01-01
A novel method for the real-time globally optimal path planning of mobile robots is proposed based on the ant colony system (ACS) algorithm. This method includes three steps: the first step is utilizing the MAKLINK graph theory to establish the free space model of the mobile robot, the second step is utilizing the Dijkstra algorithm to find a sub-optimal collision-free path,and the third step is utilizing the ACS algorithm to optimize the location of the sub-optimal path so as to generate the globally optimal path. The result of computer simulation experiment shows that the proposed method is effective and can be used in the real-time path planning of mobile robots. It has been verified that the proposed method has better performance in convergence speed, solution variation, dynamic convergence behavior, and computational efficiency than the path planning method based on the genetic algorithm with elitist model.
Practical Research on Robot Path Planning Algorithm%机器人室内路径规划算法的实用性研究
周嵘; 张志翔; 翟晓晖; 闵慧芹; 孔庆杰
2016-01-01
Path planning is an important branch in the field of robot research,and its research has been a hot topic.In this paper,based on the experimental platform for robot P3 DX,the indoor environment is divided into blocks using the grid modeling method.The feasibility of the four path planning back path planning,alternate path planning,heuristic path planning and bounding path planning,has been veri-fied.In order to verify the practicability of the four path planning,the four path planning algorithms are studied in the real environment.According to the data returned by the robot after walking,we plot a road-map through software.At the same time,according to the path planning algorithm of the roadmap for the different repetition rates and coverage rates,we find out the efficient path planning algorithm.%机器人研究领域中的一个关键分支即路径规划技术，本课题在机器人P3 DX实验平台的基础上，通过栅格化建模对室内的环境实现分块。4种路径规划回字形路径规划、迂回式路径规划、启发式路径规划与包围式路径规划的可行性已经得到验证，为验证4种路径规划的实用性，在真实环境中将这4种路径规划算法进行了实验研究，通过软件将机器人行走后返回的数据绘制出相应的路线图，同时，根据各路径规划算法的路线图的不同重复率与覆盖率，找出效率较高的路径规划算法。
On the rejection-based algorithm for simulation and analysis of large-scale reaction networks
Thanh, Vo Hong, E-mail: vo@cosbi.eu [The Microsoft Research-University of Trento Centre for Computational and Systems Biology, Piazza Manifattura 1, Rovereto 38068 (Italy); Zunino, Roberto, E-mail: roberto.zunino@unitn.it [Department of Mathematics, University of Trento, Trento (Italy); Priami, Corrado, E-mail: priami@cosbi.eu [The Microsoft Research-University of Trento Centre for Computational and Systems Biology, Piazza Manifattura 1, Rovereto 38068 (Italy); Department of Mathematics, University of Trento, Trento (Italy)
2015-06-28
Stochastic simulation for in silico studies of large biochemical networks requires a great amount of computational time. We recently proposed a new exact simulation algorithm, called the rejection-based stochastic simulation algorithm (RSSA) [Thanh et al., J. Chem. Phys. 141(13), 134116 (2014)], to improve simulation performance by postponing and collapsing as much as possible the propensity updates. In this paper, we analyze the performance of this algorithm in detail, and improve it for simulating large-scale biochemical reaction networks. We also present a new algorithm, called simultaneous RSSA (SRSSA), which generates many independent trajectories simultaneously for the analysis of the biochemical behavior. SRSSA improves simulation performance by utilizing a single data structure across simulations to select reaction firings and forming trajectories. The memory requirement for building and storing the data structure is thus independent of the number of trajectories. The updating of the data structure when needed is performed collectively in a single operation across the simulations. The trajectories generated by SRSSA are exact and independent of each other by exploiting the rejection-based mechanism. We test our new improvement on real biological systems with a wide range of reaction networks to demonstrate its applicability and efficiency.
A Method for Path Planning of UAVs Based on Improved Genetic Algorithm%基于改进遗传算法的UAV航迹规划
鲁艺; 吕跃; 罗燕; 张亮; 赵志强; 唐隆
2012-01-01
An improved genetic algorithm was proposed to solve the problem of UAV's path planning in actual battle field. First,the planned search space was generated by means of skeleton algorithm,the information of the search space was extracted, and the kill probability of path points in the search space was calculated out. Then,with the information of the planned search space and by using a special gene coding mode,K possible paths were obtained by using genetic algorithm. According to the rules of path selection, the optimal path was obtained, and was smoothed by using different step lengths. Eventually the optimal path was acquired, which can meet the safety and maneuverability requirement of UAV.%针对实际作战环境中的UAV航迹规划,提出一种基于改进遗传算法的UAV航迹规划方法；通过骨架化算法生成规划搜索空间,对规划搜索空间中的信息进行提取,求解出规划搜索空间中航迹点的杀伤概率；根据规划搜索空间中的信息,采用特殊的基因编码方式,使用遗传算法为UAV找到K条备选航迹,提高了航迹规划效率；根据设定的航迹选取原则,求出最优航迹并对其按不同步长进行平滑处理,最终得到满足UAV机动性要求的可飞航迹.
Application of Genetic Algorithm in Mobile Robot Path Planning%遗传算法在移动机器人路径规划中的应用
徐丁; 朱擎飞; 叶晓东
2013-01-01
移动机器人的路径规划是机器人研究的重要领域。文中旨在研究遗传算法对于机器人路径规划问题的适用性。对于路径规划的目标，提出了基于路径长度、路径平滑度和路径安全度等因素综合衡量的方法，并在传统的遗传算法的交叉、变异操作的基础上，针对路径规划问题的特点，增加了捷径寻找、障碍避让、平滑优化等方法。实验表明，此算法在存在形状复杂的障碍物的静态环境中表现良好，其效率与准确性皆满足机器人路径规划的要求。%Path planning is an important subject in mobile robot research area. It aims to verify the feasibility of genetic algorithm towards mobile robot path planning problem. The goal of path planning is measured by the combination of path length,path smoothness and path safety. Besides traditional operators of crossover and mutation in genetic algorithm,there are additional methods such as shortcut seeking, obstacle avoidance and smoothness optimization. Through experiments,the algorithm performs well in static environment with obstacles in complex shapes and its efficiency and accuracy satisfies the requirements of the problem.
An algorithm for treatment of patients with hypersensitivity reactions after vaccines.
Wood, Robert A; Berger, Melvin; Dreskin, Stephen C; Setse, Rosanna; Engler, Renata J M; Dekker, Cornelia L; Halsey, Neal A
2008-09-01
Concerns about possible allergic reactions to immunizations are raised frequently by both patients/parents and primary care providers. Estimates of true allergic, or immediate hypersensitivity, reactions to routine vaccines range from 1 per 50000 doses for diphtheria-tetanus-pertussis to approximately 1 per 500000 to 1000000 doses for most other vaccines. In a large study from New Zealand, data were collected during a 5-year period on 15 marketed vaccines and revealed an estimated rate of 1 immediate hypersensitivity reaction per 450000 doses of vaccine administered. Another large study, conducted within the Vaccine Safety Datalink, described a range of reaction rates to >7.5 million doses. Depending on the study design and the time after the immunization event, reaction rates varied from 0.65 cases per million doses to 1.53 cases per million doses when additional allergy codes were included. For some vaccines, particularly when allergens such as gelatin are part of the formulation (eg, Japanese encephalitis), higher rates of serious allergic reactions may occur. Although these per-dose estimates suggest that true hypersensitivity reactions are quite rare, the large number of doses that are administered, especially for the commonly used vaccines, makes this a relatively common clinical problem. In this review, we present background information on vaccine hypersensitivity, followed by a detailed algorithm that provides a rational and organized approach for the evaluation and treatment of patients with suspected hypersensitivity. We then include 3 cases of suspected allergic reactions to vaccines that have been referred to the Clinical Immunization Safety Assessment network to demonstrate the practical application of the algorithm.
基于改进RRT算法的无人机航迹规划%Path planning of UAV based on the improved rapidly-exploring random tree algorithm
崔挺; 李俨; 张明庄
2013-01-01
为了提高无人机的作战效率,航迹规划系统必须为无人机设计出安全系数高,能量消耗少,处理时间短,同时还必须满足飞行器自身物理特性的威胁回避轨迹.基于上述研究目的,本文选择快速随机搜索树算法(RRT)作为迹规划航算法主体,结合Dijkstra算法改进了RRT算法,完成最小航迹代价飞行轨迹的设计.%In order to improve the operational efficiency of the uav,path planning for uav system must design a high safety coefficient,less energy consumption,the short processing time,but also must satisfy the physical characteristics of the vehicle itself threat avoidance path.Based on the above research purpose,this article chooses fast rando.m-exploring search tree algorithm (RRT) as a trace planning navigation algorithm,combined with the main Dijkstra algorithm improved the RRT algorithm,complete the minimum path cost trajectory design.
面向信号测试的路径搜索算法研究%Research on path search algorithm for signal-oriented test
王怡苹; 李文海; 文天柱
2013-01-01
面向信号的测试是未来自动测试系统发展的趋势.信号传输路径的搜索算法是ATS软件平台内核需要解决的关键问题.本文首先给出开关资源的物理模型和数学模型,结合图论中求最短路问题的Dijkstra算法,研究了通路中继电器最少的路径搜索算法；再以继电器可靠性为基础,给出了可靠性最高的路径搜索算法,实现了通路中继电器的均衡使用；最后以某ATS工程项目中使用的较复杂组合矩阵为实例,验证了算法的可行性、有效性及相互关系,本文给出的路径搜索算法已应用于软件平台内核设计,能正确地完成测试任务.%Signal-oriented test is the development trend of next generation automatic test system (ATS),and signal transmission path search algorithm is the key problem that the kernel of ATS software platform needs to resolve.Firstly,this paper introduces the physical model and math model of switch resources;the path search algorithm with least relays is introduced based on the Dijkstra algorithm that is used to resolve shortest path problem in graph theory.Then based on relay reliability,the highest reliability path search algorithm is introduced to fulfill the balanced usage of relays in the path.A complex combination matrix used in a certain ATS engineering project is used as an example to verify the feasibility,validity and relation of the algorithm.The proposed path search algorithm has been used in the kernel design of the software platform,and it can complete the practical test tasks correctly.
A preferential shared path protection algorithm for WDM optical network%WDM光网络中一种优先共享通路保护算法
赵太飞; 王文科; 刘龙
2012-01-01
为了提高波分复用光网络的可靠性,常采用分段共享通路保护算法,该方法通常要求保护通路要均匀分段并且应满足共享风险链路组约束,网络业务的阻塞率也就比较高,因此提出了用优先共享通路保护算法来降低业务阻塞率.通过计算机仿真进行了理论分析和实验验证,取得了两种保护算法下的业务阻塞率和资源预留比的数据.结果表明,优先共享保护通路算法能够有效地融合分段共享通路保护算法的优点,同时在业务的阻塞率和资源预留比方面优于分段共享保护通路算法.%In order to improve the reliability of wavelength division multiplexing ( WDM), the segmented shared path protection ( SSPP) algorithm is usually adopted. It requires equal length segmentation in WDM optical networks and it must obey the shared risk link group (SRLG) constraint. When searching protection path, the SRLG constraint will lead the call blocking probability of the networks to rise. In order to reduce the call blocking probability, a new path protection algorithm, so-called preferential shared path protection (PSPP) was proposed. The simulation of SSPP and PSPP algorithms was done in the discrete event emulation system. The result shows the call blocking probability of the PSPP algorithm is better than that of the SSPP algorithm, and the resource reservation ratio of PSPP is also relatively better.
An interactive code (NETPATH) for modeling NET geochemical reactions along a flow PATH, version 2.0
Plummer, L. Niel; Prestemon, Eric C.; Parkhurst, David L.
1994-01-01
NETPATH is an interactive Fortran 77 computer program used to interpret net geochemical mass-balance reactions between an initial and final water along a hydrologic flow path. Alternatively, NETPATH computes the mixing proportions of two to five initial waters and net geochemical reactions that can account for the observed composition of a final water. The program utilizes previously defined chemical and isotopic data for waters from a hydrochemical system. For a set of mineral and (or) gas phases hypothesized to be the reactive phases in the system, NETPATH calculates the mass transfers in every possible combination of the selected phases that accounts for the observed changes in the selected chemical and (or) isotopic compositions observed along the flow path. The calculations are of use in interpreting geochemical reactions, mixing proportions, evaporation and (or) dilution of waters, and mineral mass transfer in the chemical and isotopic evolution of natural and environmental waters. Rayleigh distillation calculations are applied to each mass-balance model that satisfies the constraints to predict carbon, sulfur, nitrogen, and strontium isotopic compositions at the end point, including radiocarbon dating. DB is an interactive Fortran 77 computer program used to enter analytical data into NETPATH, and calculate the distribution of species in aqueous solution. This report describes the types of problems that can be solved, the methods used to solve problems, and the features available in the program to facilitate these solutions. Examples are presented to demonstrate most of the applications and features of NETPATH. The codes DB and NETPATH can be executed in the UNIX or DOS1 environment. This report replaces U.S. Geological Survey Water-Resources Investigations Report 91-4078, by Plummer and others, which described the original release of NETPATH, version 1.0 (dated December, 1991), and documents revisions and enhancements that are included in version 2.0. 1 The
Solving the SAT problem using a DNA computing algorithm based on ligase chain reaction.
Wang, Xiaolong; Bao, Zhenmin; Hu, Jingjie; Wang, Shi; Zhan, Aibin
2008-01-01
A new DNA computing algorithm based on a ligase chain reaction is demonstrated to solve an SAT problem. The proposed DNA algorithm can solve an n-variable m-clause SAT problem in m steps and the computation time required is O (3m+n). Instead of generating the full-solution DNA library, we start with an empty test tube and then generate solutions that partially satisfy the SAT formula. These partial solutions are then extended step by step by the ligation of new variables using Taq DNA ligase. Correct strands are amplified and false strands are pruned by a ligase chain reaction (LCR) as soon as they fail to satisfy the conditions. If we score and sort the clauses, we can use this algorithm to markedly reduce the number of DNA strands required throughout the computing process. In a computer simulation, the maximum number of DNA strands required was 2(0.48n) when n=50, and the exponent ratio varied inversely with the number of variables n and the clause/variable ratio m/n. This algorithm is highly space-efficient and error-tolerant compared to conventional brute-force searching, and thus can be scaled-up to solve large and hard SAT problems.
Effect of low and high heating rates on reaction path of Ni(V)/Al multilayer
Maj, Łukasz, E-mail: l.maj@imim.pl [Institute of Metallurgy and Materials Science, Polish Academy of Sciences, 25 Reymonta St., 30-059 Kraków (Poland); Morgiel, Jerzy; Szlezynger, Maciej [Institute of Metallurgy and Materials Science, Polish Academy of Sciences, 25 Reymonta St., 30-059 Kraków (Poland); Bała, Piotr; Cios, Grzegorz [AGH University of Science and Technology, Academic Centre for Materials and Nanotechnology, 30 Kawiory St., 30-055 Kraków (Poland)
2017-06-01
The effect of heating rates of Ni(V)/Al NanoFoils{sup ®} was investigated with transmission electron microscopy (TEM). The Ni(V)/Al were subjected to heating by using differential scanning calorimetry (DSC), in-situ TEM or electric pulse. Local chemical analysis was carried out using energy dispersive X-ray spectroscopy (EDS). Phase analysis was done with X-ray diffractions (XRD) and selected area electron diffractions (SAED). The experiments showed that slow heating in DSC results in development of separate exothermic effects at ∼230 °C, ∼280 °C and ∼390 °C, corresponding to precipitation of Al{sub 3}Ni, Al{sub 3}Ni{sub 2} and NiAl phases, respectively, i.e. like in vanadium free Ni/Al multilayers. Further heating to 700 °C allowed to obtain a single phase NiAl foil. The average grain size (g.s.) of NiAl phase produced in the DSC heat treated foil was comparable with the Ni(V)/Al multilayer period (∼50 nm), whereas in the case of reaction initiated with electric pulse the g.s. was in the micrometer range. Upon slow heating vanadium tends to segregate to zones parallel to the original multilayer internal interfaces, while in SHS process vanadium-rich phases precipitates at grain boundaries of the NiAl phase. - Highlights: • Peaks in DSC heating of Ni(V)/Al were explained by in-situ TEM observations. • Nucleation of Al{sub 3}Ni, Al{sub 3}Ni{sub 2} and NiAl at slow heating of Ni(V)/Al was documented. • Near surface NiAl obtained from NanoFoil show Ag precipitates at grain boundaries.
Path Planning for UAV Based on Mixed Ant Colony Algorithm%基于混合蚁群算法的无人机航路规划
税薇; 葛艳; 韩玉; 魏振钢; 孟友新
2011-01-01
The key and difficult problem of UAV path planning is how to satisfy safety and real-time environment,meanwhile, a global path-planning and a local path-planning are considered to improve operational efficiency and survival probability. For this question, according to the existing research of UAV path planning, the method of synthesizing Ant Colony Algorithm (ACA) and Artificial Potential Field (APF) was drscussed. ACA was used as a global route-planning algorithm,and APF was used as a local route-planning algorithm. Simulation results verify that the efficiency of the algorithm can provide some reference value to related researchers.%无人机(UAV)航路规划的热点和难点在于如何满足安全性和实时性的同时,兼顾全局路径规划和局部路径重规划,以提高无人机的作战效率和生存概率.针对这一问题,在现有无人机航路规划研究基础之上,提出采用蚁群算法与人工势场法相结合的方法.蚁群算法用于全局航路规划,人工势场法用于局部路径重规划.仿真结果表明,两种算法结合所得优化航路较好反映了算法的有效性,可以为航路规划辅助决策研究提供借鉴和参考.
Muller, Christophe; Marcou, Gilles; Horvath, Dragos; Aires-de-Sousa, João; Varnek, Alexandre
2012-12-21
Machine learning (SVM and JRip rule learner) methods have been used in conjunction with the Condensed Graph of Reaction (CGR) approach to identify errors in the atom-to-atom mapping of chemical reactions produced by an automated mapping tool by ChemAxon. The modeling has been performed on the three first enzymatic classes of metabolic reactions from the KEGG database. Each reaction has been converted into a CGR representing a pseudomolecule with conventional (single, double, aromatic, etc.) bonds and dynamic bonds characterizing chemical transformations. The ChemAxon tool was used to automatically detect the matching atom pairs in reagents and products. These automated mappings were analyzed by the human expert and classified as "correct" or "wrong". ISIDA fragment descriptors generated for CGRs for both correct and wrong mappings were used as attributes in machine learning. The learned models have been validated in n-fold cross-validation on the training set followed by a challenge to detect correct and wrong mappings within an external test set of reactions, never used for learning. Results show that both SVM and JRip models detect most of the wrongly mapped reactions. We believe that this approach could be used to identify erroneous atom-to-atom mapping performed by any automated algorithm.
Efficient Path Planning Algorithm in Three Dimensions for UAV%无人机快速三维航迹规划算法
尹高扬; 周绍磊; 吴青坡
2016-01-01
To satisfy the real⁃time requirement of path planning in three dimensions for unmanned aerial vehicle, a path planning algorithm based on rapidly⁃exploring random tree is proposed. By random sampling point in configura⁃tion space, the search will be guided to empty area, thus the algorithm can search the high⁃dimension space quickly and efficiently according to the current environment, which can be used in real⁃time path planner. By introducing the path length constraint, the search tree will explore along the direction of the near optimal path. The proposed al⁃gorithm overcomes the disadvantage of basic RRT algorithm that only to quickly get feasible path, unable to obtain near optimal path. During the search process, the path constraints of UAV and the terrain information are fully uti⁃lized, so that the path generated by the algorithm can avoid terrain and threat automatically, and meet the dynamic constraints of UAV. Simulations for the algorithm are made on a generated virtual digital map. Simulation results demonstrated that this proposed method can complete path planning mission in three dimensions quickly and effec⁃tively.%针对无人机三维航迹规划的实时性问题，提出了基于快速扩展随机树的三维航迹规划方法。该算法能够根据当前环境快速有效搜索规划空间，通过随机采样点将搜索导向空白区域，使三维航迹规划能够用于实时航迹规划。通过引入航迹距离约束，搜索树将沿着路径距离最短的近似最优航迹的方向进行扩展，克服了基本快速扩展随机树方法随机性强，只能快速获得可行航迹，无法获得较优航迹的缺点。在搜索过程中无人机的航迹约束条件和地形信息得到了充分利用，使算法生成的航迹能够自动回避地形和威胁，同时满足无人机的动力学约束。通过生成的虚拟数字地图对算法进行了仿真验证，仿真结果表明该方法能够快速有效
An Instruction Scheduling Algorithm Based on Weighted Paths%基于加权路径的指令调度算法
路璐; 安虹; 王莉; 王耀彬; 曾斌
2009-01-01
随着线延迟的逐渐增加,指令调度技术作为一种可以有效减少处理器片上通信的技术日益重要.本文介绍一种分片式处理器结构上基于加权路径的指令调度算法,该算法利用已经放置好的指令--锚指令信息精确计算路径长度,再用指令所在路径长度作为权值对指令进行调度.实验结果表明,本算法实现的调度器IPC比已有的两种TRIPS调度算法的IPC分别提高了21%和3%.%Growing on-chip wire delay makes instruction scheduling a more important compiler technique to decrease on-chip communication. This paper describes a compiler scheduling algorithm called weighted path scheduling, which uses the path length as the weight when scheduling instructions. To precisely calculate the weight of the path, we make use of previ-ously scheduled instructions-anchor instructions. Our experimental results show that this algorithm achieves a 21% and 3% average performance improvement over two prior scheduling algorithms of TRIPS.
Hueschen, Richard M.
1988-01-01
This report contains results of flight tests for three path update algorithms designed to provide smooth transition for an aircraft guidance system from DME, VORTAC, and barometric navaids to the more precise MLS by modifying the desired 3-D flight path. The first algorithm, called Zero Cross Track, eliminates the discontinuity in cross-track and altitude error at transition by designating the first valid MLS aircraft position as the desired first waypoint, while retaining all subsequent waypoints. The discontinuity in track angle is left unaltered. The second, called Tangent Path, also eliminates the discontinuity in cross-track and altitude errors and chooses a new desired heading to be tangent to the next oncoming circular arc turn. The third, called Continued Track, eliminates the discontinuity in cross-track, altitude, and track angle errors by accepting the current MLS position and track angle as the desired ones and recomputes the location of the next waypoint. The flight tests were conducted on the Transportation Systems Research Vehicle, a small twin-jet transport aircraft modified for research under the Advanced Transport Operating Systems program at Langley Research Center. The flight tests showed that the algorithms provided a smooth transition to MLS.
R Bagherzadeh; Sattar Ebrahimi; Moein Goodarzi
2013-07-01
The reaction paths of hydrogen trioxide (HO3) with sulphur dioxide (SO2) have been investigated on the doublet potential energy surface, theoretically. All species of the title reaction have been optimized at the PMP2(FC)/cc-pVDZ computational level. Energetic data have been obtained at the CCSD(T)//PMP2 level employing the cc-pVDZ basis set. No stable collision complexes have been found between the SO2 and HO3 molecules. Therefore, the SO2 + HO3 reaction starts without initial associations. The four possible paths, P1 through P4, have been obtained for the formation of SO3 (D3h) + HOO$^{\\bullet}$ product. Our results show that these four paths include relatively high energy barriers to produce the final product of the SO3 (D3h) + HOO$^{\\bullet}$. Therefore, the SO2 + HO3 → SO3(D3h) + HOO$^{\\bullet}$ reaction is difficult to perform under atmospheric conditions. This means that the importance of SO2 + HO3 → SO3 (D3h) + HOO$^{\\bullet}$ reaction increases with increasing temperature and, this reaction plays an important role in the SO3(D3h) production as the main molecule of the formation of acid rain at high temperatures.
The small-voxel tracking algorithm for simulating chemical reactions among diffusing molecules
Seitaridou, Effrosyni
2014-01-01
Simulating the evolution of a chemically reacting system using the bimolecular propensity function, as is done by the stochastic simulation algorithm and its reaction-diffusion extension, entails making statistically inspired guesses as to where the reactant molecules are at any given time. Those guesses will be physically justified if the system is dilute and well-mixed in the reactant molecules. Otherwise, an accurate simulation will require the extra effort and expense of keeping track of the positions of the reactant molecules as the system evolves. One molecule-tracking algorithm that pays careful attention to the physics of molecular diffusion is the enhanced Green's function reaction dynamics (eGFRD) of Takahashi, Tănase-Nicola, and ten Wolde [Proc. Natl. Acad. Sci. U.S.A.141, 2473 (2010)]. We introduce here a molecule-tracking algorithm that has the same theoretical underpinnings and strategic aims as eGFRD, but a different implementation procedure. Called the small-voxel tracking algorithm (SVTA), it combines the well known voxel-hopping method for simulating molecular diffusion with a novel procedure for rectifying the unphysical predictions of the diffusion equation on the small spatiotemporal scale of molecular collisions. Indications are that the SVTA might be more computationally efficient than eGFRD for the problematic class of non-dilute systems. A widely applicable, user-friendly software implementation of the SVTA has yet to be developed, but we exhibit some simple examples which show that the algorithm is computationally feasible and gives plausible results. PMID:25527927
A comparison of Eulerian and Lagrangian transport and non-linear reaction algorithms
Benson, David A.; Aquino, Tomás; Bolster, Diogo; Engdahl, Nicholas; Henri, Christopher V.; Fernàndez-Garcia, Daniel
2017-01-01
When laboratory-measured chemical reaction rates are used in simulations at the field-scale, the models typically overpredict the apparent reaction rates. The discrepancy is primarily due to poorer mixing of chemically distinct waters at the larger scale. As a result, realistic field-scale predictions require accurate simulation of the degree of mixing between fluids. The Lagrangian particle-tracking (PT) method is a now-standard way to simulate the transport of conservative or sorbing solutes. The method's main advantage is the absence of numerical dispersion (and its artificial mixing) when simulating advection. New algorithms allow particles of different species to interact in nonlinear (e.g., bimolecular) reactions. Therefore, the PT methods hold a promise of more accurate field-scale simulation of reactive transport because they eliminate the masking effects of spurious mixing due to advection errors inherent in grid-based methods. A hypothetical field-scale reaction scenario is constructed and run in PT and Eulerian (finite-volume/finite-difference) simulators. Grid-based advection schemes considered here include 1st- to 3rd-order spatially accurate total-variation-diminishing flux-limiting schemes, both of which are widely used in current transport/reaction codes. A homogeneous velocity field in which the Courant number is everywhere unity, so that the chosen Eulerian methods incur no error when simulating advection, shows that both the Eulerian and PT methods can achieve convergence in the L1 (integrated concentration) norm, but neither shows stricter pointwise convergence. In this specific case with a constant dispersion coefficient and bimolecular reaction A + B → P , the correct total amount of product is 0.221MA0, where MA0 is the original mass of reactant A. When the Courant number drops, the grid-based simulations can show remarkable errors due to spurious over- and under-mixing. In a heterogeneous velocity field (keeping the same constant and
A global reaction route mapping-based kinetic Monte Carlo algorithm
Mitchell, Izaac; Irle, Stephan; Page, Alister J.
2016-07-01
We propose a new on-the-fly kinetic Monte Carlo (KMC) method that is based on exhaustive potential energy surface searching carried out with the global reaction route mapping (GRRM) algorithm. Starting from any given equilibrium state, this GRRM-KMC algorithm performs a one-step GRRM search to identify all surrounding transition states. Intrinsic reaction coordinate pathways are then calculated to identify potential subsequent equilibrium states. Harmonic transition state theory is used to calculate rate constants for all potential pathways, before a standard KMC accept/reject selection is performed. The selected pathway is then used to propagate the system forward in time, which is calculated on the basis of 1st order kinetics. The GRRM-KMC algorithm is validated here in two challenging contexts: intramolecular proton transfer in malonaldehyde and surface carbon diffusion on an iron nanoparticle. We demonstrate that in both cases the GRRM-KMC method is capable of reproducing the 1st order kinetics observed during independent quantum chemical molecular dynamics simulations using the density-functional tight-binding potential.
Friedlander, E.M.; Gimpel, R.W.; Heckman, H.H.; Karant, Y.J.; Judek, B.; Ganssauge, E.
1982-08-01
We present in detail the description and the analysis of two independent experiments using Bevalac beams of {sup 16}O and {sup 56}Fe. From their results it is concluded that the reaction mean free paths of relativistic projectile fragments, 3 {<=} Z {<=} 26, are shorter for a few centimeters after emission than at large distances where they are compatible with values predicted from experiments on beam nuclei. The probability that this effect is due to a statistical fluctuation is <10{sup -3}. The effect is enhanced in later generations of fragments, the correlation between successive generations suggesting a kind of "memory" for the anomaly. Various systematic and spurious effects as well as conventional explanations are discussed mainly on the basis of direct experimental observations internal to our data, and found not to explain our results. The data can be interpreted by the relatively rare occurrence of anomalous fragments that interact with an unexpectedly large cross section. The statistical methods used in the analysis of the observations are fully described.
Li, Fajie
2011-01-01
This unique text/reference reviews algorithms for the exact or approximate solution of shortest-path problems, with a specific focus on a class of algorithms called rubberband algorithms. Discussing each concept and algorithm in depth, the book includes mathematical proofs for many of the given statements. Topics and features: provides theoretical and programming exercises at the end of each chapter; presents a thorough introduction to shortest paths in Euclidean geometry, and the class of algorithms called rubberband algorithms; discusses algorithms for calculating exact or approximate ESPs i
Wolery, T.J.; Daveler, S.A.
1992-10-09
EQ6 is a FORTRAN computer program in the EQ3/6 software package (Wolery, 1979). It calculates reaction paths (chemical evolution) in reacting water-rock and water-rock-waste systems. Speciation in aqueous solution is an integral part of these calculations. EQ6 computes models of titration processes (including fluid mixing), irreversible reaction in closed systems, irreversible reaction in some simple kinds of open systems, and heating or cooling processes, as well as solve ``single-point`` thermodynamic equilibrium problems. A reaction path calculation normally involves a sequence of thermodynamic equilibrium calculations. Chemical evolution is driven by a set of irreversible reactions (i.e., reactions out of equilibrium) and/or changes in temperature and/or pressure. These irreversible reactions usually represent the dissolution or precipitation of minerals or other solids. The code computes the appearance and disappearance of phases in solubility equilibrium with the water. It finds the identities of these phases automatically. The user may specify which potential phases are allowed to form and which are not. There is an option to fix the fugacities of specified gas species, simulating contact with a large external reservoir. Rate laws for irreversible reactions may be either relative rates or actual rates. If any actual rates are used, the calculation has a time frame. Several forms for actual rate laws are programmed into the code. EQ6 is presently able to model both mineral dissolution and growth kinetics.
Path Planning Algorithm for Smart Wheelchair Indoor Navigation%智能轮椅室内导航路径规划算法
徐彪; 蒋朝阳; 朱健铭; 陈真诚
2015-01-01
The smart wheelchair improve the quality of life and give more freedom for people who lose the ability to walk. Path planning for smart wheelchair technology is one of an important Technology. Research method The degree of difficulty walking in the actual environment is difference. A new path planning algorithm for a kind of navigation methods to find the optimal path has been proved. Firstly the grid modeling has been established for indoor environment, and the adjacent relation with the improved A* algorithm has been used to optimal planning of global path between the two positions, then the virtual force field algorithm can be implemented for the local path planning on the way. Results and Conclusions This algorithm just needs to gather the information where you want to reach, then the smart wheelchair can automatically navigate to the destination. The experiments show that the algorithm is applied to the smart wheelchair indoor navigation system to reach the expectations and has the advantages of quick response, stable performance, easy to use and strong extensibility.%智能轮椅为丧失行走能力的人提高生活质量和生活自由度. 适用于智能轮椅的路径规划问题是其重要的技术之一. 实际环境中行走的难易程度是有区别的, 对此提出一种新的路径规划算法, 即寻找最优路径的导航方法, 对室内环境进行栅格模型建模, 并利用最邻近关系结合改进的 A*算法来规划两个位置之间的最优全局路径, 采用虚拟力场算法实现途中的局部路径规划. 此算法只需要采集用户需要到达目的地的信息, 智能轮椅能自动导航到达目的地, 经实验验证, 该算法运用到智能轮椅室内导航系统中路径得到较好的改善并具有反应快、工作稳定可靠、使用灵活方便和扩展性强等优点.
Han, Miaomiao; Guo, Zhirong; Liu, Haifeng; Li, Qinghua
2017-07-01
This paper studies the influence of different path length computation models and iterative reconstruction algorithms on the quality of transmission reconstruction in Tomographic Gamma Scanning. The research purpose is to quantify and to localize heterogeneous matrices while investigating the recovery of linear attenuation coefficients (LACs) maps in 200 liter drums. Two different path length computation models so called ;point to point (PP); model and ;point to detector (PD); model are coupled with two different transmission reconstruction algorithms - Algebraic Reconstruction Technique (ART) with non-negativity constraint, and Maximum Likelihood Expectation Maximization (MLEM), respectively. Thus 4 modes are formed: ART-PP, ART-PD, MLEM-PP, MLEM-PD. The inter-comparison of transmission reconstruction qualities of these 4 modes is taken into account for heterogeneous matrices in the radioactive waste drums. Results illustrate that transmission-reconstructed qualities of MLEM algorithm are better than ART algorithm to get the most accurate LACs maps in good agreement with the reference data simulated by Monte Carlo. Moreover, PD model can be used to assay higher density waste drum and has a greater scope of application than PP model in TGS.
基于重置引用计数器值的BDD路径优化算法%An Algorithm for Minimizing Number of Paths in BDDs
段珊
2011-01-01
Variable swapping as the core of BDD optimization theory has been applied to reduce the size of BDD nodes,this paper from the standpoint of theory and practice of applying the theory to achieve the goal of reducing the number of BDD paths. By redefining the node reference field to achieve a record node path, analysis of variables in the swapping process to obtain the Changes in the amount of local path, introducing the dynamic list to complete recording and propagation of the node path, and eventually got the final path number of BDD node. The algorithm uses the C language completed, integrated into the CUDD package. Experiment result show correction and efficiency of the algorithm.%变量交换作为BDD优化算法的核心理论已成功运用于BDD节点规模的减少,本论文从理论和实践的角度提出了运用该理论实现BDD路径数量减少的目标.通过对节点引用域的重新定义来实现节点路径的记录,分析变量交换过程中本地节点重定向来获取局部路径的改变量,引入动态链表完成节点路径增量的记录和传递,最终在终节点得到了BDD的路径数量.该算法用C语言完成,整合到CUDD软件包,经多个函数的实验测试,证实了这种路径优化算法的正确、有效.
Smoothing of Piecewise Linear Paths
Michel Waringo
2008-11-01
Full Text Available We present an anytime-capable fast deterministic greedy algorithm for smoothing piecewise linear paths consisting of connected linear segments. With this method, path points with only a small influence on path geometry (i.e. aligned or nearly aligned points are successively removed. Due to the removal of less important path points, the computational and memory requirements of the paths are reduced and traversing the path is accelerated. Our algorithm can be used in many different applications, e.g. sweeping, path finding, programming-by-demonstration in a virtual environment, or 6D CNC milling. The algorithm handles points with positional and orientational coordinates of arbitrary dimension.
沈志华; 赵英凯; 吴炜炜
2006-01-01
A new genetic algorithm named niche pseudo-parallel genetic algorithm (NPPGA) is presented for path evolution and genetic op timization of autonomous mobile robot. The NPPGA is an effective improvement to maintain the population diversity as well for the sake of avoiding premature and strengthen parallelism of the population to accelerate the search process combined with niche genetic algorithms and pseudo-parallel genetic algorithms. The proposed approach is evaluated by robotic path optimization, which is a specific application of traveler salesman problem (TSP). Experimental results indicated that a shortest path could be obtained in the practical traveling salesman problem named "Robot tour around Pekin", and the performance conducted by NPPGA is better than simple genetic algorithm (SGA) and distributed paralell genetic algorithms (DPGA).
Talukder, Srijeeta; Sen, Shrabani [Department of Chemistry, University of Calcutta, 92 A P C Road, Kolkata 700 009 (India); Sharma, Rahul [Department of Chemistry, St. Xavier’s College, 30 Mother Teresa Sarani, Kolkata 700 016 (India); Banik, Suman K., E-mail: skbanik@bic.boseinst.ernet.in [Department of Chemistry, Bose Institute, 93/1 A P C Road, Kolkata 700 009 (India); Chaudhury, Pinaki, E-mail: pinakc@rediffmail.com [Department of Chemistry, University of Calcutta, 92 A P C Road, Kolkata 700 009 (India)
2014-03-18
Highlights: • We demonstrate a general strategy to map out reaction paths irrespective of the number of kinetic steps involved. • The objective function proposed does not need the information of gradient norm and eigenvalue of Hessian matrix explicitly. • A stochastic optimizer Simulated Annealing is used in searching reaction path. • The strategy is applied in mapping out the path for conformational changes in pure Ar clusters and Ar{sub N}Xe mixed clusters. - abstract: In this paper we demonstrate a general strategy to map out reaction paths irrespective of the number of kinetic steps required to bring about the change. i.e., whether the transformation takes place in a single step or in multiple steps with the appearance of intermediates. The objective function proposed is unique and works equally well for a concerted or a multiple step pathway. As the objective function proposed does not explicitly involves the calculation of the gradient of the potential energy function or the eigenvalues of the Hessian Matrix during the iterative process, the calculation is computationally economical. To map out the reaction path, we cast the entire problem as one of optimization and the solution is done with the use of the stochastic optimizer Simulated Annealing. The formalism is tested on Argon clusters (Ar{sub N}) and Argon clusters singly doped with Xenon (Ar{sub N-1}Xe). The size of the systems for which the method is applied ranges from N=7-25, where N is the total number of atoms in the cluster. We also test the results obtained by us by comparing with an established gradient only method. Moreover to demonstrate that our strategy can overcome the standard problems of drag method, we apply our strategy to a two dimensional LEPS + harmonic oscillator Potential to locate the TS, in which standard drag method has been seen to encounter problems.
罗义学
2011-01-01
基于智能Petri网构建了物流配送路径的优化模型.通过定义智能Petri网的运行规则,得到了基于智能Petri网的物流配送路径优化算法与计算流程,分析了车辆在交叉口的实际延误阻抗时配送分析的影响.该算法具有求解不需要对物流网络图作任何修改和容易实现配送过程的动态模拟的特点,利用该算法可以获取配送车辆从出发点到城市中任何一个节点的最优路径.将算例与改进的Dijkstra算法进行了对比分析,结果表明了该算法的可行性和有效性.%Based on the intelligent Petri net, a logistic delivery path optimization model is constructed. Through defining specific running rules for the intelligent Petri net, an optimization algorithm of logistic delivery path is put forward and calculation process is presented. The actual delay experienced by delivery vehicles at intersections is taken into account for analysis. The algorithm needn' t modify the logistic network and the dynamic version of the delivery process is simulated easily. The shortest path for a delivery vehicle travelling from the starting point to any point in the city is founded. By comparing with the Dijkstra algorithm in a case study, it is proven that our algorithm is both applicable and efficient.
Schalock, Peter C; Menné, Torkil; Johansen, Jeanne D
2011-01-01
algorithm to guide the selection of screening allergen series for patch testing is provided. At a minimum, an extended baseline screening series and metal screening is necessary. Static and dynamic orthopaedic implants, intravascular stent devices, implanted defibrillators and dental and gynaecological......Cutaneous and systemic hypersensitivity reactions to implanted metals are challenging to evaluate and treat. Although they are uncommon, they do exist, and require appropriate and complete evaluation. This review summarizes the evidence regarding evaluation tools, especially patch and lymphocyte...... transformation tests, for hypersensitivity reactions to implanted metal devices. Patch test evaluation is the gold standard for metal hypersensitivity, although the results may be subjective. Regarding pre-implant testing, those patients with a reported history of metal dermatitis should be evaluated by patch...
基于进化算法的多无人机协同航路规划%Cooperative Path Planning of Multi-UAV Based on Evolutionary Algorithm
李子杰; 刘湘伟
2015-01-01
以突防航路时域协同指数、空域协同指数、突防时长指数和受威胁指数为规划目标，以最小直线航路段长度、可飞空域、续航能力和进入任务航路方向为约束，构建了多无人机协同突防航路规划模型。结合模型特点，利用合作型协同进化遗传算法对该模型进行求解。%Aiming at maximizing penetration path time synergy index and penetration path airspace synergy index, minimizing penetration time length index and intimidate index, restricted by the minimum length of straight path, flyable space, endurance and intro-mission route direction, the penetration path planning model of Multiple Unmanned Serial Vehicle (Multi-UAV)is constructed. Combining its characteristic, the model is solved by use of Cooperative Co-evolutionary Genetic Algorithms(CCGA).
Nguyen Thanh Long
2015-02-01
Full Text Available MANET (short for Mobile Ad-Hoc Network consists of a set of mobile network nodes, network configuration changes very fast. In content based routing, data is transferred from source node to request nodes is not based on destination addresses. Therefore, it is very flexible and reliable, because source node does not need to know destination nodes. If We can find multiple paths that satisfies bandwidth requirement, split the original message into multiple smaller messages to transmit concurrently on these paths. On destination nodes, combine separated messages into the original message. Hence it can utilize better network resources, causes data transfer rate to be higher, load balancing, failover. Service Oriented Routing is inherited from the model of content based routing (CBR, combined with several advanced techniques such as Multicast, multiple path routing, Genetic algorithm to increase the data rate, and data encryption to ensure information security. Fuzzy logic is a logical field study evaluating the accuracy of the results based on the approximation of the components involved, make decisions based on many factors relative accuracy based on experimental or mathematical proof. This article presents some techniques to support multiple path routing from one network node to a set of nodes with guaranteed quality of service. By using these techniques can decrease the network load, congestion, use network resources efficiently.
Luo Wei
2017-01-01
Full Text Available Power transformer is one of the most important equipment in power system. In order to predict the potential fault of power transformer and identify the fault types correctly, we proposed a transformer fault intelligent diagnosis model based on chemical reaction optimization (CRO algorithm and relevance vector machine(RVM. RVM is a powerful machine learning method, which can solve nonlinear, high-dimensional classification problems with a limited number of samples. CRO algorithm has well global optimization and simple calculation, so it is suitable to solve parameter optimization problems. In this paper, firstly, a multi-layer RVM classification model was built by binary tree recognition strategy. Secondly, CRO algorithm was adopted to optimize the kernel function parameters which could enhance the performance of RVM classifiers. Compared with IEC three-ratio method and the RVM model, the CRO-RVM model not only overcomes the coding defect problem of IEC three-ratio method, but also has higher classification accuracy than the RVM model. Finally, the new method was applied to analyze a transformer fault case, Its predicted result accord well with the real situation. The research provides a practical method for transformer fault intelligent diagnosis and prediction.
Algorithm of high-speed machining tool path for molar crown%磨牙冠高速精加工刀轨生成算法
孙全平
2009-01-01
磨牙冠不仅微小、壁薄,而且外形极其复杂,尤其牙合面尖、嵴、窝个性化特点明显,采用传统加工工艺很难快速、精确地加工出修复体外形.为高效地加工出磨牙冠,提出了基于顶点的STL数据模型快速等距算法.应用行切法、小刀具,实现了微径高速铣削精加工刀轨的生成.利用米克朗UCP800高速加工中心,成功地加工出氧化铅陶瓷磨牙全冠.经综合测试表明,算法运算速度快,生成加工刀轨数据量小,加工平稳性好.%Molar crown is not only very small and thin-wall, but also has complex profile, especially occlusal surface that distributes many cusps, ridges and fossas is obviously different. If conventional processing method is used, it is impossible to rapidly and exactly machine molar prosthesis. To enhance machining velocity and improve surface precision of molar crown, an algorithm of entity rapid offset based on STL format is put forward. Applying Zigzag tool path planning and micro-machining cutter, finishing tool path for high speed milling molar prosthesis is generated. In terms of Mikron UCP800 high-speed machine center, molar all-crown whose material is Zirconia is successfully machined.Through test results show that the algorithm of tool path generation works fast, and amount of tool paths is rather few, moreover cutter feeds placidly.
Prediction of Reaction Kinetic of Al- Doura Heavy Naphtha Reforming Process Using Genetic Algorithm
Ramzy H. Saihod
2015-07-01
Full Text Available In this study, genetic algorithm was used to predict the reaction kinetics of Iraqi heavy naphtha catalytic reforming process located in Al-Doura refinery in Baghdad. One-dimensional steady state model was derived to describe commercial catalytic reforming unit consisting of four catalytic reforming reactors in series process. The experimental information (Reformate composition and output temperature for each four reactors collected at different operating conditions was used to predict the parameters of the proposed kinetic model. The kinetic model involving 24 components, 1 to 11 carbon atoms for paraffins and 6 to 11 carbon atom for naphthenes and aromatics with 71 reactions. The pre-exponential Arrhenius constants and activation energies were determined after fine tuning of the model results with experimental data. The input to the optimization is the compositions for 21 components and the temperature for the effluent stream for each one of the four reactors within the reforming process while the output of optimization is 142 predicted kinetic parameters for 71 reactions within reforming process. The differential optimization technique using genetic algorithm to predict the parameters of the kinetic model. To validate the kinetic model, the simulation results of the model based on proposed kinetic model was compared with the experimental results. The comparison between the predicted and commercially results shows a good agreement, while the percentage of absolute error for aromatics compositions are (7.5, 2, 8.3, and 6.1% and the temperature absolute percentage error are (0.49, 0.5, 0.01, and 0.3% for four reactors respectively.
An algorithm for the path-planning with multiple constraints%一种多约束条件下路径规划算法研究
李汉轩; 李志华; 吕春生
2012-01-01
针对目前导航系统中重要的多约束条件下路径规划功能,结合A＊算法和蚁群算法提出一种新的不确定算法,该算法首先将多约束条件进行融合使其适合蚁群转移,并在基本蚁群算法基础上采用了A＊算法的评估指标,为蚁群转移时提供最优预测收敛点。通过实验证明该算法可以大幅度降低时间消耗,并且全局收敛性强,计算结果稳定。%In view of the important path planning function under multi-constraint conditions in current navigation systems,a new uncertainty algorithm is proposed which is the connection of A＊ algorithm and ant Colony algorithm.To adapt transfer of ant Colony algorithm,firstly,multiple constraints is integrated.Then,I took use of the concept of evaluation indicators in A＊ algorithm to get the optimal forecast convergence point for ant colony transfer.Basing on above operation,the results show that the algorithn has,strong global convergence,and substantially reduced time consumption.
基于模糊算法的移动机器人路径规划%Mobile Robot Path Planning Based on Fuzzy Algorithms
陈卫东; 朱奇光
2011-01-01
为了解决移动机器人最优路径规划问题,提出一种基于模糊算法的移动机器人路径规划策略.利用超声波传感器对环境进行探测,得到关于障碍物和目标的信息.运用模糊推理将障碍位置信息与目标位置信息模糊化,建立模糊规则并解模糊最终使机器人可以很好的避障,从而实现了移动机器人的路径规划.仿真实验结果表明了模糊算法优于势场法和A*算法,具有较高的有效性和可行性.%To solve the optimal path planning problem of mobile robots,a novel mobile robot path planning strategy based on fuzzy algorithm has been proposed. The environment situation has been detected using ultrasonic sensors to obtain the information about obstacles and goals. Fuzzy the position informations about obstacles and goals through fuzzy reasoning and establish the fuzzy rules. By defuzzification could make the mobile robot avoid obstacles successfully and find the optimal path. The simulation experiment results have shown that the fuzzy algorithm mentioned above is superior to potential field method and the A * algorithm with more effectiveness and feasibility.
改进免疫算法在无人机航线规划中的应用%Application of Improved Immune Algorithm in UAV Path Planning
缪永飞; 钟珞; 陈艳恩; 夏罗生
2015-01-01
Unmanned aerial vehicle ( UAV) path planning method was discussed.It's designed to establish a much more ob-jective and reasonable planned path which could blend with real digital terrain.On account of the slow convergence rate, and that immune algorithm is easily to fall into local optimum, an improved immune algorithm based on tabu criterion was proposed, and it was used to solve the UAV path planning problem.It aimed at determining the individual evaluation criteria through gene enco-ding and a series of genetic manipulation such as crossover and hyper-mutation.Through the optimization of initial track of UAV on a digital elevation map which was proposed on real geographical information.The flight path could meet various constraints. The comparative analysis with ant colony algorithm shows that the algorithm is faster and more effective to get convergent process and good solutions.%针对无人机的航线规划方法展开研究，旨在建立能够融合真实数字地形的，更为客观、合理的航迹规划方法。由于免疫算法易陷入局部最优点及收敛速度过慢等问题，提出了一种基于禁忌准则的改进免疫算法，并应用于无人机航迹规划，其通过基因编码确定个体评价准则、交叉和高频变异等操作，通过在真实的地理环境信息所建立的数字高程地图上进行无人机的初始航迹优化，使航迹能够满足各种约束条件。与蚁群算法对比分析的结果表明，该算法加快了收敛进程，并可求得较优解。
Bayer, Christian
2016-02-20
© 2016 Taylor & Francis Group, LLC. ABSTRACT: In this work, we present an extension of the forward–reverse representation introduced by Bayer and Schoenmakers (Annals of Applied Probability, 24(5):1994–2032, 2014) to the context of stochastic reaction networks (SRNs). We apply this stochastic representation to the computation of efficient approximations of expected values of functionals of SRN bridges, that is, SRNs conditional on their values in the extremes of given time intervals. We then employ this SRN bridge-generation technique to the statistical inference problem of approximating reaction propensities based on discretely observed data. To this end, we introduce a two-phase iterative inference method in which, during phase I, we solve a set of deterministic optimization problems where the SRNs are replaced by their reaction-rate ordinary differential equations approximation; then, during phase II, we apply the Monte Carlo version of the expectation-maximization algorithm to the phase I output. By selecting a set of overdispersed seeds as initial points in phase I, the output of parallel runs from our two-phase method is a cluster of approximate maximum likelihood estimates. Our results are supported by numerical examples.
Vilanova, Pedro
2016-01-07
In this work, we present an extension of the forward-reverse representation introduced in Simulation of forward-reverse stochastic representations for conditional diffusions , a 2014 paper by Bayer and Schoenmakers to the context of stochastic reaction networks (SRNs). We apply this stochastic representation to the computation of efficient approximations of expected values of functionals of SRN bridges, i.e., SRNs conditional on their values in the extremes of given time-intervals. We then employ this SRN bridge-generation technique to the statistical inference problem of approximating reaction propensities based on discretely observed data. To this end, we introduce a two-phase iterative inference method in which, during phase I, we solve a set of deterministic optimization problems where the SRNs are replaced by their reaction-rate ordinary differential equations approximation; then, during phase II, we apply the Monte Carlo version of the Expectation-Maximization algorithm to the phase I output. By selecting a set of over-dispersed seeds as initial points in phase I, the output of parallel runs from our two-phase method is a cluster of approximate maximum likelihood estimates. Our results are supported by numerical examples.
Kostsov, Vladimir; Ionov, Dmitry; Biryukov, Egor; Zaitsev, Nikita
2017-04-01
A built-in operational regression algorithm (REA) of liquid water path (LWP) retrieval supplied by the manufacturer of the RPG-HATPRO microwave radiometer has been compared to a so-called physical algorithm (PHA) based on the inversion of the radiative transfer equation. The comparison has been performed for different scenarios of microwave observations by the RPG-HATPRO instrument that has been operating at St.Petersburg University since June 2012. The data for the scenarios have been collected within the time period December 2012 - December 2014. The estimations of bias and random error for both REA and PHA have been obtained. Special attention has been paid to the analysis of the quality of the LWP retrievals during and after rain events that have been detected by the built-in rain sensor. The estimation has been done of the time period after a rain event when the retrieval quality has to be considered as insufficient.
Amol M. Dalavi
2016-07-01
Full Text Available Optimization of hole-making operations in manufacturing industry plays a vital role. Tool travel and tool switch planning are the two major issues in hole-making operations. Many industrial applications such as moulds, dies, engine block, automotive parts etc. requires machining of large number of holes. Large number of machining operations like drilling, enlargement or tapping/reaming are required to achieve the final size of individual hole, which gives rise to number of possible sequences to complete hole-making operations on the part depending upon the location of hole and tool sequence to be followed. It is necessary to find the optimal sequence of operations which minimizes the total processing cost of hole-making operations. In this work, therefore an attempt is made to reduce the total processing cost of hole-making operations by applying relatively new optimization algorithms known as shuffled frog leaping algorithm and proposed modified shuffled frog leaping algorithm for the determination of optimal sequence of hole-making operations. An industrial application example of ejector plate of injection mould is considered in this work to demonstrate the proposed approach. The obtained results by the shuffled frog leaping algorithm and proposed modified shuffled frog leaping algorithm are compared with each other. It is seen from the obtained results that the results of proposed modified shuffled frog leaping algorithm are superior to those obtained using shuffled frog leaping algorithm.
Kurennov, D. V.; Petunin, A. A.; Repnitskii, V. B.; Shipacheva, E. N.
2016-12-01
The problem of approximating two-dimensional broken line with composite curve consisting of arc and line segments is considered. The resulting curve nodes have to coincide with source broken line nodes. This problem arises in the development of control programs for CNC (computer numerical control) cutting machines, permitting circular interpolation. An original algorithm is proposed minimizing the number of nodes for resulting composite curve. The algorithm is implemented in the environment of the Russian CAD system T-Flex CAD using its API (Application Program Interface). The algorithm optimality is investigated. The result of test calculation along with its geometrical visualization is given.
New exclusive CHIPS-TPT algorithms for simulation of neutron-nuclear reactions
Kosov, M.; Savin, D.
2015-05-01
The CHIPS-TPT physics library for simulation of neutron-nuclear reactions on the new exclusive level is being developed in CFAR VNIIA. The exclusive modeling conserves energy, momentum and quantum numbers in each neutron-nuclear interaction. The CHIPS-TPT algorithms are based on the exclusive CHIPS library, which is compatible with Geant4. Special CHIPS-TPT physics lists in the Geant4 format are provided. The calculation time for an exclusive CHIPS-TPT simulation is comparable to the time of the corresponding Geant4- HP simulation. In addition to the reduction of the deposited energy fluctuations, which is a consequence of the energy conservation, the CHIPS-TPT libraries provide a possibility of simulation of the secondary particles correlation, e.g. secondary gammas, and of the Doppler broadening of gamma lines in the spectrum, which can be measured by germanium detectors.
多核平台并行单源最短路径算法%Parallel Single-source Shortest Path Algorithm on Multi-core Platform
黄跃峰; 钟耳顺
2012-01-01
A multi-thread parallel Single-source Shortest Path(SSSP) algorithm is proposed in multi-cores platform. It employs buckets to sort and uses the similar parallel strategy of A-Stepping algorithm. It does edge relaxations of the same bucket in parallel by slave threads, and searches all buckets in sequence by master thread. Experimental results show that this algorithm performs 4 seconds in the USA road network, achieving a higher speedup compared with serial parallel algorithm using same code.%提出一种多核平台并行单源最短路径算法.采用与Δ-Stepping算法相似的并行策略,通过多个子线程对同一个桶中的弧段进行并行松弛,利用主线程控制串行搜索中桶的序列.实验结果表明,该算法求解全美单源最短路径的时间约为4 s,与使用相同代码实现的串行算法相比,加速比更高.
Alaqtash, Murad; Sarkodie-Gyan, Thompson; Yu, Huiying; Fuentes, Olac; Brower, Richard; Abdelgawad, Amr
2011-01-01
An automated gait classification method is developed in this study, which can be applied to analysis and to classify pathological gait patterns using 3D ground reaction force (GRFs) data. The study involved the discrimination of gait patterns of healthy, cerebral palsy (CP) and multiple sclerosis subjects. The acquired 3D GRFs data were categorized into three groups. Two different algorithms were used to extract the gait features; the GRFs parameters and the discrete wavelet transform (DWT), respectively. Nearest neighbor classifier (NNC) and artificial neural networks (ANN) were also investigated for the classification of gait features in this study. Furthermore, different feature sets were formed using a combination of the 3D GRFs components (mediolateral, anterioposterior, and vertical) and their various impacts on the acquired results were evaluated. The best leave-one-out (LOO) classification accuracy 85% was achieved. The results showed some improvement through the application of a features selection algorithm based on M-shaped value of vertical force and the statistical test ANOVA of mediolateral and anterioposterior forces. The optimal feature set of six features enhanced the accuracy to 95%. This work can provide an automated gait classification tool that may be useful to the clinician in the diagnosis and identification of pathological gait impairments.
Kamibayashi, Yuki; Miura, Shinichi
2016-08-01
In the present study, variational path integral molecular dynamics and associated hybrid Monte Carlo (HMC) methods have been developed on the basis of a fourth order approximation of a density operator. To reveal various parameter dependence of physical quantities, we analytically solve one dimensional harmonic oscillators by the variational path integral; as a byproduct, we obtain the analytical expression of the discretized density matrix using the fourth order approximation for the oscillators. Then, we apply our methods to realistic systems like a water molecule and a para-hydrogen cluster. In the HMC, we adopt two level description to avoid the time consuming Hessian evaluation. For the systems examined in this paper, the HMC method is found to be about three times more efficient than the molecular dynamics method if appropriate HMC parameters are adopted; the advantage of the HMC method is suggested to be more evident for systems described by many body interaction.
A＊算法在游戏寻路中的应用%Application of A ＊ Algorithm in Game Path-finding Development
胡正红; 张俊花
2012-01-01
Path-finding is the basic problem for game designing to solve. Usually, it is completed by breadth-first search algo- rithm. In this paper, it focuses on the feature of path-finding in ＂ Picture Matching＂ game to analyze in detail the application of A ＊ Algorithm in the game, points out the composition of evaluation function, and then gives the improved realization of A ＊ Algorithm combining With the actual condition.%寻路问题是游戏设计解决的基本问题，通常采用广度优先搜索算法完成。针对“连连看”游戏的路径搜索特点，详细地分析了A＊算法在其中的应用，确认最初估价函数的构成，结合实际应用情况，给出了A＊算法的改进及实现。
Miura, Shinichi; Okazaki, Susumu
2001-09-01
In this paper, the path integral molecular dynamics (PIMD) method has been extended to employ an efficient approximation of the path action referred to as the pair density matrix approximation. Configurations of the isomorphic classical systems were dynamically sampled by introducing fictitious momenta as in the PIMD based on the standard primitive approximation. The indistinguishability of the particles was handled by a pseudopotential of particle permutation that is an extension of our previous one [J. Chem. Phys. 112, 10 116 (2000)]. As a test of our methodology for Boltzmann statistics, calculations have been performed for liquid helium-4 at 4 K. We found that the PIMD with the pair density matrix approximation dramatically reduced the computational cost to obtain the structural as well as dynamical (using the centroid molecular dynamics approximation) properties at the same level of accuracy as that with the primitive approximation. With respect to the identical particles, we performed the calculation of a bosonic triatomic cluster. Unlike the primitive approximation, the pseudopotential scheme based on the pair density matrix approximation described well the bosonic correlation among the interacting atoms. Convergence with a small number of discretization of the path achieved by this approximation enables us to construct a method of avoiding the problem of the vanishing pseudopotential encountered in the calculations by the primitive approximation.
Harri Antikainen
2013-10-01
Full Text Available A fair amount of research has been carried out on pathfinding problems in the context of transportation networks, whereas pathfinding in off-network space has received far less interest. In geographic information systems (GIS, the latter is usually associated with the cost surface method, which allows optimum paths to be calculated through rasters in which the value of each cell depicts the cost of traversal through that cell. One of the problems with this method is computational expense, which may be very high with large rasters. In this study, a pathfinding method called Hierarchical Pathfinding A* (HPA*, based on an abstraction strategy, is investigated as an alternative to the traditional approach. The aim of this study is to enhance the method to make it more suitable for calculating paths over cost rasters with nonuniform traversal cost. The method is implemented in GIS and tested with actual data. The results indicate that by taking into account the information embedded in the cost raster, paths of relatively good quality can be calculated while effecting significant savings in computational effort compared to the traditional, nonhierarchical approach.
First-principles modeling of catalysts: novel algorithms and reaction mechanisms
Richard, Bryan Goldsmith
A molecular level understanding of a reaction mechanism and the computation of rates requires knowledge of the stable structures and the corresponding transition states that connect them. Temperature, pressure, and environment effects must be included to bridge the 'materials gap' so one can reasonably compare ab initio (first-principles, i.e., having no empirical parameters) predictions with experimental measurements. In this thesis, a few critical problems pertaining to ab initio modeling of catalytic systems are addressed; namely, 1) the issue of building representative models of isolated metal atoms grafted on amorphous supports, 2) modeling inorganic catalytic reactions in non-ideal solutions where the solvent participates in the reaction mechanism, and 3) bridging the materials gap using ab initio thermodynamics to predict the stability of supported nanoparticles under experimental reaction conditions. In Chapter I, a background on first-principles modeling of heterogeneous and homogenous catalysts is provided. Subsequently, to address the problem of modeling catalysis by isolated metal atoms on amorphous supports, we present in Chapter II a sequential-quadratic programming algorithm that systematically predicts the structure and reactivity of isolated active sites on insulating amorphous supports. Modeling solution phase reactions is also a considerable challenge for first-principles modeling, yet when done correctly it can yield critical kinetic and mechanistic insight that can guide experimental investigations. In Chapter III, we examine the formation of peroxorhenium complexes by activation of H2O2, which is key in selective oxidation reactions catalyzed by CH3ReO3 (methyltrioxorhenium, MTO). New experiments and density functional theory (DFT) calculations were conducted to better understand the activation of H2O2 by MTO and to provide a strong experimental foundation for benchmarking computational studies involving MTO and its derivatives. It was found
A Path Planning Algorithm for UAV Based on Skeleton Algorithm%一种骨架提取的无人机航迹规划法
袁操; 周德云; 张堃
2012-01-01
The Unmanned Aerial Vehicle(UAV) will play a more and more important role in the future, and how to improve its survival-rate and operational effectiveness has become focus of the path-planning. The threat-circles were simplified from threats of radar, antiaircraft missile, landform, no-fly areas and so on, and a skeleton diagram was constructed based on the distribution of the threat-circles. The skeleton graph yielded the feasible paths for travel between a set of threat-circles to avoid the threats. The vector graphics were consisted of the lines whose cost was calculated out according to the specific information of threats. The initial optimal path was obtained, which was shortened according to the need of the threat avoiding. Simulation was made with Matlab platform and the simulation result is presented in the paper.%未来战争中无人机的应用地位将大大提高,如何提高无人机的生存率、作战效率成为航路规划研究的主要方向.将敌方雷达、对空导弹、地形等威胁简化构建成威胁圆,根据威胁圆的分布情况,构造基于威胁圆的规避威胁的骨架化图；结合各具体威胁信息,计算各路径段的代价值,形成有赋值的有向图,计算初始最优航路；利用实际飞行中无人机对威胁规避的要求,对初始航路做缩短处理.运用Matlab编制图形化界面,得到仿真结果的图形显示.
Wiese, Kay Jörg
2016-04-01
We derive and study two different formalisms used for nonequilibrium processes: the coherent-state path integral, and an effective, coarse-grained stochastic equation of motion. We first study the coherent-state path integral and the corresponding field theory, using the annihilation process A+A→A as an example. The field theory contains counterintuitive quartic vertices. We show how they can be interpreted in terms of a first-passage problem. Reformulating the coherent-state path integral as a stochastic equation of motion, the noise generically becomes imaginary. This renders it not only difficult to interpret, but leads to convergence problems at finite times. We then show how alternatively an effective coarse-grained stochastic equation of motion with real noise can be constructed. The procedure is similar in spirit to the derivation of the mean-field approximation for the Ising model, and the ensuing construction of its effective field theory. We finally apply our findings to stochastic Manna sandpiles. We show that the coherent-state path integral is inappropriate, or at least inconvenient. As an alternative, we derive and solve its mean-field approximation, which we then use to construct a coarse-grained stochastic equation of motion with real noise.
Ju Young Kang
2017-09-01
Full Text Available Subsea pipeline route design is a crucial task for the offshore oil and gas industry, and the route selected can significantly affect the success or failure of an offshore project. Thus, it is essential to design pipeline routes to be eco-friendly, economical and safe. Obstacle avoidance is one of the main problems that affect pipeline route selection. In this study, we propose a technique for designing an automatic obstacle avoidance. The Laplacian smoothing algorithm was used to make automatically generated pipeline routes fairer. The algorithms were fast and the method was shown to be effective and easy to use in a simple set of case studies.
陶莉莉; 孔祥东; 钟伟民; 钱锋
2012-01-01
In recent years, immune genetic algorithm (IGA) is gaining popularity for finding the optimal solution for non-linear optimization problems in many engineering applications. However, IGA with deterministic mutation factor suffers from the problem of premature convergence. In this study, a modified self-adaptive immune genetic algorithm (MSIGA) with two memory bases, in which immune concepts are applied to determine the mutation parameters, is proposed to improve the searching ability of the algorithm and maintain population diversity. Performance comparisons with other well-known population-based iterative algorithms show that the proposed method converges quickly to the global optimum and overcomes premature problem. This algorithm is applied to optimize a feed forward neural network to measure the content of products in the combustion side reaction of p-xylene oxidation, and satisfactory results are obtained.
Takahashi, Takahiro; Nakai, Hiroyuki; Kinpara, Hiroki; Ema, Yoshinori
2011-09-01
The identification of appropriate reaction models is very helpful for developing chemical vapor deposition (CVD) processes. In this study, we have developed an automatic system to model reaction mechanisms in the CVD processes by analyzing the experimental results, which are cross-sectional shapes of the deposited films on substrates with micrometer- or nanometer-sized trenches. We designed the inference engine to model the reaction mechanism in the system by the use of real-coded genetic algorithms (RCGAs). We studied the dependence of the system performance on two methods using simple genetic algorithms (SGAs) and the RCGAs; the one involves the conventional GA operators and the other involves the blend crossover operator (BLX-alpha). Although we demonstrated that the systems using both the methods could successfully model the reaction mechanisms, the RCGAs showed the better performance with respect to the accuracy and the calculation cost for identifying the models.
Dynamic differential evolution algorithm for swarm robots search path planning%复杂环境移动群机器人最优路径规划方法
徐雪松; 杨胜杰; 陈荣元
2016-01-01
研究了一类复杂环境下移动群机器人的建模与控制策略.采用栅格法对机器人工作环境进行建模,基于个体的有限感知能力和局部的交互机制设计了响应概率函数,解决群机器人任务分配与信息共享难题.通过施加螺旋控制于早期信号搜索,并将该搜索信息作为启发因子改进动态差分进化算法,对群机器人进行路径优化.仿真结果表明,当响应概率函数中距离变量调节因子β=0.006时,任务分配控制算法达到最好效果.同时,移动群机器人路径规划的平均路径长度ˉS,平均移动时间Tˉ以及平均收敛代数Mˉ,相比扩展PSO算法分别提高了16%、57%及230%.最后,将该算法应用于AS-UⅢ型轮式移动群机器人物理实验,并设计了协同控制平台,具有较好的工程应用价值.%A novel optimization algorithm based on differential evolution is proposed in this paper .The modeling and the control strategies of swarming robots for search planning in a complex environment are discussed .Grid method is used for robot working environment modeling .The response probability function is designed based on in-dividual's limited cognitive ability and local interaction mechanism , which can solve the problem of the swarm robot task allocation and information sharing.Robots moving spirally to search cues can offer evidence for using dynamic differential evolution algorithm to search target optimally.The simulation results show that when the response proba-bility function distance variable regulating factorβ=0.006, task allocation control algorithm can achieve the best effect .At the same time , the mobile robot path planning group of average path length , average moving time and av-erage convergence algebraic extension compared to PSO algorithm is enhanced by 16%, 57% and 230% respec-tively.This algorithm is introduced to AS-UⅢ wheel mobile robots real experiments and illustrated its engineering application value.
Poulsen, Jens Aage; Nyman, Gunnar; Rossky, Peter J
2006-11-01
The Feynman-Kleinert Linearized Path Integral (FK-LPI) representation of quantum correlation functions is extended in applications and algorithms. Diffusion including quantum effects for a flexible simple point charge model of liquid water is explored, including new tests of internal consistency. An ab initio quantum correction factor (QCF) is also obtained to correct the far-infrared spectrum of water. After correction, a spectrum based on a classical simulation is in good agreement with the experiment. The FK-LPI QCF is shown to be superior to the so-called harmonic QCF. New computational algorithms are introduced so that the quantum Boltzmann Wigner phase-space density, the central object in the implementation, can be obtained for arbitrary potentials. One scheme requires only that the standard classical force routine be replaced when turning from one molecular problem to another. The new algorithms are applied to the calculation of the Van Hove spectrum of liquid He(4) at 27 K. The spectrum moments are in very good agreement with the experiment. These observations indicate that the FK-LPI approach can be broadly effective for molecular problems involving the dynamics of light nuclei.
WANG Yunfeng; BIAN Jinian; HONG Xianlong; ZHOU Qiang; WU Qiang
2007-01-01
As the feature size of integrated circuits is reduced to the deep sub-micron level or the nanometer level, the interconnect delay is becoming more and more important in determining the total delay of a circuit. Re-synthesis after floorptan is expected to be very helpful for reducing the interconnect delay of a circuit. In this paper,a force-balance-based re-synthesis algorithm for interconnect delay o ptimization after floorplan is proposed. The algorithm optimizes the inter connect delay by changing the operation scheduling and the functional unit allocation andbinding. With this method the number and positions of all functional units are not changed, but some operations are allocated or bound to different units. Preliminary experimental results show that the interconnect wire delays are reduced efficiently without destroying the floorplan performance.
王怿; 祝小平; 周洲
2012-01-01
提出了一种新的基于Clothoid曲线的无人机复合路径规划算法.该算法考虑了无人机在起点和目标点的方向以及无人机转弯半径的约束,能够在任意起止点位置和方向下得到更短的曲率连续的便于无人机飞行控制跟踪实现的Clothoid复合路径.与现有的基于微分几何的迭代算法相比,该算法迭代简单在给定范围内选择迭代初值,可以得到惟一解.%A new algorithm producing Clothoid composite path is proposed in this paper. A shorter path with continuous curvature which is easy to follow for UAVs can be obtained by this algorithm in any start and finish poses, with the constraints of the start and finish poses and the turning radius of UAV taken into consideration. Sections 1 through 3 of the full paper explain and evaluate the path planning algorithm mentioned in the title, which we believe is better than the existing differential geometry algorithm. The core of sections 1 through 3 consists of; ( 1) section 1 briefs Clothoid curve; ( 2 ) section 2 explains our path planning algorithm; for convenience, it is divided into two subsections (2. 1 and 2. 2); Figs. 1 and 2 are worth noticing; (3) section 3 evaluates our path planning algorithm ; simulation results are presented in Figs. 3 through 5; the simulation results and their analysis show preliminarily that, compared with the differential geometry algorithm, the proposed iteration algorithm is indeed simpler and the nonlinear equation has a unique solution by choosing the starting value in the starting interval.
Adaptive Path Planning of the UAV Based on Genetic Algorithm%基于遗传算法的UAV自适应航迹规划
王琪; 马璐; 邓会亨
2013-01-01
根据遗传算法与动态的稀疏A*搜索(Dynamic Sparse A* Search, DASA)算法各自的特点,提出一种组合优化算法来实现在不确定战场环境中自适应航迹规划。在无人机(UAV, Unmanned Aerial Vehicles)飞行前,采用全局搜索能力强的遗传算法进行全局搜索,对从起始点到目标点的飞行航线进行规划,生成全局最优或次优的可行参考飞行航线；在无人机任务执行阶段,以参考飞行航线为基准,采用 DASA 算法进行在线实时航迹再规划。仿真结果表明,与遗传算法相比,该组合算法不但能生成近似最优解,而且能够满足在线实时应用的要求。%According to the characteristics of genetic algorithm and the Dynamic Sparse A*Search (Dynamic Sparse A*Search, DASA) algorithm, this paper puts forward a combinational optimal algorithm fulfilling adaptive path planning in flying environment with unknown threat. Before flight, the ground station adopt genetic algorithm which possess the powerful ability of global search to realize Universal Search, we proceed programme from the starting point to the target point to generate the global optimal or suboptimal feasible reference airline. When the UAV is executing fly missions, DASA algorithm is used for on line route re planning based on the reference flight line as the benchmark. The simulation results show that compared with the genetic algorithm, the combined algorithm cannot only produce an approximate optimal solution, but also meet the requirements of real-time online application.
Riihimaki, Laura D.; Comstock, Jennifer M.; Anderson, K. K.; Holmes, Aimee E.; Luke, Edward
2016-06-10
Knowledge of cloud phase (liquid, ice, mixed, etc) is necessary to describe the radiative impact of clouds and their lifetimes, but is a property that is difficult to simulate correctly in climate models. One step towards improving those simulations is to make observations of cloud phase with sufficient accuracy to help constrain model representations of cloud processes. A variety of methods, based primarily on decision tree approaches, have been used to identify cloud phase from active remote sensors. These algorithms do not include uncertainty estimates, which contributes an unknown amount of uncertainty to the retrieval of cloud microphysical properties and to model parameterization development and evaluation. In this study, we outline a methodology using a Bayesian classifier to estimate the probabilities of cloud phase class from Atmospheric Radiation Measurement (ARM) vertically pointing active remote sensors. We also test the value of including higher moments of the cloud radar Doppler spectrum than are traditionally used operationally. Using training data of known phase from the Mixed-Phase Arctic Cloud Experiment (M-PACE) field campaign, we demonstrate a proof of concept for how the algorithm can be trained and run as an operational cloud phase retrieval. Over 95% of data is identified correctly for pure ice and liquid cases used in this study. Mixed-phase and snow cases are more problematic to identify correctly. When lidar data are not available, including additional information from the Doppler spectrum provides substantial improvement to the algorithm.
基于典型事例推理的路径规划方法研究%A Path Planning Algorithm Based on Typical Case Reasoning
翁敏; 魏秀琴; 瞿嵘; 蔡忠亮
2009-01-01
Case-based reasoning is an AI technique in which the previous solutions are stored for future use. People are used to guiding themselves according to those routes that are stored in their memories and have been used by them before. It is just based on people's preference to familiar routes, which are gained through the study of the cognitive activities. We propose to apply the intelligent method based on the case reasoning to path planning. It is impossible for a case base to store all the solutions to all the shortest paths; therefore, part of them should be stored. However, which routes should be stored and which should not be? How do we adapt the cases that have already been stored and how do we acquire the shortest route based on them? All these issues need to be explained by integrating knowledge of the network on account of case-based reasoning techniques. This paper suggests the case-based reasoning in another point. This means finding some irreplaceable links on the basis of the complete analysis of the problems space, which are called the must_be_passed link between the source and destination. Merely compute the shortest path case from those best exit/entry nodes of the grids to the irreplaceable links, and then add them into the case base storing for future use. This method is based on case-based reasoning technique and com-pletely considers the properties of the problem space. In addition to the use of knowledge of the natural grid in the route network, this method is more efficient than existing algorithms on computing efficiency.
Exclusive CHIPS-TPT algorithms for simulation of neutron-nuclear reactions
Kosov, Mikhail; Savin, Dmitriy
2016-09-01
The CHIPS-TPT physics library for simulation of neutron-nuclear reactions on the new exclusive level is being developed in CFAR VNIIA. The exclusive modeling conserves energy, momentum and quantum numbers in each neutron-nuclear interaction. The CHIPS-TPT algorithms are based on the exclusive CHIPS library, which is compatible with Geant4. Special CHIPS-TPT physics lists in the Geant4 format are provided. The calculation time for an exclusive CHIPS-TPT simulation is comparable to the time of the corresponding inclusive Geant4-HP simulation and much faster for mono-isotopic simulations. In addition to the reduction of the deposited energy fluctuations, which is a consequence of the energy conservation, the CHIPS-TPT libraries provide a possibility of simulation of the secondary particles correlation, e.g. secondary gammas or n-γ correlations, and of the Doppler broadening of the γ-lines in the simulated spectra, which can be measured by germanium detectors.
Shortest Dijkstra Path Routing Algorithm in WOBAN%WOBAN中最短路径Dijkstra路由算法
马应平; 柯赓; 曹文婷
2012-01-01
光纤无线宽带混合接入网（WOBAN）是一种新型的具有前景的混合接入网，通过改进其无线端网络的路由算法能够有效克服WOBAN的瓶颈限制。最小跳路由算法（MHRA）和最小时延路由算法（MDRA）是将Diikstra算法应用在WOBAN前端无线Mesh网（WMN）中的新型路由算法，低负载情况下两算法性能相近，高负载情况下MDRA具有更好的网络性能。通过仿真比较，高负载情况下MDRA的时延和TDR性能明显优于MHRA。%The hybrid Wireless-Optical Broadband Access Network (WOBAN) is a promis- ing architecture for future access networks. The characteristics of the Minimum Delay Routing Algorithm (MDRA) and Dijkstra Minimum Hop Routing Algorithm (MHRA) in the wireless front-end of a WOBAN were investigated. Our performance studies show that MDRA has the similar performance with the MHRA in the situation of low load, while it acts shorter delay and higher TDR than MHRA in the situation of high load.
基于几何相交测试的机器人路径规划算法%Geometry intersection testing based robot path planning algorithm
周之平; 黎明; 华路
2011-01-01
针对机器人路径规划问题,提出一种基于几何相交测试的路径规划方法.该方法首先搜索位于当前路径点到目标点连线上的首障碍栅格;然后结合贪婪法、回溯法和邻域搜索策略从障碍栅格邻域搜索下一个路径栅格;接着从新的路径点出发迭代搜索后续的路径点,从而确定从起点到目标点的路径;最后对得到的最好路径进行路径点合并以提高路线的连贯性.实验结果表明,新方法规划的路径性能优于其他同类算法,路径呈现出更好的连续性,规划时间能满足实际应用的要求.%For the problem of robot path planning,a geometry intersection testing based path planning algorithm is presented.Firstly,the first obstacle grid is searched in the configuration space which lies on the oriented segment from start to target.By combining the greedy method and backward strategy,the grid where next way point lies is determined from the neighbors of the first obstacle grid by local searching.Then subsequent way points are obtained iteratively scratching from the last obtained way point in order to get some routes from start to target as possible.Finally,the best route is refined by incorporating subroutes to maintain the consistency of trajectory.The experimental results show that,the presented method can plan a shorter and more reasonable path than other algorithms,which represents higher consistency of trajectory,and the computing time can meet the requirement of practical application.
Channeling the SmI₂ reactions to the radical path: radicals resisting reduction by SmI₂.
Yella, Ramesh; Hoz, Shmaryahu
2014-08-01
Studies on the reaction of 4-(2,2-diphenylvinyl)pyridine with SmI2 revealed that the intermediate radical strongly resists further reduction to the corresponding anion. The resistance of the radical to accepting another electron is traced to its stabilization by the nitrogen lone pair. The literature suggests that oxygen may also play a role similar to that of nitrogen in directing the course of the reaction toward radical rather than to anionic chemistry.
Parallel parking algorithm based on autonomous path planning%一种基于路径规划的自动平行泊车算法
林蓁蓁; 李庆; 梁艳菊; 陈大鹏
2012-01-01
针对城市中停车位狭小、现有自动泊车方法缺乏连贯性的问题,提出一种自动平行泊车算法.对现有的五阶多项式路径规划方法加以改进,并有针对性地设计罚函数,采用遗传算法计算最佳泊车路径和最小泊车空间,实现自动平行泊车.仿真结果表明,该算法能快速有效地完成泊车,车辆损伤小,对空间的要求最低.%In order to solve problems of narrow parking space in cities and lack of continuity of vehicle' s motion in other parking approaches, this paper proposed an autonomous parking algorithm. It improved the approach of fifth-order polynomial, and designed penalty function and genetic algorithm to calculate the best path and the tightest parking space, finally realizing automatic parallel parking. The simulation result indicates that this method can park a car swiftly and efficiently with slight impact on vehicles and the least space requirement.
Campodonico, Miguel A.; Andrews, Barbara A.; Asenjo, Juan A.
2014-01-01
to computationally design metabolic pathways for chemical production. Although algorithms able to provide specific metabolic interventions and heterologous production pathways are available, a systematic analysis for all possible production routes to commodity chemicals in Escherichia call is lacking. Furthermore......The production of 75% of the current drug molecules and 35% of all chemicals could be achieved through bioprocessing (Arundel and Sawava, 2009). To accelerate the transition from a petroleum based chemical industry to a sustainable bio-based industry, systems metabolic engineering has emerged...... native compounds from different feedstocks. In this study, we extended this analysis for non-native compounds by using an integrated approach through heterologous pathway integration and growth coupled metabolite production design. In addition to integration with genome-scale model integration, the GEM...
Minyaev, Ruslan M., E-mail: minyaev@ipoc.sfedu.ru [Institute of Physical and Organic Chemistry, Southern Federal University, 194/2 Stachka Ave., Rostov-on-Don 344090 (Russian Federation); Quapp, Wolfgang; Schmidt, Benjamin [Leipzig University, Mathematical Institute, Augustusplatz, D-04109 Leipzig (Germany); Getmanskii, Ilya V.; Koval, Vitaliy V. [Institute of Physical and Organic Chemistry, Southern Federal University, 194/2 Stachka Ave., Rostov-on-Don 344090 (Russian Federation)
2013-11-08
Highlights: • High level quantum chemical calculations are performed for two S{sub N}2 reactions. • The calculated gradient reaction pathways for reactions have an unusual behavior. • An unusual saddle point of index two lies on the gradient reaction path. • VRI points have been detected by using Newton trajectories for the reaction path. • An infinite flow of gradient lines emanates at three equivalent product minima. - Abstract: Quantum chemical (CCSD(full)/6-311++G(3df,3pd), CCSD(T)(full)/6-311++G(3df,3pd)) and density function theory (B3LYP/6-311++G(3df,3pd)) calculations were performed for the S{sub N}2 nucleophile substitution reactions CH{sub 4} + H{sup −} → CH{sub 4} + H{sup −} and CH{sub 4} + F{sup −} → CH{sub 3}F + H{sup −}. The calculated gradient reaction pathways for both reactions have an unusual behavior. An unusual stationary point of index 2 lies on the gradient reaction path. Using Newton trajectories for the reaction path, we can detect VRI point at which the reaction path branches.
Neutron Transfer Reactions on Neutron-Rich N=50 and N=82 Nuclei Near the r-Process Path
Cizewski, J. A. [Rutgers University; Jones, K. L. [University of Tennessee, Knoxville (UTK); Kozub, R. L. [Tennessee Technological University; Pain, S. D. [Rutgers University; Thomas, J. S. [Rutgers University; Arbanas, Goran [ORNL; Adekola, Aderemi S [ORNL; Bardayan, Daniel W [ORNL; Blackmon, Jeff C [ORNL; Chae, K. Y. [University of Tennessee, Knoxville (UTK); Chipps, K. [Colorado School of Mines, Golden; Dean, David Jarvis [ORNL; Erikson, Luke [Colorado School of Mines, Golden; Gaddis, A. L. [Furman University; Harlin, Christopher W [ORNL; Hatarik, Robert [Rutgers University; Howard, Joshua A [ORNL; Johnson, Micah [ORNL; Kapler, R. [University of Tennessee, Knoxville (UTK); Krolas, W. [University of Warsaw; Liang, J Felix [ORNL; Livesay, Jake [ORNL; Ma, Zhanwen [ORNL; Matei, Catalin [Oak Ridge Associated Universities (ORAU); Moazen, Brian [University of Tennessee, Knoxville (UTK); Nesaraja, Caroline D [ORNL; O' Malley, Patrick [Rutgers University; Paulauskas, Stanley V [ORNL; Shapira, Dan [ORNL; ShrinerJr., J. F. [Tennessee Technological University; Sissom, D. J. [Tennessee Technological University; Smith, Michael Scott [ORNL; Swan, T. P. [University of Surrey, UK; Wilson, Gemma L [ORNL
2009-01-01
Neutron transfer (d,p) reaction studies on the N = 50 isotones, 82Ge and 84Se, and A{approx}130 nuclei, 130,132Sn and 134Te, have been measured. Direct neutron capture cross sections for 82Ge and 84Se (n,?) have been calculated and are combined with Hauser-Feshbach expectations to estimate total (n,?) cross sections. The A{approx}130 studies used an early implementation of the ORRUBA array of position-sensitive silicon strip detectors for reaction proton measurements. Preliminary excitation energy and angular distribution results from the A{approx}130 measurements are reported.
王建新; 王新辉; 彭革刚
2002-01-01
An important issue for providing better guarantees of Quality of Service (QoS) to applications is QoS rout-ing. The task of QoS routing is to determine a feasible path that satisfies a set of constraints while maintaining high u-tilization of network resources. For the purpose of achieving the latter objective additional optimality requirementsneed to be imposed. In general, multi-constrained path selection problem is NP-hard so it cannot be exactly solved inpolynomial time. Accordingly heuristics and approximation algorithms with polynomial or pseudo-polynomial timecomplexity are often used to deal with this problem. However, many of these algorithms suffer from either excessivecomputational complexity that cannot be used for online network operation or low performance. Moreover, they gen-erally deal with special cases of the problem (e. g. , two constraints without optimization, one constraint with opti-mization, etc. ). In this paper, the authors propose a new efficient algorithm (EAMCOP) for the problem. Makinguse of efficient pruning policy, the algorithm reduces greatly the size of search space and improves the computationalperformance. Although the proposed algorithm has exponential time complexity in the worst case, it can get verygood performance in real networks. The reason is that when the scale of network increases, EAMCOP controls effi-ciently the size of search space by constraint conditions and prior queue that improves computational efficiency. Theresults of simulation show that the algorithm has good performance and can solve effectively multi-constrained opti-mal path (MCOP) problem.
Uitdehaag, Joost C.M.; Veen, Bart A. van der; Dijkhuizen, Lubbert; Elber, Ron; Dijkstra, Bauke W.
2001-01-01
Cyclodextrin glycosyltransferase (CGTase) is an enzyme belonging to the ol-amylase family that forms cyclodextrins (circularly linked oligosaccharides) from starch. X-ray work has indicated that this cyclization reaction of CGTase involves a 23-Angstrom movement of the nonreducing end of a linear ma
Nordin, Noraimi Azlin Mohd; Omar, Mohd; Sharif, S. Sarifah Radiah
2017-04-01
Companies are looking forward to improve their productivity within their warehouse operations and distribution centres. In a typical warehouse operation, order picking contributes more than half percentage of the operating costs. Order picking is a benchmark in measuring the performance and productivity improvement of any warehouse management. Solving order picking problem is crucial in reducing response time and waiting time of a customer in receiving his demands. To reduce the response time, proper routing for picking orders is vital. Moreover, in production line, it is vital to always make sure the supplies arrive on time. Hence, a sample routing network will be applied on EP Manufacturing Berhad (EPMB) as a case study. The Dijkstra's algorithm and Dynamic Programming method are applied to find the shortest distance for an order picker in order picking. The results show that the Dynamic programming method is a simple yet competent approach in finding the shortest distance to pick an order that is applicable in a warehouse within a short time period.
吴宪祥; 郭宝龙; 王娟
2009-01-01
针对移动机器人路径规划问题,提出了一种基于粒了群三次样条优化的路径规划方法.借助三次样条连接描述路径,这样将路径规划问题转化为三次样条曲线的参数优化问题.借助粒了群优化算法快速收敛和全局寻优特性实现最优路径规划.实验结果表明:所提算法町以快速有效地实现障碍环境下机器人的无碰撞路径规划,规划路径平滑,利于机器人的运动控制.%A novel algorithm based on particle swarm optimization (PSO) of cubic splines is proposed for mobile robot path planning. The path is described by string of cubic splines, thus the path planning is equivalent to parameter optimization of particular cubic splines. PSO is introduced to get the optimal path for its fast convergence and global search character. Ex-perimental results show that a collision-avoidance path can be found fleetly and effectively among obstacles by the proposed algorithm. The planned path is smooth which is useful for robot motion control.
一种图的st编号路径长度算法%Algorithm of St-numbering Path Length of Graph
刘阳; 晏立
2013-01-01
通过对无向图的顶点标注st-编号,可以使它转换为一个有向图,根据有向图的方向可计算出从源点到汇点的路径长度.用DFS算法可计算出st-编号,但一个图有多种不同的st-编号方法,不能确定图的最长路径或者最短路径.使用移除法,连续移除根据时间戳选择出来的顶点,计算出图的st-编号,能够确定图的最长路径或者最短路径.st-编号路径长度在计算网络动态路由、计算最少着色数、减少框图高度等问题上有广泛的应用.%An undirected graph with vertices labeled St-numbering can be turned into a directed graph.The DFS algorithm can compute a st-numbering of the graph,but cannot confirm its longest or shortest path,cause a graph may have several different st-numberings.While the Removing method,which successively remove vertices selected by the timestamp,can compute the st-numbering of the graph and confirm the longest or shortest path of it.The length of st-numberings graph has a wide application in the computation of network dynamic routing and the minimum number of Graph Coloring,reduction of height of the block diagram and so on.
Shortest Paths and Vehicle Routing
Petersen, Bjørn
This thesis presents how to parallelize a shortest path labeling algorithm. It is shown how to handle Chvátal-Gomory rank-1 cuts in a column generation context. A Branch-and-Cut algorithm is given for the Elementary Shortest Paths Problem with Capacity Constraint. A reformulation of the Vehicle R...... Routing Problem based on partial paths is presented. Finally, a practical application of finding shortest paths in the telecommunication industry is shown.......This thesis presents how to parallelize a shortest path labeling algorithm. It is shown how to handle Chvátal-Gomory rank-1 cuts in a column generation context. A Branch-and-Cut algorithm is given for the Elementary Shortest Paths Problem with Capacity Constraint. A reformulation of the Vehicle...
Multi-UAVs cooperative path planning based on A* fixed length search algorithm%基于A*定长搜索算法的多无人机协同航迹规划
肖自兵; 袁冬莉; 屈耀红
2012-01-01
An improved A * algorithm for fixed length path searching was proposed based on the path planning problems of multiple unmanned aerial vehicles ( UAVs) operating simultaneously. A path with fixed length was obtained by choosing nodes with costs closest to given value as best nodes in the algorithm. Then, the path was smoothed by limiting the range of the best nodes choosing from in the algorithm. Simulation results show that length error of the fixed length path obtained from the algorithm can be controlled within 1. 4% , and length error of collaborative paths is less than 0. 8%. It basically meets the requirements of multi-UAVs arriving at the same time.%基于多无人机同时作业情况下的航迹规划问题,提出了一种A*定长航迹搜索算法.该算法通过选择代价值最接近给定值的节点作为最佳节点,得到定长规划航迹,接着进一步通过限定最佳节点的选择范围,改善了航迹的可飞性.仿真结果表明,利用该算法规划的定长航迹长度误差可以控制在1.4％以内,协同航迹长度误差可以控制在0.8％以内,能够满足多无人机同时到达的一般要求.
Shortest-path routing algorithm based on selected RSL in WlrelessHART%基于RSL筛选的WirelessHART最短路径路由算法
党魁; 沈继忠; 董利达
2012-01-01
无线HART网络协议中提出的Graph路由是同类无线网络中健壮性最好的路由方式之一.针对目前实现该路由方式的算法非常少且性能不佳的现状,提出一种基于BFS的Graph路由算法.该算法得到的路由具有跳间冗余的特点,能够最大限度地增加路由健壮性,并且路径最短；引入RSL作为链路质量衡量标准,剔除质量较差的链路,同时对每跳的邻居数设置上限,保证了路由的健壮性,同时避免了低质量的链路带来的通信资源浪费.此外,论证了协议所没有提及的广播路由存在的必要,并给出了实现算法.%The Graph routing proposed by WirelessHART is one of the routing protocols which with best robustness among all the wireless networks. Since there is little algorithm on Graph routing at present and the routing performance is poor, a shortest-path Graph routing algorithm based on BFS( Breadth-First Search) is presented. The routing algorithm has a character of neighbor redundancies, which can maximize to increase the routing robustness. With the introduction of RSL(Receive Signal Level) as a link quality measurement, removing the links with poor quality, setting an upper limit to the number of neighbors in each hop, both methods are aimed to increase the routing robustness and minimize the waste communication resources. In addition, the necessary of broadcast routing which WirelessHART has not mentioned is demonstrated and the reality algorithm is also proposed.
Mastromatteo, Michael; Jackson, Bret
2013-11-21
Electronic structure methods based on density functional theory are used to construct a reaction path Hamiltonian for CH4 dissociation on the Ni(100) and Ni(111) surfaces. Both quantum and quasi-classical trajectory approaches are used to compute dissociative sticking probabilities, including all molecular degrees of freedom and the effects of lattice motion. Both approaches show a large enhancement in sticking when the incident molecule is vibrationally excited, and both can reproduce the mode specificity observed in experiments. However, the quasi-classical calculations significantly overestimate the ground state dissociative sticking at all energies, and the magnitude of the enhancement in sticking with vibrational excitation is much smaller than that computed using the quantum approach or observed in the experiments. The origin of this behavior is an unphysical flow of zero point energy from the nine normal vibrational modes into the reaction coordinate, giving large values for reaction at energies below the activation energy. Perturbative assumptions made in the quantum studies are shown to be accurate at all energies studied.
Finding conserved and non-conserved reactions using a metabolic pathway alignment algorithm.
Clemente, José C; Satou, Kenji; Valiente, Gabriel
2006-01-01
Using a metabolic pathway alignment method we developed, we studied highly conserved reactions in different groups of organisms and found out that biological functions vital for each of the groups are effectively expressed in the set of conserved reactions. We also studied the metabolic alignment of different strains of three bacteria and found out several non-conserved reactions. We suggest that these reactions could be either misannotations or reactions with a relevant but yet to be specified biological role, and should therefore be further investigated.
Ji, Yanqing; Ying, Hao; Dews, Peter; Mansour, Ayman; Tran, John; Miller, Richard E; Massanari, R Michael
2011-05-01
Early detection of unknown adverse drug reactions (ADRs) in postmarketing surveillance saves lives and prevents harmful consequences. We propose a novel data mining approach to signaling potential ADRs from electronic health databases. More specifically, we introduce potential causal association rules (PCARs) to represent the potential causal relationship between a drug and ICD-9 (CDC. (2010). International Classification of Diseases, Ninth Revision (ICD-9). [Online]. Available: http://www.cdc.gov/nchs/icd/icd9.html) coded signs or symptoms representing potential ADRs. Due to the infrequent nature of ADRs, the existing frequency-based data mining methods cannot effectively discover PCARs. We introduce a new interestingness measure, potential causal leverage, to quantify the degree of association of a PCAR. This measure is based on the computational, experience-based fuzzy recognition-primed decision (RPD) model that we developed previously (Y. Ji, R. M. Massanari, J. Ager, J. Yen, R. E. Miller, and H. Ying, "A fuzzy logic-based computational recognition-primed decision model," Inf. Sci., vol. 177, pp. 4338-4353, 2007) on the basis of the well-known, psychology-originated qualitative RPD model (G. A. Klein, "A recognition-primed decision making model of rapid decision making," in Decision Making in Action: Models and Methods, 1993, pp. 138-147). The potential causal leverage assesses the strength of the association of a drug-symptom pair given a collection of patient cases. To test our data mining approach, we retrieved electronic medical data for 16,206 patients treated by one or more than eight drugs of our interest at the Veterans Affairs Medical Center in Detroit between 2007 and 2009. We selected enalapril as the target drug for this ADR signal generation study. We used our algorithm to preliminarily evaluate the associations between enalapril and all the ICD-9 codes associated with it. The experimental results indicate that our approach has a potential to
Gürber, Susanne; Baumeler, Luzia; Grob, Alexander; Surbek, Daniel; Stadlmayr, Werner
2017-08-01
Postpartum depressive symptoms (PDS) and acute stress reactions (ASR) after childbirth are frequently documented in mothers, but research is scarce in fathers. In a longitudinal path analysis, the interplay of depressive symptoms in pregnancy and the subjective childbirth experience of mothers and fathers are examined with regard to the development of PDS and ASR postpartum. One hundred eighty nine expectant couples were recruited between August 2006 and September 2009. They completed the Edinburgh Postnatal Depression Scale (EPDS) in the last trimester of pregnancy. In the first week postpartum, they answered the Salmon's Item List (subjective birth experience), and four weeks after birth the EPDS and the Impact of Event Scale - revised (IES-r). The data were evaluated in a longitudinal path analysis. Compared with fathers, mothers reported more depressive symptoms (pregnancy: pexperience' (p0.10), but moderately correlated four weeks after birth (r=0.387, pexperience were independently predictive of PDS and ASR after childbirth in mothers and fathers controlling for age, mode of delivery, parity, epidural anaesthesia, infant gender and birth weight. Antenatal depressive symptoms were related to subjective childbirth experience only in fathers. Parental prenatal depressive symptoms and subjective birth experience are important predictors of postnatal psychological adjustment in mothers and fathers. Copyright © 2017. Published by Elsevier B.V.
Moyocoyani Molina-Espíritu
2013-09-01
Full Text Available An information-theoretical complexity analysis of the SN2 exchange reaction for CH3Cl + F− is performed in both position and momentum spaces by means of the following composite functionals of the one-particle density: D-L and I-J planes and Fisher-Shannon’s (FS and López-Ruiz-Mancini-Calbet (LMC shape complexities. It was found that all the chemical concepts traditionally assigned to elementary reactions such as the breaking/forming regions (B-B/F, the charge transfer/reorganization and the charge repulsion can be unraveled from the phenomenological analysis performed in this study through aspects of localizability, uniformity and disorder associated with the information-theoretical functionals. In contrast, no energy-based functionals can reveal the above mentioned chemical concepts. In addition, it is found that the TS critical point for this reaction does not show any chemical meaning (other than the barrier height as compared with the concurrent processes revealed by the information-theoretical analysis. Instead, it is apparent from this study that a maximum delocalized state could be identified in the transition region which is associated to the charge transfer process as a new concurrent phenomenon associated with the charge transfer region (CT for the ion-complex is identified. Finally it is discussed why most of the chemical features of interest (e.g., CT, B-B/F are only revealed when some information-theoretic properties are taken into account, such as localizability, uniformity and disorder.
Application of multilevel reduction algorithm to PCB path optimization%多级规约算法在PCB钻孔路径优化中的应用
程森林; 曾伟
2012-01-01
The PCB(Printed Circuit Board) path optimization is a large-scale TSP(Traveling Salesman Problem) problem. An Enhanced Multilevel Reduction algorithm (EMR) is proposed to solve this problem. The proposed algorithm redesigns the reduction operator and brings a control parameter to improve its flexibility. Meanwhile, in view of the difficulties of saving the results produced by reduction operator, a new data structure like human family tree is presented. Experimental results, compared with the other method, demonstrate that EMR outperforms in practicability and generality with higher quality and efficiency of optimization.%以求解PCB(Printed Circuit Board)钻孔路径优化这一大规模复杂的TSP(Traveling Salesman Problem)问题为背景,研究了一种改进的多级规约算法(EMR).该算法依据工程应用中实用性、通用性的特点重新设计了多级规约算法(MR)的规约和细化算子并增加了控制参数以提高算法的灵活性；针对算法中会产生大量部分解集且难以储存这一问题,设计了一种类似人类族谱的数据结构.实验结果以及与循环LK算法和蚁群算法的对比分析表明,EMR算法兼顾了实用性和通用性,且有较高的优化质量和优化效率.
Azuri, Asaf; Engel, Hamutal; Doron, Dvir; Major, Dan Thomas
2011-05-10
A practical approach to treat nuclear quantum mechanical (QM) effects in simulations of condensed phases, such as enzymes, is via Feynman path integral (PI) formulations. Typically, the standard primitive approximation (PA) is employed in enzymatic PI simulations. Nonetheless, these PI simulations are computationally demanding due to the large number of discretizations, or beads, required to obtain converged results. The efficiency of PI simulations may be greatly improved if higher order factorizations of the density matrix operator are employed. Herein, we compare the results of model calculations obtained employing the standard PA, the improved operator of Takahashi and Imada (TI), and several gradient-based forward corrector algorithms due to Chin (CH). The quantum partition function is computed for the harmonic oscillator, Morse, symmetric, and asymmetric double well potentials. These potentials are simple models for nuclear quantum effects, such as zero-point energy and tunneling. It is shown that a unique set of CH parameters may be employed for a variety of systems. Additionally, the nuclear QM effects of a water molecule, treated with density functional theory, are computed. Finally, we derive a practical perturbation expression for efficient computation of isotope effects in chemical systems using the staging algorithm. This new isotope effect approach is tested in conjunction with the PA, TI, and CH methods to compute the equilibrium isotope effect in the Schiff base-oxyanion keto-enol tautomerism in the cofactor pyridoxal-5'-phosphate in the enzyme alanine racemase. The study of the different factorization methods reveals that the higher-order actions converge substantially faster than the PA approach, at a moderate computational cost.
Kuesters, Tim; Mueller, Thomas; Renner, Joerg
2016-04-01
Reliably predicting the evolution of mechanical and chemical properties of reservoir rocks is crucial for efficient exploitation of enhanced geothermal systems (EGS). For example, dissolution and precipitation of individual rock forming minerals often result in significant volume changes, affecting the hydraulic rock properties and chemical composition of fluid and solid phases. Reactive transport models are typically used to evaluate and predict the effect of the internal feedback of these processes. However, a quantitative evaluation of chemo-mechanical interaction in polycrystalline environments is elusive due to poorly constrained kinetic data of complex mineral reactions. In addition, experimentally derived reaction rates are generally faster than reaction rates determined from natural systems, likely a consequence of the experimental design: a) determining the rate of a single process only, e.g. the dissolution of a mineral, and b) using powdered sample materials and thus providing an unrealistically high reaction surface and at the same time eliminating the restrictions on element transport faced in-situ for fairly dense rocks. In reality, multiple reactions are coupled during the alteration of a polymineralic rocks in the presence of a fluid and the rate determining process of the overall reactions is often difficult to identify. We present results of bulk rock-water interaction experiments quantifying alteration reactions between pure water and a granodiorite sample. The rock sample was chosen for its homogenous texture, small and uniform grain size (˜0.5 mm in diameter), and absence of pre-existing alteration features. The primary minerals are plagioclase (plg - 58 vol.%), quartz (qtz - 21 vol.%), K-feldspar (Kfs - 17 vol.%), biotite (bio - 3 vol.%) and white mica (wm - 1 vol.%). Three sets of batch experiments were conducted at 200 ° C to evaluate the effect of reactive surface area and different fluid path ways using (I) powders of the bulk rock with
Shieh, Shin-Lin; Han, Yunghsiang S
2007-01-01
A common problem on sequential-type decoding is that at the signal-to-noise ratio (SNR) below the one corresponding to the cutoff rate, the average decoding complexity per information bit and the required stack size grow rapidly with the information length. In order to alleviate the problem in the maximum-likelihood sequential decoding algorithm (MLSDA), we propose to directly eliminate the top path whose end node is $\\Delta$-trellis-level prior to the farthest one among all nodes that have been expanded thus far by the sequential search. Following random coding argument, we analyze the early-elimination window $\\Delta$ that results in negligible performance degradation for the MLSDA. Our analytical results indicate that the required early elimination window for negligible performance degradation is just twice of the constraint length for rate one-half convolutional codes. For rate one-third convolutional codes, the required early-elimination window even reduces to the constraint length. The suggestive theore...
Nicole C Wright
Full Text Available Validation of claims-based algorithms to identify serious hypersensitivity reactions and osteonecrosis of the jaw has not been performed in large osteoporosis populations. The objective of this project is to estimate the positive predictive value of the claims-based algorithms in older women with osteoporosis enrolled in Medicare. Using the 2006-2008 Medicare 5% sample data, we identified potential hypersensitivity and osteonecrosis of the jaw cases based on ICD-9 diagnosis codes. Potential hypersensitivity cases had a 995.0, 995.2, or 995.3 diagnosis code on emergency department or inpatient claims. Potential osteonecrosis of the jaw cases had ≥1 inpatient or outpatient physician claim with a 522.7, 526.4, 526.5, or 733.45 diagnosis code or ≥2 claims of any type with a 526.9 diagnosis code. All retrieved records were redacted and reviewed by experts to determine case status: confirmed, not confirmed, or insufficient information. We calculated the positive predictive value as the number of confirmed cases divided by the total number of retrieved records with sufficient information. We requested 412 potential hypersensitivity and 304 potential osteonecrosis of the jaw records and received 174 (42% and 84 (28% records respectively. Of 84 potential osteonecrosis of the jaw cases, 6 were confirmed, resulting in a positive predictive value (95% CI of 7.1% (2.7, 14.9. Of 174 retrieved potential hypersensitivity records, 95 were confirmed. After exclusion of 25 records with insufficient information for case determination, the overall positive predictive value (95% CI for hypersensitivity reactions was 76.0% (67.5, 83.2. In a random sample of Medicare data, a claim-based algorithm to identify serious hypersensitivity reactions performed well. An algorithm for osteonecrosis of the jaw did not, partly due to the inclusion of diagnosis codes that are not specific for osteoporosis of the jaw.
Wright, Nicole C; Curtis, Jeffrey R; Arora, Tarun; Smith, Wilson K; Kilgore, Meredith L; Saag, Kenneth G; Safford, Monika M; Delzell, Elizabeth S
2015-01-01
Validation of claims-based algorithms to identify serious hypersensitivity reactions and osteonecrosis of the jaw has not been performed in large osteoporosis populations. The objective of this project is to estimate the positive predictive value of the claims-based algorithms in older women with osteoporosis enrolled in Medicare. Using the 2006-2008 Medicare 5% sample data, we identified potential hypersensitivity and osteonecrosis of the jaw cases based on ICD-9 diagnosis codes. Potential hypersensitivity cases had a 995.0, 995.2, or 995.3 diagnosis code on emergency department or inpatient claims. Potential osteonecrosis of the jaw cases had ≥1 inpatient or outpatient physician claim with a 522.7, 526.4, 526.5, or 733.45 diagnosis code or ≥2 claims of any type with a 526.9 diagnosis code. All retrieved records were redacted and reviewed by experts to determine case status: confirmed, not confirmed, or insufficient information. We calculated the positive predictive value as the number of confirmed cases divided by the total number of retrieved records with sufficient information. We requested 412 potential hypersensitivity and 304 potential osteonecrosis of the jaw records and received 174 (42%) and 84 (28%) records respectively. Of 84 potential osteonecrosis of the jaw cases, 6 were confirmed, resulting in a positive predictive value (95% CI) of 7.1% (2.7, 14.9). Of 174 retrieved potential hypersensitivity records, 95 were confirmed. After exclusion of 25 records with insufficient information for case determination, the overall positive predictive value (95% CI) for hypersensitivity reactions was 76.0% (67.5, 83.2). In a random sample of Medicare data, a claim-based algorithm to identify serious hypersensitivity reactions performed well. An algorithm for osteonecrosis of the jaw did not, partly due to the inclusion of diagnosis codes that are not specific for osteoporosis of the jaw.
Lodola, Alessio; Sirirak, Jitnapa; Fey, Natalie; Rivara, Silvia; Mor, Marco; Mulholland, Adrian J
2010-09-14
The effects of structural fluctuations, due to protein dynamics, on enzyme activity are at the heart of current debates on enzyme catalysis. There is evidence that fatty acid amide hydrolase (FAAH) is an enzyme for which reaction proceeds via a high-energy, reactive conformation, distinct from the predominant enzyme-substrate complex (Lodola et al. Biophys. J. 2007, 92, L20-22). Identifying the structural causes of differences in reactivity between conformations in such complex systems is not trivial. Here, we show that multivariate analysis of key structural parameters can identify structural determinants of barrier height by analysis of multiple reaction paths. We apply a well-tested quantum mechanics/molecular mechanics (QM/MM) method to the first step of the acylation reaction between FAAH and oleamide substrate for 36 different starting structures. Geometrical parameters (consisting of the key bond distances that change during the reaction) were collected and used for principal component analysis (PCA), partial least-squares (PLS) regression analysis, and multiple linear regression (MLR) analysis. PCA indicates that different "families" of enzyme-substrate conformations arise from QM/MM molecular dynamics simulation and that rarely sampled, catalytically significant conformational states can be identified. PLS and MLR analyses allowed the construction of linear regression models, correlating the calculated activation barriers with simple geometrical descriptors. These analyses reveal the presence of two fully independent geometrical effects, explaining 78% of the variation in the activation barrier, which are directly correlated with transition-state stabilization (playing a major role in catalysis) and substrate binding. These results highlight the power of statistical approaches of this type in identifying crucial structural features that contribute to enzyme reactivity.
Characterization of the Minimum Energy Paths for the Ring Closure Reactions of C4H3 with Acetylene
Walch, Stephen P.
1995-01-01
The ring closure reaction of C4H3 with acetylene to give phenyl radical is one proposed mechanism for the formation of the first aromatic ring in hydrocarbon combustion. There are two low-lying isomers of C4H3; 1-dehydro-buta-l-ene-3-yne (n-C4H3) and 2-dehydro-buta-l-ene-3-yne (iso-C4H3). It has been proposed that only n-C4H3 reacts with acetylene to give phenyl radical, and since iso-C4H3 is more stable than n-C4H3, formation of phenyl radical by this mechanism is unlikely. We report restricted Hartree-Fock (RHF) plus singles and doubles configuration interaction calculations with a Davidson's correction (RHF+1+2+Q) using the Dunning correlation consistent polarized valence double zeta basis set (cc-pVDZ) for stationary point structures along the reaction pathway for the reactions of n-C4H3 and iso-C4H3 with acetylene. n-C4H3 plus acetylene (9.4) has a small entrance channel barrier (17.7) (all energetics in parentheses are in kcal/mol with respect to iso-C4H3 plus acetylene) and the subsequent closure steps leading to phenyl radical (-91.9) are downhill with respect to the entrance channel barrier. Iso-C4H3 Plus acetylene also has an entrance channel barrier (14.9) and there is a downhill pathway to 1-dehydro-fulvene (-55.0). 1-dehydro-fulvene can rearrange to 6-dehydro-fulvene (-60.3) by a 1,3-hydrogen shift over a barrier (4.0), which is still below the entrance channel barrier, from which rearrangement to phenyl radical can occur by a downhill pathway. Thus, both n-C4H3 and iso-C4H3 can react with acetylene to give phenyl radical with small barriers.
Mark Setterfield
2015-01-01
Path dependency is defined, and three different specific concepts of path dependency – cumulative causation, lock in, and hysteresis – are analyzed. The relationships between path dependency and equilibrium, and path dependency and fundamental uncertainty are also discussed. Finally, a typology of dynamical systems is developed to clarify these relationships.
王保伟; 杨恩翠; 许根慧; 郝金库
2007-01-01
The direct synthesis of C2 hydrocarbons (ethylene, acetylene and ethane) from methane is one of the most important task in C1 chemistry. Higher conversion of methane and selectivity to C2 hydrocarbons can be realized through plasma reaction. In order to explore the reaction process and mechanism, the possible reaction paths (1)-(4) were proposed on coupling reaction of methane through plasma and studied theoretically using semi-PM3 method [PM3 is parametcrization method of modified neglect of diatomic overlap (MNDO)] including determining the transition state, calculating the activation energy and thermodynamic state functions and analyzing the bond order and intrinsic reaction coordinate. The reaction heat results indicate that the reactions (2) and (4) are exothermic,while reactions of (1) and (3) are endothermic. The activation energy results show that activation energy for reactions (1) and (2) was much lower than that of reaction paths (3) and (4). Therefore, paths (1) and (2) is the favorable reaction path energetically. More interestingly by comparing the intrinsic reaction coordinated (IRC) of the reaction paths (1) and (2), it is found that the variations of bond lengths in reaction path (1) has a crucial effect on the potential energy, while in reaction path (2), the adjustment of the system geometry also contributes to the whole potential energy of the system.
Francisco Casesnoves
2014-08-01
delivery model. Simulations results gave acceptable trigonometrical approximations/data that can be used for LINAC applications/planning-system software. The integral formulas presented are practical for dose delivery calculations/3D-approximations when using WF/other similar types of beam modification devices. Limit angle formulation and conformal wedge concept was also presented...................................................Cite this article as: Casesnoves F. Geometrical determinations of IMRT photon pencil-beam path in radiotherapy wedges and limit divergence angle with the Anisotropic Analytic Algorithm (AAA. Int J Cancer Ther Oncol 2014; 2(3:02031. DOI:10.14319/ijcto.0203.1
Smith, Eric A.; Turk, F. Joseph; Farrar, Michael R.; Mugnai, Alberto; Xiang, Xuwu
1997-04-01
This study presents research in support of the design and implementation of a combined radar-radiometer algorithm to be used for precipitation retrieval during the Tropical Rainfall Measuring Mission (TRMM). The combined algorithm approach is expected to overcome various difficulties that arise with a radar-only approach, particularly related to estimates of path-integrated attenuation (PIA) along the TRMM radar beam. A technique is described for estimating PIA at the 13.8-GHz frequency of the TRMM precipitation radar (PR) from 10.7-GHz brightness temperature TB measurements obtained from the TRMM microwave imager. Because the PR measures at an attenuating frequency, an independent estimate of PIA is used to constrain the solution to the radar equation, which incorporates effects of attenuation propagation along a radar beam. Through the use of variational or probabilistic techniques, the independent PIA calculations provide a means to adjust for errors that accumulate in estimates of range-dependent rain rates at progressively increasing range positions from radar reflectivity vectors. The accepted radar approach for obtaining PIA from ocean-viewing radar reflectivity measurements is called the surface reference technique, a scheme based on the difference in ocean surface cross sections between cloud-free and raining radar pixels. This technique has encountered problems, which are discussed and analyzed with the aid of coordinated aircraft radar (Airborne Rain Mapping Radar) and radiometer (Advanced Microwave Precipitation Radiometer) measurements obtained during the west Pacific Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment in 1993. The derived relationship expressing 13.8-GHz PIAs as a function of 10.7-GHz TB's is based on statistical fitting of many thousands of radiative transfer (RTE) calculations in which the relevant physical and radiative parameters affecting transmission, absorption, and scattering in a raining column and
基于节点可达度的公交多路径搜索算法%Multi-path search algorithm in public transportation based on node accessibility
符光梅; 王红
2012-01-01
针对公交网络路径搜索问题,以复杂网络的角度进行了相关研究.根据出行者实际需求,提出一种基于节点可达度的公交多路径搜索算法.采用复杂二分网络模型来描述公交网络,将公交线路和公交站点分别看做一类节点,每条公交线路与它所经过的公交站点之间存在连边;在分析网络社团结构的基础上定义了节点可达度,算法根据节点可达度逐步搜索直至目的节点,搜索过程保留可能存在的多条最佳路径.实验结果表明,该方法能够得到最小换乘的多条有效路径.%This paper studied path search problem in public transport network from the perspective of complex network, and proposed a multi-path search algorithm in public transportation based on node accessibility from the actual needs of travelers. This algorithm represented public transport network with complex bipartite network, which regarded bus lines and bus stations as different kinds of nodes respectively and there was an edge between each line and every station it passed. Based on the analysis of network community, it defined a concept of node accessibility. The algorithm searched paths from source node to destination node according to node accessibility and it reserved multiple possible optimal paths. Experiment result shows that this algorithm can find several effective paths which have the minimum transfer times.
Argoti, A.; Fan, L. T.; Cruz, J.; Chou, S. T.
2008-01-01
The stochastic simulation of chemical reactions, specifically, a simple reversible chemical reaction obeying the first-order, i.e., linear, rate law, has been presented by Martinez-Urreaga and his collaborators in this journal. The current contribution is intended to complement and augment their work in two aspects. First, the simple reversible…
Delany, J.M.
1985-11-25
EQ3/6 geochemical modeling code package was used to investigate the interaction of the Topopah Spring Tuff and J-13 water at high temperatures. EQ3/6 input parameters were obtained from the results of laboratory experiments using USW G-1 core and J-13 water. Laboratory experiments were run at 150 and 250{sup 0}C for 66 days using both wafer-size and crushed tuff. EQ3/6 modeling reproduced results of the 150{sup 0}C experiments except for a small increase in the concentration of potassium that occurs in the first few days of the experiments. At 250{sup 0}C, the EQ3/6 modeling reproduced the major water/rock reactions except for a small increase in potassium, similar to that noted above, and an overall increase in aluminum. The increase in potassium concentration cannot be explained at this time, but the increase in A1 concentration is believed to be caused by the lack of thermodynamic data in the EQ3/6 data base for dachiardite, a zeolite observed as a run product at 250{sup 0}C. The ability to reproduce the majority of the experimental rock/water interactions at 150{sup 0}C validates the use of EQ3/6 as a geochemical modeling tool that can be used to theoretically investigate physical/chemical environments in support of the Waste Package Task of NNWSI.
限定搜索区域的分层遗传算法无人机路径规划%Restricted Searching Area Hierarchical Genetic Algorithm for UAV Path Planning
王景; 李京华; 倪宁; 武琳静
2011-01-01
为克服简单遗传算法易陷入局部最优解的缺点,减小路径搜索范围,提出了限定搜索区域的分层遗传算法无人机路径规划方法,该方法将分层遗传算法引入无人机路径规划的优化搜索问题中,将路径节点的二维坐标作为基因进行编码,根据威胁的分布情况缩小路径规划算法的搜索范围,使子种群可以获得包含不同优良模式的新个体,为子种群提供更加平等的竞争生存机会,使优化搜索有较为明确的搜索方向.仿真结果表明:与基于分层遗传算法的路径规划方法相比,该方法提高了路径寻优算法的性能,减少了绕行路径的出现几率,缩短了最优路径的长度.%In order to overcome the shortcoming of simple genetic algorithm (SGA) that it is to fall into the local optimal solution and reduce the path search range, a restricted-searching-area HGA path planning approach was proposed. In this approach,the Hierarchy Genetic Algorithm (HGA) was introduced into the optimization problem of the UAV path planning, 2D coordinates of path nodes were coded as genes, searching area of path planning algorithm was reduced according to the distribution of threats,subpopulation could obtain individuals of different optimal patterns, and provided the subpopulation more equal an opportunity to compete with each to survival,thus the searching process became more directional. The simulation results showed that,comparing with HGA based path planning approaches, the proposed approach enhanced the performance optimal path planning and reduced the incidence of by-pass paths, thus the length of optimal path was shortened.
An Improved Algorithm of Semantic Similarity Computing Based on Path%一种改进的基于路径的语义相似度计算算法
曾诚; 韩光辉; 李兵; 朱子龙
2011-01-01
在概念之间的相似程度计算算法中,基于路径的语义相似度算法扮演着重要的角色.首先分析常用的几种基于路径的相似度计算算法,然后针对Wu和Palmer算法中存在的两个缺陷,提出了一种改进算法.从整体上来讲,这种算法的改进较为直观,容易实现,算法时间复杂度和Wu和Palmer算法类似.%In the kinds of similarity computing algorithms between concepts,path-based semantic similarity algorithm plays an important role.In this paper several path-based similarity computation algorithms are first introduced,and then an improved algorithm is provided in order to overcome the two defects in Wu and Palmer algorithms.General speaking,this improved algorithm is comparatively intuitive and easy to implement,and it＇s time complexity is similar to Wu and Palmer.
Research on genetic algorithm to hull markline marking path optimization%船体装配线划线优化遗传算法研究
吴俊杰; 纪卓尚; 常会青
2012-01-01
船体装配线划线作业是与船体零件数控切割作业同时进行的,是现代造船模式中的一个重要环节.分析归纳了装配线划线作业的特点,以划线顺序和划线方向为参数,划线空走路径最短为目标,采用多参数混合编码法,建立了划线优化的遗传算法优化数学模型.对划线顺序和划线方向采用不同的遗传策略进行进化.提出的随机变异算子维持了种群的多样性,精英子自进化策略加快了种群进化过程.运用＂贪心策略＂初始化种群,提高了种群的适应度.仿真证明该模型是可行的,实际应用表明可有效减少划线空走路径,提高船厂生产效率.%Hull markline marking, which is done with the CNC operations for hull parts at the same time, is one of the important parts in modern shipbuilding. According to the features of the marking, taking the marking order and the marking direction as the parameters and taking the minimum idle marking path as the objective, a mathematical model of marking optimization is established on the basis of hybrid encoding in genetic algorithm. The different genetic strategies are used for evolution of the marking order and the marking direction. The random mutation operator maintains the diversity of the population and the self-evolution of elite operator accelerates the evolution process. The use of ＂greedy strategy＂ for initial population improves the fitness of the population. The simulation results show that the model is effective, which can effectively reduce the idle marking path and improve the efficiency of shipbuilding.
An analytic algorithm for the space-time fractional reaction-diffusion equation
M. G. Brikaa
2015-11-01
Full Text Available In this paper, we solve the space-time fractional reaction-diffusion equation by the fractional homotopy analysis method. Solutions of different examples of the reaction term will be computed and investigated. The approximation solutions of the studied models will be put in the form of convergent series to be easily computed and simulated. Comparison with the approximation solution of the classical case of the studied modeled with their approximation errors will also be studied.
Schalock, Peter C; Menné, Torkil; Johansen, Jeanne D
2011-01-01
algorithm to guide the selection of screening allergen series for patch testing is provided. At a minimum, an extended baseline screening series and metal screening is necessary. Static and dynamic orthopaedic implants, intravascular stent devices, implanted defibrillators and dental and gynaecological...
Sassi, R.; Marcuzzi, F.; Mazzoli, C.
2008-12-01
One of the main goals of metamorphic petrology is to obtain information on the variations of metamorphic P-T conditions during orogenesis (P-T-t paths). For this purpose petrologists are aware of the potentiality of studying reaction microstructures, although results are not always satisfactory as in most cases qualitative approaches, failing on the real meaning of specific microstructral relationships, are often adopted. Thus, the present research aimed to study the petrogenetic meaning of reaction microstructure in metamorphic rocks through the formulation of a new true three-dimensional finite-element model. For this purpose, different petrologically well studied metamorphic microstructural situations have been selected, in order to identify information, variables and constraints fundamental for the development of the model. A generalised finite-elements model (FEM) has been developed, applicable to any microstructural situation, independently on grain-size and distribution of minerals in the matrix, and able to also consider growth anisotropies, intracrystalline diffusion, pressure solution, and possibly anisotropy of the strain field. This model is based on a combination of the usual diffusion linear equations used in current irreversible thermodynamic models, providing constraints on absolute values of diffusion coefficients of chemical components, chemical potential gradients and time of reactions during metamorphism, starting from information on textural anisotropies observed in metamorphic rocks. In the model, parameterization is given by diffusion, convection and reaction coefficients of each chemical species within each finite element, which dimension is equal to the spatial resolution of the experimentally measured input data (i.e. SEM elemental maps). Thus, parameterization is able to describe locally heterogeneous reaction phenomena although based on a basically linear partial derivative differential model. Such a discretization of the continuum model
Tsyganov, Y S
2015-01-01
Application of real-time matrix algorithm in heavy ion induced complete fusion nuclear reactions of superheavy elements synthesis is reviewed in brief. An extended algorithm, for the case of the recoil detection efficiency is not close to 100% has been proposed.
魏瑞轩; 许卓凡; 王树磊; 吕明海
2015-01-01
In order to relieve the operation burden and time consume for unmanned aerial vehicle (UAV) path planning,a novel UAV path planning method named LA-Star algorithm is proposed which as well guaran-tees the adaption in scenarios of various threat areas and terrains.Under the roundness assumption of all threat areas and no-fly-zones,the Laguerre diagram algorithm is applied to pre-plan the flight path which largely bene-fits path re-plan because of shrunk operation space.With the original shape of threat areas,improved A-Star al-gorithm is then applied in path re-planning with reference to pre-planned path.Finally,optimize the path planned above.Simulations show the LA-Star algorithm satisfies time and veracity requirements.%为了降低无人机航路规划的运算量，减少规划时间，确保算法对于任意形状威胁区域和地形的适应性以及所规划航路的准确性，提出了一种新颖的 LA-Star 算法用于无人机航路规划。首先把威胁区域和禁飞区域简化为圆形，利用 Laguerre 图算法进行航路预规划，在此基础上简化二次规划空间的范围，之后恢复威胁区域和禁飞区域的真实形状，在简化后的规划空间内使用改进 A-Star 算法实施二次航路规划，最后对生成的航路进行自优化处理。仿真结果证明了 LA-Star 算法满足航路规划的实时性和准确性要求。
冯奇; 周雪忠; 黄厚宽; 张小平
2011-01-01
Trial-based value iteration is a class of efficient algorithms to solve partially observable Markov decision process (POMDP), among which FSVI is one of the fastest algorithms. But the overhead of computing MDP value function by FSVI is not negligible for large-scale POMDP problems. In this paper, we propose a new value iteration method based on the shortest Hamiltonian path (shortest Hamiltonian path-based value iteration, SHP-VI). This method explores an optimal belief trajectory using the shortest Hamiltonian path resulting from ant colony optimization, and updates value function over the encountered belief states in reversed order. Compared with FSVI, the experimental results show that SHP-VI accelerates the computation of belief trajectory greatly in trial-based algorithms.%基于试探(trial-based)的值迭代算法是求解部分可观察Markov决策过程(partially observable Markov decision process,POMDP)模型的一类有效算法,其中FSVI算法是目前最快的算法之一.然而对于较大规模的POMDP问题,FSVI计算MDP值函数的时间是不容忽视的.提出一种基于最短哈密顿通路(shortest Hamiltonian path)的值迭代算法(shortest Hamiltonian path-based value iteration,SHP-VI).该方法用求解最短哈密顿通路问题的蚁群算法计算一条最优信念状态轨迹,然后在这些信念状态上反向更新值函数.通过与FSVI算法的实验比较,结果表明SHP-VI算法很大程度地提高了基于试探的算法计算信念状态轨迹的效率.
电力网络拓扑分析与源流路径链生成算法%Algorithm of Power Network Topology Analysis and Path Chains Generation
陈彬; 于继来
2012-01-01
For obtaining path chains between sources and flows quickly, a new algorithm, which can analyze power network topology and generate path chains, was proposed in the paper. The algorithm firstly built directed graph and adjacency list between sending buses and sending branches based on the network topology and flow state; and then, it obtained path chain sets from the path chain trees which were generated through two rounds network topology. Getting rid of the adjacency matrix, the proposed algorithm is easier and faster. Moreover, it can change the path chains locally while the topology or the flow state changes in some part of the power network.%为快速、准确和全面地求取电力网络源流路径链,提出了一种新型的网络拓扑分析与源流路径链生成算法.该算法首先根据电网某—拓扑结构及其潮流状态形成有向图和送端节点—送电支路邻接表,然后进行两轮拓扑分析,快速生成源流路径树,并由此获取相关的源流路径链.此算法无需通过基于图论邻接终点矩阵的复杂运算,简便快捷.此外,该算法可用于求解电力网络发生局部拓扑和局部潮流流向变化后的路径链局部修改问题.
傅阳光; 周成平; 胡汉平
2012-01-01
To investigate the path of unmanned aerial vehicle ( UA) in ocean environment, a method based on the differential evolution(DE) is proposed. It pretreats the planning environment and takes all islands as threatened areas, the path planning problem is simplified as a two-dimensional planning problem. A real number coding is used to represent the candidate paths, and a mathematical model of path cost is established. The performance of differential evolution algorithm is compared with that of genetic algorithm ( GA) and particle swarm optimization ( PSO) in terms of path quality, robustness and convergence speed. The experimental results demonstrate that the proposed method is able to generate a safe and flya-ble path for UAV in a complex ocean environment.%为研究海洋环境下的无人飞行器(UAv)航迹规划问题,提出了一种基于差分进化算法(DE)的航迹规划方法.该方法通过对规划环境进行预处理将岛屿处理成地形威胁区,使问题简化为二维平面规划.采用实数编码方式对航迹进行编码,建立了航迹代价函数的数学模型,从航迹质量、算法稳定性和收敛速度3个方面比较了DE与遗传算法(GA)和粒子群优化算法(PSO)的性能.仿真实验结果表明,所提方法能在复杂的海洋环境下为飞行器规划出一条安全的可飞航迹.
王玮; 王玉惠; 王文敬; 张洪波
2016-01-01
The path planning for warship-aircraft joint operation is studied. Firstly, the weapon system of the destroyer is analyzed to obtain the safe distance when the shipboard helicopter and the destroyer are performing a task cooperatively. Since the traditional A∗ algorithm cannot be applied directly to the path planning for warship-aircraft joint operation, the security costs and the path safety factor are introduced. An improved weighted A∗ algorithm is given based on the traditional algorithm, to solve the path planning problem for warship-aircraft joint operation. Finally, a case simulation is given to verify the effectiveness of the improved algorithm.%基于改进加权A∗算法研究了舰机联合航迹规划问题。首先，通过分析驱逐舰的武器系统结构，得出驱逐舰和舰载直升机在联合执行任务时的安全距离；由于传统A∗算法运用于舰机联合航迹规划问题的局限性，引入安全代价和路径安全值加权系数，基于传统A∗算法给出了改进加权A∗算法，协同规划舰艇和舰载机的路径；最后，通过案例仿真验证了算法的有效性。
General Attitude Control Algorithm for Spacecraft Equipped with Star Camera and Reaction Wheels
Wisniewski, Rafal; Kulczycki, P.
A configuration consisting of a star camera, four reaction wheels and magnetorquers for momentum unloading has become standard for many spacecraft missions. This popularity has motivated numerous agencies and private companies to initiate work on the design of an imbedded attitude control system...... realized on an integrated circuit. This paper considers two issues: slew maneuver with a feature of avoiding direct exposure of the camera's CCD chip to the Sun %, three-axis attitude control and optimal control torque distribution in a reaction wheel assembly. The attitude controller is synthesized...
基于遗传算法的无人机航迹规划代价函数%A Study on Cost Function of UAV Path Planning Based on Genetic Algorithm
杨楠; 张健; 朱凡; 陈力威
2012-01-01
With the shortage of cost function of UAV path planning, an optimization method based on genetic algorithm is proposed. The traditional genetic algorithm is improved and the polar coordinate coding mode and path fitness function are designed. On the basis of genetic operators, the strategy for elite preserving is adopted to promote the algorithm effectiveness; Besides cost normalized and optimized thought are used to get the optimized weight values. The optimization results show this method can obtain the lower cost path.%针对当前使用的无人机航迹规划代价函数的不足之处,提出一种利用遗传算法对无人机航迹规划代价函数进行优化的方法.对基本遗传算法进行了局部改进,设计了航迹极坐标编码方式及航迹适应度函数,在采用基本遗传操作算子的基础上采取精英保存策略,提高了算法的效率；采用代价归一化并进行优化的思想,得到优化之后的代价函数权重值.优化结果表明,该方法可以获得代价更低的航迹.
Application of Artificial Immune Algorithm in Path Planning of Mobile Robot%免疫算法在移动机器人路径规划中的应用
赵娜
2012-01-01
The article expounds in details the application of immune algorithm in the path planning of mobile robot.It makes the robot avoiding obstacles and finding a shortest path from starting point to the target point.To build the mathematical model and affinity function of mobile robot,it gives the control method for robot;also the algorithm description and simulation experiment are given in detail in this paper.The experiment result shows that the immune algorithm has good performance when applying into the path planning.%具体阐述了免疫算法在移动机器人路径规划中的应用,使机器人从给定点到目标点可以有效地躲避障碍物而且找到一条最短的路径;构建了机器人的数学模型和亲和力函数,并且说明了机器人的控制方式,给出了算法的具体实现步骤以及仿真实验。实验结果表明,免疫算法在应用到移动机器人路径规划时具有良好的性能。
无线传感器网络中能量多路径路由算法的研究%Research on Energy Multi-path Routing Algorithm for Wirelss Sensor Networks
李琴
2014-01-01
能量多路径路由算法考虑了通信路径上的能量消耗和剩余能量，节点根据概率选择下一跳节点。改进算法在原有算法的基础上加入了路由跳数控制，实验仿真结果表明根据改进算法所获得的传输路径跳数和传输能耗明显减少，延长了网络生命周期。由于无线传感器网络是动态变化的，文章最后提出了动态跳数限制的想法以期能够更好的适应传感器网络，选择最优路径。%Energy multi-path routing algorithm considers energy consumption and residual energy on the communication path, node based on the probability to select the next hop node. Improved algorithm adds the control of routing hops, Simulation proof Improved algorithm select a smaller number of hops to extend the network life cycle. Wireless sensor network is dynamic, in the end we put up dynamic hop count limit in order to adapt to WSN and select the optimal path.
彭松; 贾阳
2012-01-01
In the tele-operation system of lunar rover,the path planning contains three levels： mission-level path planning,global path planning and local path planning.Based on the requirements of the global path planning of the lunar rover,the Particle Swarm Optimization（PSO） algorithm is introduced in the global navigation point planning.Since the PSO algorithm may converge ill or not converge in path planning, the algorithm is modified.In the modified algorithm,the velocity inertial weight is deleted,but the cognitive and social coefficients are kept,with the aim at making the algorithm converge quickly in path planning.Also the variation coefficient in evolution algorithm is imported to enhance the global optimization ability.Simulation results show the improved algorithm is simple and has high ability to find the best path.Also simulation tests are done in several different simulated lunar terrain maps,and optimization methods are given to make the planning result better.%在月面巡视器遥操作系统中,路径规划分为任务级路径规划、全局路径规划和局部路径规划。根据巡视器全局路径规划的应用要求,引入粒子群优化算法应用于全局导航点的规划。针对粒子群算法在路径规划中容易造成不收敛或病态收敛的问题,对算法进行了修改,去掉了速度更新中的速度惯性因子,只保留自身认识因子和社会认识因子,使其在全局路径规划中能够快速收敛;同时引入经典遗传算法中的变异因子以增强算法的全局优化能力。仿真结果表明该算法具有计算简单、全局寻优能力强等特点,能够快速地找到优化的全局导航点。同时在不同的模拟月面地形上进行仿真试验,针对存在的问题提出了对应的二次优化方法,结果表明该方法较好地满足了巡视器全局路径规划的应用需求。
An exact and efficient first passage time algorithm for reaction-diffusion processes on a 2D-lattice
Bezzola, Andri; Bales, Benjamin B.; Alkire, Richard C.; Petzold, Linda R.
2014-01-01
We present an exact and efficient algorithm for reaction-diffusion-nucleation processes on a 2D-lattice. The algorithm makes use of first passage time (FPT) to replace the computationally intensive simulation of diffusion hops in KMC by larger jumps when particles are far away from step-edges or other particles. Our approach computes exact probability distributions of jump times and target locations in a closed-form formula, based on the eigenvectors and eigenvalues of the corresponding 1D transition matrix, maintaining atomic-scale resolution of resulting shapes of deposit islands. We have applied our method to three different test cases of electrodeposition: pure diffusional aggregation for large ranges of diffusivity rates and for simulation domain sizes of up to 4096×4096 sites, the effect of diffusivity on island shapes and sizes in combination with a KMC edge diffusion, and the calculation of an exclusion zone in front of a step-edge, confirming statistical equivalence to standard KMC simulations. The algorithm achieves significant speedup compared to standard KMC for cases where particles diffuse over long distances before nucleating with other particles or being captured by larger islands.
Williams, Virginia Vassilevska
2010-01-01
The replacement paths problem for directed graphs is to find for given nodes s and t and every edge e on the shortest path between them, the shortest path between s and t which avoids e. For unweighted directed graphs on n vertices, the best known algorithm runtime was \\tilde{O}(n^{2.5}) by Roditty and Zwick. For graphs with integer weights in {-M,...,M}, Weimann and Yuster recently showed that one can use fast matrix multiplication and solve the problem in O(Mn^{2.584}) time, a runtime which would be O(Mn^{2.33}) if the exponent \\omega of matrix multiplication is 2. We improve both of these algorithms. Our new algorithm also relies on fast matrix multiplication and runs in O(M n^{\\omega} polylog(n)) time if \\omega>2 and O(n^{2+\\eps}) for any \\eps>0 if \\omega=2. Our result shows that, at least for small integer weights, the replacement paths problem in directed graphs may be easier than the related all pairs shortest paths problem in directed graphs, as the current best runtime for the latter is \\Omega(n^{2.5...
Path Optimization of Cold Chain Logistics Based on Improved Genetic Algorithm%基于改进遗传算法的冷链物流路径优化研究
陶云; 张鹏程
2016-01-01
针对冷链物流配送优化问题，以配送成本最低、运输路径最优为目标，发现冷链物流存在配送成本较高、配送路径待优化等问题，基于此，提出路径优化的论点。考虑货损成本和惩罚成本，构建带时间窗的配送模型，并选用遗传算法作为路径优化的算法基础，引入Tent混沌映射对种群加以扰动，对算法各算子模块作改进，得到改进遗传算法，并以淮南田家庵区苏果超市冷链配送为例，验证了算法的有效性和优越性。%For the cold chain logistics distribution optimization problem ,with the lowest cost of distribution and the optimal transportation path as the goal ,it analyzed some problems in this paper such as the distri-bution cost of cold-chain logistics is very high and distribution path waits to be further optimized ,then it put forward some research arguments based on these problems .Considering the damage cost and punish-ment cost ,it constructed a distribution model with time Windows and used genetic algorithm as path opti-mization algorithm .It brought in the Tent chaos mapping to perturbance population ,and improved opera-tors of the algorithm to get the improved genetic algorithm .Finally through the example of Suguo super-market in Tianjiaan area of Huainan city on cold-chain distribution problem ,simulation consequence veri-fied the validity and superiority of the algorithm .
刘锴; 游晓明; 刘升
2016-01-01
针对蚁群算法易陷入路径死锁的缺点,提出了一种复杂环境下移动机器人路径规划的改进蚁群算法.对机器人环境建立栅格模型,在传统转移规则中引入指向上一节点的数组,增强了算法的逃逸能力;在信息素更新中减去最差蚂蚁释放的信息量,有利于种群的进化.仿真分析了主要参数对算法性能的影响,实验结果表明,该算法在复杂地图中搜索到的路径优于传统算法.%For the shortcomings of easy to fall into the path deadlocks, an improved ant colony algorithm is proposed to plan the optimal collision-free path for a mobile robot in a complex environment. Firstly, grid model of the robot environ-ment is established, and an array of element point to the previous is employed to enhance the escaping capability of algo-rithm. It utilizes the pheromone released by the worst ant to update the pheromone, which is conducive to the evolution of the colony. The main parameters'influence on the performance of the algorithm is analyzed. Simulation results show that the optimal collision-free path on the complex map obtained by this algorithm is superior to the traditional algorithm.
Luiz C. G. de Souza
2013-01-01
Full Text Available An experimental attitude control algorithm design using prototypes can minimize space mission costs by reducing the number of errors transmitted to the next phase of the project. The Space Mechanics and Control Division (DMC of INPE is constructing a 3D simulator to supply the conditions for implementing and testing satellite control hardware and software. Satellite large angle maneuver makes the plant highly nonlinear and if the parameters of the system are not well determined, the plant can also present some level of uncertainty. As a result, controller designed by a linear control technique can have its performance and robustness degraded. In this paper the standard LQR linear controller and the SDRE controller associated with an SDRE filter are applied to design a controller for a nonlinear plant. The plant is similar to the DMC 3D satellite simulator where the unstructured uncertainties of the system are represented by process and measurements noise. In the sequel the State-Dependent Riccati Equation (SDRE method is used to design and test an attitude control algorithm based on gas jets and reaction wheel torques to perform large angle maneuver in three axes. The SDRE controller design takes into account the effects of the plant nonlinearities and system noise which represents uncertainty. The SDRE controller performance and robustness are tested during the transition phase from angular velocity reductions to normal mode of operation with stringent pointing accuracy using a switching control algorithm based on minimum system energy. This work serves to validate the numerical simulator model and to verify the functionality of the control algorithm designed by the SDRE method.
Malinovsky, Yaakov; Albert, Paul S; Roy, Anindya
2016-03-01
In the context of group testing screening, McMahan, Tebbs, and Bilder (2012, Biometrics 68, 287-296) proposed a two-stage procedure in a heterogenous population in the presence of misclassification. In earlier work published in Biometrics, Kim, Hudgens, Dreyfuss, Westreich, and Pilcher (2007, Biometrics 63, 1152-1162) also proposed group testing algorithms in a homogeneous population with misclassification. In both cases, the authors evaluated performance of the algorithms based on the expected number of tests per person, with the optimal design being defined by minimizing this quantity. The purpose of this article is to show that although the expected number of tests per person is an appropriate evaluation criteria for group testing when there is no misclassification, it may be problematic when there is misclassification. Specifically, a valid criterion needs to take into account the amount of correct classification and not just the number of tests. We propose, a more suitable objective function that accounts for not only the expected number of tests, but also the expected number of correct classifications. We then show how using this objective function that accounts for correct classification is important for design when considering group testing under misclassification. We also present novel analytical results which characterize the optimal Dorfman (1943) design under the misclassification.
基于遗传算法的多边形分割AUV全局路径规划%Genetic algorithm based on polygon segmentation AUV global path planning
李建文; 李沙沙
2013-01-01
Appear in the actual AUV global path planning applications for genetic algorithm computed data,path planning issues such as spikes,a new path planning method is proposed.Plane rectangular coordinate system environment modeling obstacle simplified polygon is divided into triangles.End-to-end path segment,the fixed abscissa,ordinate randomly generated binary-coded genetic algorithm obstacle triangle intersection determination,the path from the operation prepared by the applicable function.After genetic path through the obstacle avoidance,delete nodes,smooth operation to determine the final optimization path.Results show that the simplified implementation obstacles triangle program optimization in genetic operation,use of obstacle avoidance,remove redundant node,smooth operation,can very good eliminate peak,can find a relatively optimal path.%针对遗传算法在实际AUV全局路径规划应用中出现运算数据大、路径规划有尖峰等问题,提出了新型路径规划方法.利用平面直角坐标系实现环境的建模,将障碍物简化成多边形并分割为三角形.路径用首尾相接的线段表示,通过固定横坐标,随机生成纵坐标的方式实现遗传算法二进制编码,对障碍物三角形交叉判断,路径距离运算实现适用度函数编写.对遗传之后的路径通过避障、删除节点、平滑的操作确定最终优化路径.结果表明,对障碍物的三角形简化实现了在遗传操作中的程序优化,利用避障、删除多余节点、平滑操作实可很好的消除尖峰,可寻找一条相对较优的路径.
赵连娜; 赵凯; 李磊; 赵秀娟; 李洋
2016-01-01
In order to recognize the special path of smart car quickly, stably and autonomously, an algorithm of recognizing the special path autonomously was proposed. The embedded system based on MK60DN512 was used as well as CMOS camera OV7620 as the chief sensor. The special paths such as the switch between single and double line, the right angle, the obstacle and the four cross way, are identified by using racing track center line, bang-bang and the least square method fitting path trajectories. The experimental results show that the smart car which applies the proposed algorithm could achieve accurate-recognition and rapid-driving in any path.%为实现智能车特殊路径快速稳定自主识别，本文提出了一种特殊路径快速识别算法。采用MK60DN512为核心控制模块，选用CMOS摄像头OV7620为主要传感器，通过中心线跟踪检测和最小二乘法拟合路径轨迹实现特殊路径的识别，其中特殊路径包括单双线切换、直角、障碍和十字叉路。所提控制算法能够使得智能车快速有效地实现任意路径的准确识别与平稳行驶，实验结果验证了控制算法有效可行。
Path indexing for term retrieval
1992-01-01
Different methods for term retrieval in deduction systems have been introduced in literature. This report eviews the three indexing techniques discrimination indexing, path indexing, and abstraction tree indexing. A formal approach to path indexing is presented and algorithms as well as data structures of an existing implementation are discussed. Eventually, experiments will show that our implementation outperforms the implementation of path indexing in the OTTER theorem prover.
巩敦卫; 曾现峰; 张勇
2013-01-01
Aiming at the path planning problem of robot in global static environment, a modified simulated annealing algorithm was proposed which is easy to implement. In this algorithm, a new method used to generate new status was introduced by defining an off-barrier operator and an optimal search operator. The first operator utilizes a directional disturbance strategy to help path points jump off the obstacles. It not only ensures free-collision of the generated path, but also enhances search efficiency of the algorithm. The second one adjusts the path points chosen randomly with dynamic ranges. Hence, it makes the algorithm be able to generate new position in the whole search space, and enhances the global search capability of the algorithm. Finally, simulation results verify the effectiveness of the proposed algorithm.%针对全局静态移动机器人路径规划问题,给出了一种简单易行的改进模拟退火算法.算法通过引入脱障算子和一致寻优算子,提出了一种新的状态产生方法.前者采用维值定向扰动策略,使碰撞路段的两个端点以一定步长跳离障碍物,这既保证了路径的无碰性,又加快了寻优效率；后者对随机选取的若干个路径点进行变步长地调整,使产生的候选解可以遍布整个解空间,提高了算法的全局寻优能力.最后,通过对一般环境和“陷阱”环境路径规划问题的仿真,验证了该方法的有效性.
A Path Planning Algorithm Based on Convex Hull for Autonomous Service Robot%一种基于凸壳的智能服务机器人路径规划算法
杨毅; 刘亚辰; 刘明阳; 付梦印
2011-01-01
A path planning algorithm based on convex hull is applied to autonomous service robot in this paper. Firstly, the coordinates of ball positions are determined by using Haar-like features classifier, the coordinate of robot's position and its heading are determined by using the method based on color model. According to the features of the robot itself, the balls in a certain range can be treated as one target point. Then a better ball-picking path is elaborated with a path planning algorithm based on convex hull, which takes the target points as the input of algorithm. The algorithm alleviates the robot's motion cost and improves the ball-picking efficiency of the autonomous service robot obviously.%将一种基于凸壳的路径规划算法应用于体育场智能服务机器人,首先采用基于Haar特征分类器的方法确定球的坐标,采用基于颜色模型的方法确定机器人的位置及航向,并根据机器人的自身特点,将一定范围内的多个球视为一个目标点处理;然后以目标点坐标作为算法输入,采用基于凸壳的路径规划算法得到一条较优的捡球路径.该算法可以降低机器人的捡球运动代价,有效提高机器人的捡球效率.
王江华; 楼佩煌; 钱晓明
2015-01-01
针对自动导引车系统路径规划问题，首先提出了一种新的路径网络模型，即单双向混合路径网络布局。然后在仔细分析该种路径布局的特征和优势的基础上，使用改进的遗传算法实现其路径网络的规划，并详细描述了算法步骤。最后，通过对两个自动搬运系统进行路径规划、系统建模、系统仿真和对比分析，验证了单双向混合路径网络布局的优越性和可行性。%To deal with the guide-path configuration problem for automated guided vehicle system, it presents a new guide-path model called mixed uni/bidirectional guide-path network, analyzes both structure and advantages of the guide-path network, proposes an improved genetic algorithm to configure the mixed uni/bidirectional guide path network.To verify the superiority and feasibility of mixed uni/bidirectional guide-path network, it illustrates two examples of automated handling system.This method configures the mixed networks, shows their perform-ance and compares them with the corresponding unidirectional AGVS.
齐骥; 王宇鹏; 钟志
2016-01-01
In this paper,a multi-stage path prediction algorithm of the decentralized mission planning for cooperative UAVs is presented. The planning horizon is defined as the period between the start of task assignment and completion of any task.In every planning horizon, each UAV utilizes the A* algorithm to predict the paths to all tasks and provide the path distances for task assignment.Furthermore,the cluster algorithm is introduced to modify the tasks value vector.The UAVs negotiate the task assignment solution and calculate the shortest path to assigned task in the detection range in real time.Finally,the B-spline curve is addressed to convert the shortest path into flyable smoothing trajectory that subject to the flight constraints.For validation,the scenario of multiple UAVs to perform cooperative missions is considered.Numerical results show that the proposed algorithm can achieve the quasi-optimal assignment solution and generate the flyable trajectory in real time.In addition,the satisfactory performance to accomplish the pop-up tasks is demonstrated.%针对多无人机（Unmanned Aerial Vehicles，UAVs）协同控制问题，提出了一种UAVs多阶段航迹预测分布式任务规划方法；定义从一次任务分配开始到其中一项任务完成为一个任务周期；在每个规划周期，首先，各UAV使用A*算法快速预测到所有任务目标的路径，提供至任务分配；然后，采用聚类算法修改目标价值向量，协商分配结果，并实时计算探测范围内的最短路径；最后，采用三次B样条曲线平滑所分配的最短路径，在线规划出满足飞行约束的飞行航迹；通过仿真实验对算法的有效性进行了验证，结果表明，提出的算法能够实时获得近似最优的任务分配结果并规划出可飞行航迹，并有效处理突发任务。
Criscenti, Louise J; Kubicki, James D; Brantley, Susan L
2006-01-12
Molecular orbital energy minimizations were performed with the B3LYP/6-31G(d) method on a [((OH)3SiO)3SiOH-(H3O+).4(H2O)] cluster to follow the reaction path for hydrolysis of an Si-O-Si linkage via proton catalysis in a partially solvated system. The Q3 molecule was chosen (rather than Q2 or Q1) to estimate the maximum activation energy for a fully relaxed cluster representing the surface of an Al-depleted acid-etched alkali feldspar. Water molecules were included in the cluster to investigate the influence of explicit solvation on proton-transfer reactions and on the energy associated with hydroxylating the bridging oxygen atom (Obr). Single-point energy calculations were performed with the B3LYP/6-311+G(d,p) method. Proton transfer from the hydronium cation to an Obr requires sufficient energy to suggest that the Si-(OH)-Si species will occur only in trace quantities on a silica surface. Protonation of the Obr lengthens the Si-Obr bond and allows for the formation of a pentacoordinate Si intermediate ([5]Si). The energy required to form this species is the dominant component of the activation energy barrier to hydrolysis. After formation of the pentacoordinate intermediate, hydrolysis occurs via breaking the [5]Si-(OH)-Si linkage with a minimal activation energy barrier. A concerted mechanism involving stretching of the [5]Si-(OH) bond, proton transfer from the Si-(OH2)+ back to form H3O+, and a reversion of [5]Si to tetrahedral coordination was predicted. The activation energy for Q3Si hydrolysis calculated here was found to be less than that reported for Q3Si using a constrained cluster in the literature but significantly greater than the measured activation energies for the hydrolysis of Si-Obr bonds in silicate minerals. These results suggest that the rate-limiting step in silicate dissolution is not the hydrolysis of Q3Si-Obr bonds but rather the breakage of Q2 or Q1Si-Obr bonds.
A New System Restoration Path Search Algorithm and Its Applicability Research%系统恢复路径搜索新算法及其适用性研究
周云; 严正; 李乃湖; 冯冬涵; 戴世刚; 陈丽霞
2016-01-01
系统恢复过程中，恢复路径承担着为非自启动机组传输启动功率、响应临近子系统的功率需求和提供用户负荷功率等任务。恢复路径搜索模块作为整体系统恢复优化模型重要且必要的模块之一，现有基于图论的经典路径搜索算法计算复杂度高，影响了系统恢复优化模型的整体计算速度。该文分别基于线路参数、系统潮流和复杂网络理论建立系统恢复路径权值模型，利用系统地理位置信息构建A*算法中的估值函数，进而建立系统恢复路径搜索新算法。采用路径搜索过程中展开的节点数和搜索耗时综合衡量路径搜索算法的计算复杂度，华东某实际区域电网算例和美国某州电网算例验证了新算法对不同系统恢复路径权值模型的适用性。%During system restoration process, restoration paths are used for transferring cranking power to non-black-start units, responding to power request from neighboring subsystems and serving user loads. Restoration path search module is one of both important and necessary modules of the entire system restoration optimization model. The existing classical path search algorithms based on graph theory have high computational complexity, which affects the overall computing speed of the system restoration optimization model. In this paper, the system restoration path weighting models were built up based on line parameters, system power flow and complex network (CN) theory respectively. The evaluation function in A* algorithm was constructed by system geographic information and on this basis a new system restoration path search algorithm was proposed. The count of nodes expanded and searching duration in the search process were introduced to measure the computational complexity of the path search algorithm comprehensively. Case studies of an actual regional power grid in eastern China and an open accessed state power grid of USA demonstrated the
Global path planning for lunar rover based on fruit fly optimization algorithm%基于果蝇优化算法的月球车全局路径规划
毛正阳; 方群
2014-01-01
Based on the requirements of the global path planning of the lunar rover, the Fruit Fly Optimization Algorithm is introduced in the global navigation point planning. Since FOA may converge ill, the algorithm is modified. In the modified algorithm, the distance from fruit flies to the origin is directly put into the fitness function, which is not easy to fall into local optimum,improve the stability of the algorithm, and make the flies group fly to known food source. Simulation results show the improved algorithm is simple and has high ability to find the best path.%基于月球车全局路径规划的任务要求，采用果蝇优化算法应用于全局路径的规划。针对果蝇优化算法在路径规划中容易形成局部最优的问题，对算法进行了修改，将果蝇与原点的距离直接带入味道浓度判定函数，从而不易陷入局部最优，提高了算法的稳定性，并可使果蝇群体向已知食物源飞行。通过仿真表明该算法具有计算简单、全局寻优能力强等特点，能够快速地找到优化的全局路径。
Auction Algorithm for Shortest Paths and its Application in Route Guidance%最短路径Auction算法及其在路径诱导中的应用
杜牧青; 程琳
2012-01-01
Taking Dijkstra's algorithm as a reference, the algorithm s performance was tested in the "one-to-one" shortest path problems via a corresponding computer program coded in C#. The computational tests on the actual networks and random networks show the advantages of Auction algorithm' s principle. But its overall performance is not as good as labeling algorithms, I. E. Some computational steps of iteration are repeated too many times, affecting the efficiency. Reducing these redundant operations, Auction algorithm could be improved.%通过采用C#语言程序,对比传统路径算法,并在实际道路网络和随机网络中进行了试验,测试了算法在求解网络“一对一”最短路径问题时的运算性能.结果表明,Auction算法在求解此类问题时,体现算法自身原理的优势,虽然整体性能表现不及经典的路径算法,即迭代步骤略多,但仍有改进的余地.
陈侠; 刘冬
2013-01-01
With respect to the problem of 3D path planning of Unmanned Aerial Vehicles ( UAV) under uncertain environments when the target is moving,a method of fast 3D path planning was designed based on the improved D*Lite algorithm .By use of the improved cost evaluating function and the real-time information of unanticipated threats and moving targets,and based on the constraints together with the improved search algorithm,a method of 3D path planning for UAVs was given .The simulation results demonstrated that the algorithm can not only meet the real-time path planning demands,avoid the unanticipated threats and attack the moving targets,but also reduce the search space,improve the search efficiency and optimizing capability,which is a good method for path planning of UAV under uncertain environments .% 针对不确定环境下目标移动时的无人飞行器三维航迹规划问题，采用改进的D*Lite搜索算法，设计了一种三维航迹快速规划方法。利用改进的代价评估函数，根据突发威胁和移动目标的实时信息，将航迹规划约束条件和改进的搜索算法相结合，给出了地面目标移动时的无人飞行器三维航迹规划方法。仿真结果表明，该算法不但可以满足实时在线的航迹规划要求，能够有效躲避突发威胁，打击移动目标，还能有效地缩小搜索空间，提高搜索效率及寻优能力，能较好地解决不确定环境下目标移动时的航迹规划问题。
高国琴; 李明
2014-01-01
针对温室移动机器人机器视觉导航路径识别实时性差、受光照干扰影响严重等问题，首先，将HSI颜色空间3个分量进行分离，选取与光照信息无关且可以有效抑制噪声影响的色调分量H进行后续图像处理，以削弱光照对机器人视觉导航的不良影响；针对温室环境图像特有的颜色特征信息，引入K-means算法对图像进行聚类分割，将垄间道路信息与绿色作物信息各自聚类，再通过形态学腐蚀方法去除聚类后图像中存在的冗余、干扰信息，以获得完整的道路信息，与常用阈值分割方法相比，可降低因分割信息不明确而导致后续Hough变换进行直线拟合时需占据大量内存且计算量较大的问题，进而提高移动机器人路径识别的快速性，并适应温室作业机器人自主导航的高实时性要求。试验结果表明，该文方法在复杂背景与变光照条件下的温室作业环境中可大幅降低光照对机器人导航的影响，对于光照不均具有良好的鲁棒性，道路信息提取率可达95%。同时，其平均单幅图像处理时耗降低53.26%，可显著提高路径识别速度。该研究可为解决温室移动机器人机器视觉导航路径识别的鲁棒性及实时性问题提供参考。%In a greenhouse with an unstructured environment, for the images collected by monocular vision, conventional path recognition algorithms are difficult to guarantee their robustness due to illumination variation, background reflection, shadow noise, etc. In addition, the increase of the amount of calculation of algorithms caused by the complicated background information of the greenhouse environment affects the quickness and the real-timeness of the greenhouse mobile robot autonomous navigation, which leads to the difficulty of meeting the requirement for the operation efficiency of the greenhouse mobile robot and impedes the practical application of the mobile robot
农用轮式铰接车辆滑模轨迹跟踪控制算法%Sliding mode control algorithm for path tracking of articulated dump truck
赵翾; 杨珏; 张文明; 曾珺
2015-01-01
The articulated frame steering vehicles (ASV) are widely implemented in agriculture, mining, construction and forestry sectors due to their high maneuverability. The ASVs, however, are known to possess lower dynamic stability and yield high magnitude of whole-body vibration, which are reported to be harmful to the operators. Automatic driving system is thus necessary for the ASVs to exclude the human driver from detrimental operations, especially for the agricultural ASV. In order to enable the automation of ASV, path tracking strategies are essential to maintain the normal work of the vehicles. As the ASV dynamics significantly are different from the conventional vehicles with front wheel steering, the path tracking controller derived for conventional vehicles is considered not to be applicable for the ASVs. Moreover, large variations of the vehicle load and the off-road excisions challenge the robustness of path tracking algorithms. In this paper, a path tracking strategy is proposed for the ASVs on the basis of sliding mode control (SMC). The kinematic model of the ASV is derived neglecting the vehicle dynamics. Three measurable errors are defined to indicate the deviation of real path from reference path, i.e. lateral displacement error, orientation error and curvature error. These errors serve as the inputs in order to synthesize the SMC. The exponential reaching law is selected in order to increase the reaching speed and reduce chattering. The sign function of exponential reaching law is replaced by a continuous function to further suppress the chattering. Lyapunov function is then utilized in order to assess the system stability. The system transition performances in terms of response time, setting time and overshooting are tuned via pole placement method. The differential transformation method is implemented to determine the poles, in order to obtain the transition performances while preserving the system stability. Ackermann’s formula is used to improve
UAV Path Planning Based on Adaptive Genetic Algorithm%基于自适应遗传算法的无人机航迹规划方法研究
徐正军; 唐硕
2008-01-01
With the development of the warfare, it becomes more and more difficult for the military aircraft to attack the target. Path planning is one of the available methods to increase the survival probability. In recent years, genetic algorithm (GA) has been successfully applied to path planning problems for unmanned aerial vehicle (UAV) systems, including single- and multi-vehicle systems. A new encoding method was designed by using bilinear-chain node and the mutation operator with combined operator with reconstruction operator and disturbance operator was improved. An adaptive genetic algorithm (ADGA), which determined the optimal path between the nodes with respect to a set of cost factors and constraints, was applied to the optimal path planning. Example simulation shows that the new algorithm satisfies the requirements in the computation efficiency and the precision of the solution. The algorithm is easy to be realized. Its practicability is improved.%随着攻防系统的发展与完善,实现飞行器有效突防越来越困难,而采用航迹规划技术能够有效的提高飞行器的突防概率.基于此,首先研究了参考航迹的角度、高度以及航迹段长度等约束条件;其次对航迹编码方式进行了改进,采用全实数的双向链表的编码方式;对自适应遗传算法的交叉和变异概率的计算方法、交叉算子和变异算子进行了改进,并应用该算法在求解航迹规划问题上进行了仿真研究,对采用不同的变异算子所得结果进行了对比分析.仿真计算的结果表明,该算法能够规划出一条满足要求的参考航迹,采用组合变异算子能取得比采用单个变异算子更优的参考航迹.
Ghassib, Humam B; Sakhel, Asaad R; Obeidat, Omar; Al-Oqali, Amer; Sakhel, Roger R
2012-01-01
We demonstrate the effectiveness of a statistical potential (SP) in the description of fermions in a worm-algorithm path-integral Monte Carlo simulation of a few 3He atoms floating on a 4He layer adsorbed on graphite. The SP in this work yields successful results, as manifested by the clusterization of 3He, and by the observation that the 3He atoms float on the surface of 4He. We display the positions of the particles in 3D coordinate space, which reveal clusterization of the 3He component. The correlation functions are also presented, which give further evidence for the clusterization.
马继红
2016-01-01
In order to improve the adaptive ability of the planter of complex block, enhance the sowing efficiency of planter seeding accuracy, it put forward suitable for precision seeding machine in sub regional exhumation of full area coverage path planning method based on the seeder row fertilizer.The seed metering device was improved so as to adapt to the need of automatic path planning.In order to optimize the path search method based on sub region, the artificial po-tential field and genetic algorithm are used to optimize the optimization method, which improves the efficiency of the algo-rithm.For the validity and reliability of the test method, path planning system is installed in the planting machinery. Through the seeding test, the method realized complex plots sown with the full area coverage and obstacle avoidance.On the three different algorithms for comparison tests,it was found that optimization effect is the best for its large coverage ar-ea based on genetic algorithm of sub regional model for path planning, turning times less, fewer, the shortest time only 11.25min, only for 1/2 of the other algorithm, path division of higher efficiency and meet the intelligent demand of pre-cision seeding machine, which can be used in path planning system in precision seeder.%为了提高播种机对复杂地块的自适应能力,提升播种机的播种精度和播种效率,提出了适合精播机的基于子区域的折返全区域覆盖路径规划方法,并对播种机的排肥器和排种器进行了改进,以适应自动路径规划的需要. 为了优化基于子区域的路径搜索方法,使用人工势场和遗传算法对寻优方法进行了优化,提高了算法的效率. 为了测试该方法的有效性和可靠性,将路径规划系统安装到了播种机械上,通过对播种的测试发现,该方法实现了复杂地块播种的全区域覆盖,并且可以有效地躲避障碍物. 对3 种不同的算法进行对比测试发现:基于遗传算法的子
赵著行; 闵应骅; 等
1997-01-01
For different delay models,the concept of sensitization can be very different.Traditonal concepts of sensitization cannot precisely describe circuit behavior when the input vectors change very fast.Using Boolean process aporoach,this paper presents a new definition of sensitization for arbitrary input waveforms.By this new concept it is found that if the inputs of a combinational circuit can change at any time,and each gate's delay varies within an interval (bounded gate delay model),then every path,which is not necessarily a single topological path,is sensitizable.From the experimental results it can be seen that,all nonsensitizable paths for traditional concepts actually can propagate transitions along them for some input waveforms.However,specified time between input transitions(STBIT) and minimum permissible pulse width(ε）are two major factors to make some paths non-sensitizable.
赵晓侠; 鞠成恩
2016-01-01
In view of the problems of agricultural products in transportation, such as long time and easy to go bad, the distribution path of fruit and vegetable transport vehicles is reasonably planned.Based on the basic ant colony algorithm, an improved algorithm is proposed, which is suitable for solving path planning .The adaptive scheme is proposed to improve the ability of avoiding local optimal solution and the global conver-gence of the algorithm.The simulation results show that the improved algorithm is feasible and efficient .It can achieve the purpose of optimizing the route of transport vehicles, and provide theoretical basis for improving the efficiency of agricultural products transportation, reducing costs and improving income.%针对农产品在运输过程中运输时间长易变质等问题，合理规划果蔬运输车辆的配送路径。在基本蚁群算法的基础上，提出适合求解路径规划的改进型算法，同时提出了自适应调整的方案，提高跳出局部优解的能力以及算法的全局收敛性。仿真试验结果验证了改进型算法的可行性和高效性，从而达到运输车辆路径优化的目的，为提高农产品的运输效率、降低成本、提高收益提供了理论依据。
Portnoy, Sigal; Hersch, Ayelet; Sofer, Tal; Tresser, Sarit
2017-06-01
To test whether paired-play will induce longer path length and ranges of movement of the center of pressure (COP), which reflects on balance performance and stability, compared to solo-play and to test the difference in the path length and ranges of movement of the COP while playing the virtual reality (VR) game with the dominant hand compared to playing it with the nondominant hand. In this cross-sectional study 20 children (age 6.1 ± 0.7 years old) played an arm movement controlled VR game alone and with a peer while each of them stood on a pressure measuring pad to track the path length and ranges of movement of the COP. The total COP path was significantly higher during the paired-play (median 295.8 cm) compared to the COP path during the solo-play (median 189.2 cm). No significant differences were found in the reaction time and the mediolateral and anterior-posterior COP ranges between solo-play and paired-play. No significant differences were found between the parameters extracted during paired-play with the dominant or nondominant hand. Our findings imply that the paired-play is advantageous compared to solo-play since it induces a greater movement for the child, during which, higher COP velocities are reached that may contribute to improving the balance control of the child. Apart from the positive social benefits of paired-play, this positive effect on the COP path length is a noteworthy added value in the clinical setting when treating children with balance disorder.
Yuzhu Guo
2017-09-01
Full Text Available Measurement of the ground reaction forces (GRF during walking is typically limited to laboratory settings, and only short observations using wearable pressure insoles have been reported so far. In this study, a new proxy measurement method is proposed to estimate the vertical component of the GRF (vGRF from wearable accelerometer signals. The accelerations are used as the proxy variable. An orthogonal forward regression algorithm (OFR is employed to identify the dynamic relationships between the proxy variables and the measured vGRF using pressure-sensing insoles. The obtained model, which represents the connection between the proxy variable and the vGRF, is then used to predict the latter. The results have been validated using pressure insoles data collected from nine healthy individuals under two outdoor walking tasks in non-laboratory settings. The results show that the vGRFs can be reconstructed with high accuracy (with an average prediction error of less than 5.0% using only one wearable sensor mounted at the waist (L5, fifth lumbar vertebra. Proxy measures with different sensor positions are also discussed. Results show that the waist acceleration-based proxy measurement is more stable with less inter-task and inter-subject variability than the proxy measures based on forehead level accelerations. The proposed proxy measure provides a promising low-cost method for monitoring ground reaction forces in real-life settings and introduces a novel generic approach for replacing the direct determination of difficult to measure variables in many applications.
Research and Implementation of the Shortest Path Algorithm in Road Network Model%最短路径算法在路网模型中的研究与实现
董文科; 赵俊三; 杨哲; 陈雷
2016-01-01
传统的基于距离的路网模型以车辆通过的距离为权值计算最短路径，该模型无法满足基于时间的计算。要解决时间路网模型的设计问题，应该在基于距离的最短路径研究中，将动态的阻抗系数在计算机中表示出来，在算法实现过程中，解决如何在不同情况下调用不同的阻抗系数来选择相应情况下最合适的时间最短路径问题。%The traditional network model based on distance calculates the shortest path with the distance that the vehicle travels as the weights, and it can't meet the calculation based on time. In order to solve the design of the time road network model, we need to show the dynamic impedance coefficient in the computer in the shortest path based on distance. In the process of algorithm implementation, the problems of calling different resistance coefficients in different situation to select the most proper time-saving path in the corresponding cases shall be solved.
A Virus-Evolutionary Genetic Algorithm-Based Fast Air Vehicle Path Planning%基于病毒遗传算法的快速航迹规划方法
俞琪; 刘新; 周成平; 蔡超
2011-01-01
To enhance the real time planning ability of existing system , a fast path planning method based on virus-evolutionary genetic algorithm is proposed, the proposed method is aimed at improving the global step of a path planning method based on hierarchical strategy. The hierarchical planning method is used to efficiently handle path constraints by dividing the whole planning process into two steps : global planing and local planning. Employing a hierarchical strategy, this method may reduce the computation complexity. However it is well known that problems of premature and weakness in local searching exist in the genetic algorithm used in glohal planning. To overcome problems, the theory of virus-evolution is introduced into the global planning step. By designing a problem-specific representation of virus solutions and its virus infection operators ,the convergence performance and search efficiency are improved. Simulation results show that given the same path constraints our method can fast generate a satisfactory path.%为了提高现有航迹规划系统的实时规划能力,对基于分层策略的航迹规划方法中全局规划部分进行改进,提出了基于病毒遗传算法的快速规划方法.分层策略的航迹规划包括全局规划和局部规划,由于对不同性质的约束条件分阶段进行处理,该方法降低了航迹规划的计算复杂度.但全局规划采用的标准遗传算法仍存在早熟和局部收敛慢的问题.针对这些缺陷,采用病毒遗传算法进行改进.结合航迹规划的领域知识,给出了病毒种群的编码方法并设计了特定的病毒感染算子,使航迹寻优效率得以提高.仿真实验表明,在相同约束条件下,该方法能更快生成满足战术要求的航迹.
高晓静; 陈晓峰
2015-01-01
小型折翼变体无人飞行器（ Mini⁃Folding Wing Morphing Unmanned Aerial Vehicles， M⁃FMUAV）通常要在有限的巡飞航程中对指定目标区进行全面探测，为了有效地完成侦查任务，需要使规划的路径最短。规划的整条路径一般可分为直线段和转弯段，在直线段进行位置和偏差角控制，转弯段采用转弯控制，平滑路径使路径满足飞行性能。利用智能优化算法解决巡飞区最短路径问题，并从运算速度、收敛速度和路径最优率等方面对几种智能优化算法进行了比较，为折翼变体无人飞行器的推广应用提供了参考依据。%Minitype Folding Wing Morphing UAV ( M⁃FMUAV ) usually implements a comprehensive detection in limited loitering flight route. In order to complete effectively reconnaissance tasks, it is necessary to enable the shortest path planning. The planned path can be divided into straight segment and the turn segment.The position and deviation control can be used in straight seg⁃ment and the turn control can be used in turn segment. The smoothing path is implemented to meet the flight performance. This paper uses the intelligent optimization algorithm to solve the problem of shortest path in loitering flight area and compares several algorithms from the aspects of calculation speed,convergence rate and optimal path rate,which provides the reference for the popularization and application of M⁃FMUAV.
邹益民; 高阳; 高碧悦
2013-01-01
Obstacle avoidance of the mobile robot is a hot research field of mobile robot control.Face with the given mobile robot obstacle avoidance problems,the path planning of shortest and fastest were explored.For shortest path planning,a simplified path mesh modal was established.Thus,a candidate solution was obtained by treating the scene as twodimensional map composed of nodes and edges and using classical Dijkstra algorithm to seek the shortest route.For fastest path planning,by analyzing the moving speed of the mobile robot along arc-shaped route,the strict mathematical relationship between the robot moving time with transition arc center was deduced based on geometric method,thereafter to obtain the optimal movement path by means of MATLAB optimization function.The proposed algorithm can be extended to solve similar robot obstacle avoidance problems.%移动机器人的避障问题是移动机器人控制领域的研究热点.针对给定的移动机器人避障问题,探讨了最短路径及最短时间路径的路径规划问题.对于最短路径问题,建立了简化的路径网格模型,将其抽象为由节点及边构成的两维图,再使用经典的Dijkstra算法获得可行的最短路径.对于最短时间路径问题,通过分析移动机器人弯道运行的速度曲线,基于几何方法得出了移动时间与过渡圆弧圆心之间严格的数学关系,此后借助MATLAB优化函数获得最佳的移动路径.算法可为类似机器人避障问题的解决提供借鉴.
屈耀红; 肖自兵; 袁冬莉
2012-01-01
To shorten the flight time of UAV, we propose an algorithm of UAV flight path planning on-line under battle field threats. Sections 1 through 3 of the full paper explain our method of flight path planning mentioned in the title, which we believe is better than the existing ones and whose core consists of: "UAV estimates the wind field information on-line using our proposed method during the flight. Then the choice of the extend nodes in A * search algorithm is considered according to the wind direction and the cost function is designed as the flight time". Section 3 is entitled " Method of UAV Flight Path Planning On-Line in Wind Field Using Improved A * Searching Algorithm"; for convenience, we divide it into four sub-sections: 3.1, 3.2, 3.3 and 3.4. Simulation results, presented in Figs. 4 and 5 and Table 2, and their analysis show preliminarily that the flight time is indeed less than that obtained with the traditional method based on the length of the flight path.%风场是影响无人机飞行速度的一个重要因素.为了缩短任务执行中的飞行时间,考虑战场环境存在外界威胁情况,提出了一种利用组合导航在线估计风场信息的无人机航迹规划方法.该方法基于飞行时间为代价,利用改进的A*搜索算法对航迹进行顺风搜索,从而实现最短理想耗时的航迹规划.计算机仿真结果表明,与传统的最短航迹长度规划方法相比,无人机按该方法规划的航迹飞行时,理想耗时最少.
基于改进A＊算法的室内移动机器人路径规划%Indoor mobile-robot path planning based on an improved A ＊ algorithm
王殿君
2012-01-01
针对移动机器人在室内定位的特点，在结构化环境下，开发了机器人路径规划系统。在阐述了全局地图构建方法基础上，根据移动机器入的实际运行环境采用栅格法构建了环境地图。利用A。算法进行初步路径规划，其不足之处是路径规划数据中包含了所有规划点的坐标，冗余点较多，且移动机器人无法在拐点处调整自身姿态。针对这些不足，提出了能够计算出拐点、旋转方向及旋转最小角度的A’路径规划改进算法并进行了实验。移动机器人定位实验结果表明：利用改进后的A。路径规划算法不仅简化了路径，而且在拐点处移动机器人能够调整自身姿态，可以较好地满足室内移动机器人全自主运动的要求。%An indoor mobile robot path planning system was developed under the structured environment in consideration of the characteristics of mobile-robot technology on indoor localization. Based on the global map building methods, the environment map was built in the robot＇s actual environment using the grid method. The path preliminarily planned by A＊ algorithm contained all planning point coordinates, which caused more redundant points with the robot not being able to adjust its posture at the inflection point. An improved A＊ algorithm, which can calculate the inflection point, rotation direction and the minimum rotation angles, was then proposed against the shortage of the path planning. Mobile-robot positioning tests show that the improved algorithm not only simplifies the path, but also adjusts the robot＇s posture at the inflection point, which can meet the requirements of robot autonomous movement,
陈文强; 顾玉磊
2013-01-01
本文构建了物流配送网络中货物时间价值相关的最小配送费用路径模型，并研究了其算法。模型把整个配送过程分为运输过程和装卸过程，并且考虑了由于运输过程和装卸过程时间延迟造成的货物价值损失，这也是和其它类似成本路径模型最大的区别。该模型算法可以利用计算机自动完成，不受物流配送网络大小和节点的限制，并保证算法的正确性。%A time-value-dependent logistics minimum cost admeasure path model for a logistics network was constructed, and its algorithm was studied. The model divided a delivery process into two parts, that is, the transportation and the loading and unloading processes, meanwhile, the lost due to the time delays in the two processes was considered. This is the great difference from the other models. The efficient implementation was designed that allowed path computating on a realistic large-scale network without limiting the transport node number. The correctness of the algorithm was gurrantied.
Improved transfer logic of two-path algorithm for acoustic echo cancellation%基于声回波抵消两路算法的改进更新逻辑
王飞; 刘畅
2012-01-01
the two-path algorithm in the acoustic echo cancellation ia widely applied to avoid the false adaptation problem during the double-talk situation. This paper proposed an improved transfer logic for the two-path algorithm; based on the comparison of the Echo Return Los9 Enhancement (ERLE) for the fillers, the improved transfer logic decided whether to permit filter update. Furthermore, the improved transfer logic managed to detect the double-talk and avoid the false filter update, improved the convergence speed and allowed the reduction of the memory requirement and computational complexity. The simulation results show the improved performance of the proposed solution.%声回波抵消两路算法被广泛用来检测系统双向通话；基于声回波抵消两路算法,提出了一种改进的控制更新逻辑.此更新逻辑通过比较滤波器的回波返回损失(ERLE),判断是否对滤波器进行更新.此改进更新逻辑能正确检测系统双向通话,避免滤波器的错误更新,并提高两路算法的收敛速度,减小存储器资源和计算量.仿真结果证实了此更新逻辑的有效性.
Vanícek, Jirí
2011-01-01
Nuclear tunneling and other nuclear quantum effects have been shown to play a significant role in molecules as large as enzymes even at physiological temperatures. I discuss how these quantum phenomena can be accounted for rigorously using Feynman path integrals in calculations of the equilibrium and kinetic isotope effects as well as of the temperature dependence of the rate constant. Because these calculations are extremely computationally demanding, special attention is devoted to increasing the computational efficiency by orders of magnitude by employing efficient path integral estimators.
Hu, T C
2002-01-01
Newly enlarged, updated second edition of a valuable text presents algorithms for shortest paths, maximum flows, dynamic programming and backtracking. Also discusses binary trees, heuristic and near optimums, matrix multiplication, and NP-complete problems. 153 black-and-white illus. 23 tables.Newly enlarged, updated second edition of a valuable, widely used text presents algorithms for shortest paths, maximum flows, dynamic programming and backtracking. Also discussed are binary trees, heuristic and near optimums, matrix multiplication, and NP-complete problems. New to this edition: Chapter 9
孙玲芳; 候志鲁; 许锋; 周家波
2016-01-01
The paper proposes an energy-saving multi-path adaptive algorithm based on random network coding in wireless sensor networks (RNC-ESMP). First of all, This algorithm considers the nodesˊenergy, let the data packets transmitted on the paths which have least energy consumption during data transferring. Second, considering the decoding probability of the sink nodes as the feedback factor, the algorithm builds a feedback mechanism from the sink nodes to the source nodes to make self-adaptive impossible. Then the algorithm proposes the encoding options and probability of the intermediate nodes so as to reduce the complexity of encoding. At last, it builds the platform on MATLAB to simulate the algorithm. The results of the experiment shows that this algorithm not only can reduce the average energy consumption of networks efficiently but also can extend the networksˊlife-time.%提出一种多路径的无线传感器网络（WSN）自适应节能算法，该算法的实现基于随机网络编码（RNC－ESMP）。其基本思想是：首先，该算法以WSN节点能量为考量，将数据经由节点能量最多的路径传输；其次，以目的节点解码成功率为反馈因子，构建目的节点到源节点的反馈机制，实现自适应；再次，选择合适的编码策略对数据包进行编码。最后在MATLAB环境下搭建仿真平台进行模拟仿真。实验结果表明，相比于传统的多路径算法，RNC－ESMP算法能够有效降低网络平均能耗，延长网络生命周期。
Hu, Hao; Lu, Zhenyu; Parks, Jerry M.; Burger, Steven K.; Yang, Weitao
2008-01-01
To accurately determine the reaction path and its energetics for enzymatic and solution-phase reactions, we present a sequential sampling and optimization approach that greatly enhances the efficiency of the ab initio quantum mechanics/molecular mechanics minimum free-energy path (QM/MM-MFEP) method. In the QM/MM-MFEP method, the thermodynamics of a complex reaction system is described by the potential of mean force (PMF) surface of the quantum mechanical (QM) subsystem with a small number of degrees of freedom, somewhat like describing a reaction process in the gas phase. The main computational cost of the QM/MM-MFEP method comes from the statistical sampling of conformations of the molecular mechanical (MM) subsystem required for the calculation of the QM PMF and its gradient. In our new sequential sampling and optimization approach, we aim to reduce the amount of MM sampling while still retaining the accuracy of the results by first carrying out MM phase-space sampling and then optimizing the QM subsystem in the fixed-size ensemble of MM conformations. The resulting QM optimized structures are then used to obtain more accurate sampling of the MM subsystem. This process of sequential MM sampling and QM optimization is iterated until convergence. The use of a fixed-size, finite MM conformational ensemble enables the precise evaluation of the QM potential of mean force and its gradient within the ensemble, thus circumventing the challenges associated with statistical averaging and significantly speeding up the convergence of the optimization process. To further improve the accuracy of the QM/MM-MFEP method, the reaction path potential method developed by Lu and Yang [Z. Lu and W. Yang, J. Chem. Phys. 121, 89 (2004)] is employed to describe the QM/MM electrostatic interactions in an approximate yet accurate way with a computational cost that is comparable to classical MM simulations. The new method was successfully applied to two example reaction processes, the
Aircraft Path Planning under Adverse Weather Conditions
Xie Z.
2016-01-01
Full Text Available In recent years, flight safety is still one of the main issues for all airlines. En route civil airplanes may encounter adverse weather conditions. Some fatal airplane accidents happened because of the weather disturbance. Moreover, we should also design path to avoid the prohibited area. Therefore a good path planning algorithm plays an increasingly important role in air traffic management. An efficient path planning algorithm can help the plane to avoid severe weather conditions, restricted areas and moving obstacles to ensure the safety of the cabin crews and passengers. Here, we build our algorithm based on the A* search algorithm. Moreover, our algorithm can also find the path with least energy costs. As a result, our algorithm can improve the safety operation of the airplanes and reduce the workload of pilots and air traffic controllers.
Madsen, Mogens Ove
Begrebet Path Dependence blev oprindelig udviklet inden for New Institutionel Economics af bl.a. David, Arthur og North. Begrebet har spredt sig vidt i samfundsvidenskaberne og undergået en udvikling. Dette paper propagerer for at der er sket så en så omfattende udvikling af begrebet, at man nu kan...... tale om 1. og 2. generation af Path Dependence begrebet. Den nyeste udvikling af begrebet har relevans for metodologi-diskusionerne i relation til Keynes...
Feasible Path Planning for Autonomous Vehicles
Vu Trieu Minh
2014-01-01
Full Text Available The objective of this paper is to find feasible path planning algorithms for nonholonomic vehicles including flatness, polynomial, and symmetric polynomial trajectories subject to the real vehicle dynamical constraints. Performances of these path planning methods are simulated and compared to evaluate the more realistic and smoother generated trajectories. Results show that the symmetric polynomial algorithm provides the smoothest trajectory. Therefore, this algorithm is recommended for the development of an automatic control for autonomous vehicles.
彭志红; 孙琳; 陈杰
2012-01-01
为了解决无人机在部分未知敌对环境中的低空突防航迹规划问题，提出了一种改进的差分进化算法．该算法的进化模型采用冯·诺伊曼拓扑结构，并对其进行拓展，使种群在进化初期保持多样性，避免进化早期陷入局部最优，而进化后期加快收敛速度．该算法改进了差分进化算子中的变异操作，从而加快算法的收敛速度，快速找到多目标优化问题的最优解；同时，采用将绝对笛卡儿坐标和相对极坐标相结合的编码方式以提高搜索效率．将该算法用于无人机在线航迹规划仿真实验，并和未改进的算法结果作比较，验证了该算法的有效性．%An improved differential evolution algorithm was proposed for solving the online path planning problem of unmanned aerial vehicle （UAV） low-altitude penetration in partially known hostile environments. The algorithm adopts von Neumann topology and improves its structure to maintain the diversity of the population, prevent the population from falling into local optima in the early evolution and speed up the convergence rate in the later evolution as well. The mutation operator of differential evolution is improved to speed up the convergence rate of the algorithm, so that the optimal solution of the multi-objective optimization problem can be found quickly; the coding method combined the absolute Cartesian coordinates with the relative polar coordinates is used to improve the searching efficiency. The simulation experiment of online path planning for UAV low-altitude penetration shows that the proposed algorithm has a better performance than the unimproved differential evolution algorithm.
徐利超; 张世武
2013-01-01
In order to solve the problem of finding the shortest path to a specific target for robots,this paper presented a novel path planning method based on improved ant colony algorithm.The method made the ant have local path thinking ability by endowing it with sense of direction similar to human beings.The thought of combining deterministic selection and random selection,as well as adaptive adjustment strategy of deterministic selection probability and pheromone evaporation coefficient,were also adopted.These means greatly improved the global search ability of the ant colony algorithm and accelerated the search speed,as well as improved its ability to find optimal solution.In the simulation environment based on grid map,under different conditions of problem size and obstacle distribution,the method could always find the optimization results and meet the speed requirement for real-time path planning.%针对寻找机器人在障碍环境下到达特定目标最短路径问题,提出一种基于改进蚁群算法的路径规划方法.该算法通过赋予蚂蚁类似于人的方向感,使其具备局部路径思考能力,同时在蚁群算法中引入确定性选择和随机性选择相结合的方法,以及确定性选择概率和信息素挥发系数自适应调整策略,极大地改善了蚁群算法的全局搜索能力和搜索速度,并且显著地提高了算法寻找最优解的能力.在基于栅格地图的仿真测试条件下,该方法在不同问题规模和障碍条件下,均能达到很好的优化结果,并且满足实时路径规划的搜索速度要求.
空中机器人路径规划算法研究%Research on the Air Robot Path Planning Algorithm
林文
2015-01-01
Air robot can complete the assigned task in the boring, bad and dangerous field without human intervention. In recent years, it has been more and more widely used in the military and civilian aspects. According to the distribution of all sorts of threats on the battlefield, this paper constructs Voronoi diagram, combining with specific information of different kinds of threats, calculat-ing the path cost of Voronoi diagram. Finally, with the calculation and correction, it concludes the optimal flight path.%空中机器人能够在枯燥的任务领域、恶劣及危险的环境任务领域不需人为干预地完成指定任务，近年来在军事和民用两个方面得到越来越广泛应用。本文根据战场上各种威胁的分布情况，构建了Voronoi图，结合不同威胁的具体信息，计算Voronoi图中路径段的代价，最后通过计算和修正，得出了空中机器人的飞行最优路径。
黄海燕; 姚秀美; 朱海燕; 陈亚江
2016-01-01
Based on the Hamilton principle,a numerical algorithm associated with Lagrange multiplier method for the classical motion path problem is proposed. Different from traditional variational method,the present algorithm transforms the classical motion path problem into the conditional extremum problem with respect to the motion equation. By utilizing this algorithm,numerical solutions to motion path problems in one-dimensional gravitation potential and one-dimensional elastic potential are obtained and compared with the corresponding analytical results,respectively. Such two examples can be used as practical and interesting teaching cases for the relevant curriculums,e.g. Mechanics in college physics,Hamilton principle in theoretical mechanics and numerical calculation in computational mathematics. These examples are helpful for students to understand the Hamilton principle more deeply,and improve the ability of applying the knowledge in the fields of physics,mathematics, and computer science.%基于哈密顿原理，提出经典运动路径问题的拉格朗日乘数数值算法。与传统的变分方法不同，该算法将经典运动路径问题改写为关于路径方程的条件极值问题。利用该算法得到了一维重力势中的运动路径和一维弹性势中的运动路径的数值解，并与各自的解析解作了比较分析。这2个例子可以作为大学物理力学、理论力学哈密顿原理以及计算数学数值计算等相关课程内容实用教学案例，其有助于学生更深刻地理解哈密顿原理，提高综合应用物理、数学、计算机科学等知识的能力。
Distributed Power Control Routing Algorithm Based on Shortest Path Tree%基于最短路径树的分布式功率控制路由算法
陈友荣; 任条娟; 刘半藤; 葛灵晓
2012-01-01
When the nodes can not get the distance to neighbor nodes, to solve the problem that node consumes excessive energy,fails prematurely and leads to reduce the network lifetime,distributed power control routing algorithm based on shortest path tree( DPCRA_SPT) is proposed. Considering energy for transmitting data and neighbor nodes' residual energy, the new weight function and linear power attenuation model are introduced. Finally distributed asynchronous Bellman-Ford algorithm is used to construct the shortest path tree. All nodes transmit data along the shortest path tree to Sink node. Simulation results show that in the densely distributed wireless sensor networks, by adjusting the parameters, DPCRA_SPT can prolong network lifetime and remain energy consumption at a lower level. Under certain conditions,DPCRA_SPT outperforms Ratio_w_FTP,BFFTP,BFSAM and BFPAM algorithms.%当节点不能获知与邻居节点的距离时,为解决节点能量消耗过快而过早失效,从而减少网络生存时间的问题,提出基于最短路径树的分布式功率控制路由算法( DPCRA_SPT).该算法综合考虑网络中节点间传输数据的能耗和邻居节点的剩余能量,引入新的权值函数和功率线性衰减模型.运用分布式非同步Bellman-Ford算法构建最短路径树,所有节点沿着最短路径树将数据汇集到Sink节点.仿真结果表明:在密集分布的无线传感网中,通过调整参数,DPCRA_STT算法可以延长网络生存时间,将能耗保持在较低的水平.在一定的条件下,DPCRA_SPT算法比Ratio_w_FTP、BFFTP、BFSAM、BFPAM算法更优.
Fritz, Sean
2015-01-01
In this study, an interplanetary space flight mission design is established to obtain the minimum \\(\\Delta V\\) required for a rendezvous and sample return mission from an asteroid. Given the initial (observed) conditions of an asteroid, a (robust) genetic algorithm is implemented to determine the optimal choice of \\(\\Delta V\\) required for the rendezvous. Robustness of the optimum solution is demonstrated through incorporated bounded-uncertainties in the outbound \\(\\Delta V\\) maneuver via genetic fitness function. The improved algorithm results in a solution with improved robustness and reduced sensitivity to propulsive errors in the outbound maneuver. This is achieved over a solution optimized solely on \\(\\Delta V\\), while keeping the increase in \\(\\Delta V\\) to a minimum, as desired. Outcomes of the analysis provide significant results in terms of improved robustness in asteroid rendezvous missions.
Logistics Distribution Shortest Path Based on Dijkstra Algorithm%基于Dijkstra算法的物流配送最短路径算法研究
王华
2011-01-01
根据城市交通网络的特点,运用结点一弧段一有向线结构描述交通网络,利用动态分段技术建立了基于ARC-GIS的配货网络数据库,充分考虑了配货路线短、用时少、费用低的特点,运用Dijkstra算法实现物流配送最短路径算法,提高了城市物流配送的便利性和高效性.%Establish a logistics distribution database based on ArcGIS according to the characteristics of urban traffic network, using node-arc description of transport, achieve logistics distribution shortest path based on dijkstra considering of less rount/time/cost, improve the convenience of ueban logistics distribution efficiency.
A Task Duplication Algorithm Based on Dynamic Critical Path and Edge-Zeroing%基于动态关键路径与边消除的任务复制分配算法
尤涛; 杨凯; 杜承烈; 钟冬; 朱怡安
2013-01-01
当前的分布式任务调度算法中，都存在无法得到调度最优解、无法最小化处理器资源的问题。针对并行与分布式系统中相关任务的静态调度问题，以最小化调度长度为主要目标，以减少资源数为次要目标，提出了一种基于动态关键路径与边消除的任务复制算法。该算法依据调度长度不增加原则，发展了子节点无约束复制的调度长度不增加定理、子结点带约束复制的调度长度不增加原则、动态关键路径聚簇的调度长度不增加原则，从而缩短了任务的执行时间和占用资源的个数。整个算法流程对任务计算时间与任务间通信时间未做任何限制。通过与相关工作的比较可以看出：DDE算法在调度长度与处理器使用数目上优于其他同类算法。%Task scheduling is critical for a parallel and distributed system .The task duplication and scheduling al-gorithm and other typical algorithms cannot obtain the optimal solutions for scheduling length even under optimal conditions.Moreover, they are constrained by the node selection scope and node execution time scope when alloca-ting nodes, being unable to minimize the number of processors required by the algorithms .To carry out the static scheduling of the related tasks in the parallel and distributed system , this paper proposes the task in the parallel and distributed system , this paper proposes the task duplication algorithm based on dynamic critical path and edge -zeroing , whose main objective is to reduce the number of resources .The algorithm develops the principles that the scheduling length of sub-nodes that are duplicated with no constraints should not increase , that the scheduling length of sub-nodes that are duplicated with constraints should not increase and the scheduling length of dynamic critical path clustering should not increase , thus reducing the task execution time and the number of resources used . The algorithm
王超杰; 任建文; 徐伟男; 李越佳
2016-01-01
For the load power loss due to power grid failure or equipment maintenance,it has now become an essential function of looking for a power supply path for the power lost load in a lot of power grid analysis software.The grid can be divided into several electric islands through the topological analysis program.The traditional searching algorithm for island restoration of power supply path based on the tree search method is inadequate in path searching.Inspired by the Internet routing protocol algorithm,all kinds of electric islands are regarded as routers while a kind of search algorithm based on distance vector is put forward.Through the formation of initial routing tables and routing table update processing,the entire network routing table of each island is eventually obtained,through which all the possible power supply paths of power losing electric islands in conformity with dispatching schedules can be obtained.By using the optimal power flow of the interior point method,the feasibility of power solutions is verified as is the algorithm effectiveness on an IEEE 14-bus standard test system.%由于电网故障或设备检修造成负荷失电，为失电负荷寻找供电路径成为目前许多电网分析软件的必备功能。通过拓扑分析程序将电网划分为若干电气岛，传统的根据树搜索法的孤岛恢复供电路径搜索算法，在路径的搜索上存在不足。文中受因特网路由选择协议算法的启发，将各类电气岛看成路由器，提出一种基于距离向量的搜索算法，通过对各电气岛初始路由表的形成和对路由表的更新处理，最终获得电气岛的全网路由表，通过该路由表可以得到所有可能并且符合调度规程的失电孤岛供电路径。利用内点法最优潮流对搜索得到的供电方案进行可行性验证。以 IEEE 14节点标准测试系统为例，验证了该算法的可行性。
祁悦; 赵洋; 杨帆
2014-01-01
This paper focuses on how to generate a 3D navmesh and implement high-speed path-finding for autonomous characters in 3D games. We proposed a hierarchical solution to meet the requirement. Firstly, a navmesh is used to divide the state space. Then we used the A* algorithm to find the path of the navmesh with making use of binary heaps to optimize the OPEN table. We also proposed a method of corner points to find the final path. At last, we used ray transmission to detect the dynamic obstacles. The initial experimentation shows that our solution is able to be used in some 3D games.%以3D游戏中智能体的路径规划为研究背景，对于如何生成3D游戏的地形网格以及如何进行高速、准确的路径规划进行了研究。提出了一种分层的解决方案，首先通过建立导航网格划分状态空间；接着使用引入地形估价因子的算法进行网格寻路，并通过拐角点法生成路径，同时对算法的OPEN表进行了二叉堆的优化；最后介绍了基于射线透射的局部算法对动态障碍物的处理。实验分析表明该算法的有效性。
Karnøe, Peter; Garud, Raghu
2012-01-01
This paper employs path creation as a lens to follow the emergence of the Danish wind turbine cluster. Supplier competencies, regulations, user preferences and a market for wind power did not pre-exist; all had to emerge in a tranformative manner involving multiple actors and artefacts. Competenc......This paper employs path creation as a lens to follow the emergence of the Danish wind turbine cluster. Supplier competencies, regulations, user preferences and a market for wind power did not pre-exist; all had to emerge in a tranformative manner involving multiple actors and artefacts....... Competencies emerged through processes and mechanisms such as co-creation that implicated multiple learning processes. The process was not an orderly linear one as emergent contingencies influenced the learning processes. An implication is that public policy to catalyse clusters cannot be based...
基于化学反应算法的系统辨识%SYSTEM IDENTIFICATION USING CHEMICAL REACTION OPTIMISATION ALGORITHMS
何兴华; 周永华
2016-01-01
化学反应优化算法起源于化学反应过程中的能量变化的模拟。提出一种利用化学反应优化算法对系统进行辨识的方法。即通过建立连续系统和离散系统的传递函数结构模型，首先将系统辨识问题转化为数学上求取相关参数的全局最优估计问题，然后利用化学反应优化算法对该问题进行求解。最后给出仿真实例，并且与遗传算法进行了比较，结果表明该方法具有较好的效果，且兼具速度快、精度高等特点。%Chemical reaction optimisation algorithms are derived from simulating the energy changes in chemical reaction process.This paper shows how the chemical reaction optimisation algorithms be applied for system identification.That is,by building the transfer function structural model of continuous and discrete systems,first we convert the problem of system identification to a global optimal estimation problem of seeking the correlated parameters in mathematics,then we use chemical reaction optimisation algorithms to solve the problem.In end of the paper,we give some simulation examples and compare them with genetic algorithms.Results prove that our method has better effect,and has the features of both high speed and accuracy.
Formal language constrained path problems
Barrett, C.; Jacob, R.; Marathe, M.
1997-07-08
In many path finding problems arising in practice, certain patterns of edge/vertex labels in the labeled graph being traversed are allowed/preferred, while others are disallowed. Motivated by such applications as intermodal transportation planning, the authors investigate the complexity of finding feasible paths in a labeled network, where the mode choice for each traveler is specified by a formal language. The main contributions of this paper include the following: (1) the authors show that the problem of finding a shortest path between a source and destination for a traveler whose mode choice is specified as a context free language is solvable efficiently in polynomial time, when the mode choice is specified as a regular language they provide algorithms with improved space and time bounds; (2) in contrast, they show that the problem of finding simple paths between a source and a given destination is NP-hard, even when restricted to very simple regular expressions and/or very simple graphs; (3) for the class of treewidth bounded graphs, they show that (i) the problem of finding a regular language constrained simple path between source and a destination is solvable in polynomial time and (ii) the extension to finding context free language constrained simple paths is NP-complete. Several extensions of these results are presented in the context of finding shortest paths with additional constraints. These results significantly extend the results in [MW95]. As a corollary of the results, they obtain a polynomial time algorithm for the BEST k-SIMILAR PATH problem studied in [SJB97]. The previous best algorithm was given by [SJB97] and takes exponential time in the worst case.
王浚岭
2005-01-01
In this paper a high-order feasible interior point algorithm for a class of nonmonotonic (P-matrix) linear complementary problem based on large neighborhoods of central path is presented and its iteration complexity is discussed.These algorithms are implicitly associated with a large neighborhood whose size may depend on the dimension of the problems. The complexity of these algorithms bound depends on the size of the neighborhood. It is well known that the complexity of large-step algorithms is greater than that of short- step ones. By using high-order power series (hence the name high-order algorithms), the iteration complexity can be reduced. We show that the upper bound of complexity for our high-order algorithms is equal to that for short-step algorithms.
UAV On-line Path Re-planning Based on Threats Evaluation Improved Algorithm%基于改进威胁代价的无人机路径在线重规划
高晓光; 魏小丰; 郑景嵩
2012-01-01
针对路径在线重规划中的威胁代价评估问题,提出了基于最大综合拦截概率的在线威胁代价评估改进算法.在该算法中,以已有威胁代价评估模型为基础,给出不同信息支持条件下的“瞬时跟踪概率”计算模块,进而引入“连续跟踪概率”概念,并结合“杀伤概率”得到“拦截概率”概念模块.在此基础上,提出“最大拦截概率”概念,以此作为单个主动威胁作用下的在线威胁代价评估标准,最后将其拓展到“最大综合拦截概率”作为多个主动威胁作用下的在线威胁代价评估标准.在此基础上,结合MPC算法给出路径在线重规划的模型.通过仿真结果对比,说明上述模型的合理性和算法的有效性.%An improved threats evaluation algorithm is proposed for the on-line path re-planning of Unmanned Aerial Vehicle (UAV). Based on the existing threat evaluation model, instantaneous radar tracking probability computation modules on condition of different information is given to calculate the continuous radar tracking probability. Kill probability on condition of continuous radar tracking is proposed. As a result, interception probability and maximum interception probability are figured out to provide an evaluation criterion for a single threat, while the maximum integrated interception probability is consider as the criterion for multiple threats-Based on the threats evaluation improved algorithm, Model Predictive Control (MPC) is adopted to implement the on-line path planning. Simulation results have shown that the model is more intelligent and the approach is more effective in path re-planning.
Rock climbing: A local-global algorithm to compute minimum energy and minimum free energy pathways
Templeton, Clark; Chen, Szu-Hua; Fathizadeh, Arman; Elber, Ron
2017-10-01
The calculation of minimum energy or minimum free energy paths is an important step in the quantitative and qualitative studies of chemical and physical processes. The computations of these coordinates present a significant challenge and have attracted considerable theoretical and computational interest. Here we present a new local-global approach to study reaction coordinates, based on a gradual optimization of an action. Like other global algorithms, it provides a path between known reactants and products, but it uses a local algorithm to extend the current path in small steps. The local-global approach does not require an initial guess to the path, a major challenge for global pathway finders. Finally, it provides an exact answer (the steepest descent path) at the end of the calculations. Numerical examples are provided for the Mueller potential and for a conformational transition in a solvated ring system.
孙小雷; 齐乃明; 董程; 姚蔚然
2015-01-01
针对无人机协同控制问题，提出一种多无人机任务分配与航迹规划的整体控制架构。将威胁和障碍区域考虑为合理的多边形模型，使用改进的 A*算法规划出两个航迹点之间的最短路径。并利用该路径航程作为任务分配过程全局目标函数的输入，采用与协同系统相匹配的粒子结构进行改进粒子群优化（particle swarm optimization， PSO）任务分配迭代寻优。根据分配结果并考虑无人机性能约束，基于 B-spline 法平滑路径组合，生成飞行航迹。仿真结果表明，算法在保证计算速度和收敛性能的同时，能够产生合理的任务分配结果和无人机的可飞行航迹。%An integrating framework of task assignment and path planning for multiple unmanned aerial ve-hicles (UAVs)is presented.To avoid the obstacles area which is represented as polygon,the shortest path seg-ment between UAVs and task can be found by the improved A* algorithm.According to this segment distance, the global objective function of task allocation is modeled.The assignment process is determined by improved particle swarm optimization (PSO),which particle structure matches the cooperative system.The B-spline method is adopted to smooth the flight path,which consists of path segments of the assignment.Numerical re-sults demonstrate that the proposed method can achieve the optimal task assignment solution and best flight routes.
郭蕴华; 王晓宗
2016-01-01
An improved algorithm based on the quantum-behaved particle swarm optimization is proposed for UAV path planning problem .The updated position of the particle is adaptively adjusted by the distance between the particle and the local at -tractor point and the distance between the particle and the boundary of the feasible region .Simulation results show that the im-proved QPSO algorithm can get the track with higher quality , and its convergence is better .%针对无人机路径规划算法收敛速度慢、易陷入局部最优等问题,提出一种改进的量子粒子群算法. 该算法根据粒子与局部吸引点和可行解边界的距离动态的修正粒子更新位置,改善了算法的全局寻优能力和收敛性能. 仿真实验表明所提出的改进QPSO算法比其他已有算法可以得到更高质量的航迹,并且其收敛性较好.
Supply Chain Network Path Based On Floyd Algorithm Research%基于Floyd算法的供应链网络路径研究
楼振凯
2014-01-01
21世纪的竞争不是企业与企业之间的竞争，而是供应链之间的竞争。运输系统是供应链中一个重要的子系统，运输路径的选择是否合理直接影响供应链的运作成本、速度和效益。文中考虑在拉动式生产的背景下，当销售商提出需求订单的时候，最快的选择相应的制造商和配送中心，使得供应链的总运输成本最小化的问题，利用floyd算法研究三级供应链的运作模式，理论证明其可行性，并通过算例分析验证了此优化算法使得供应链运输成本最小化。%Competition in the 21st century is not the competition between enterprises and enterprises,but the competition between supply chains.Transportation system is an important subsystem in the supply chain,transportation route choice is reasonable direct impact on the performance of a supply chain cost,speed and efficiency.Considered in this paper under the background of pull production,when the seller put forward demand order,select the manufacturer and distribution center of the fastest,minimize the total transportation costs of the supply chain problems,Floyd algorithm was used to study the three levels of the supply chain operation model and theory to prove its feasibility,and the optimization algorithm is verified by an example analysis makes the supply chain to minimize transportation costs.
周波; 钱来; 孟正大; 戴先中
2011-01-01
The common task planning problem of multiple discrete paths integration for industrial robots was studied in this paper. By transformed into a nonsymmetrical Hamiltonian graph, the problem was modeled and solved in an unified framework of open generalized traveling salesman problem (GTSP)· And the corresponding cost matrix and objective function were also created. A new genetic algorithm with multiple chromosome structures was proposed to find the global optimal solution. The sequences and directions of paths were expressed by different chromosomes respectively to improve the search ability and convergence speed of the algorithm, as well as the drawback of falling to local extreme. Simulation results with comparison to traditional genetic algorithm for TSP show the effectiveness and feasibility of the proposed method.%针对工业机器人应用中常见的一类涉及离散多路径组合优化的任务规划问题进行了研究,通过将其转化为非对称哈密顿图表示,采用统一的开环式广义旅行商问题的框架进行建模和求解,由此建立了相应的代价矩阵和目标函数,在此基础上提出了一种新的具有多染色体结构的遗传算法来寻找问题的全局最优解.通过采用不同的染色体分别表示路径的顺序和方向,改进了传统遗传算法容易陷入局部最优值的缺陷,提高了算法的搜索能力和收敛速度.仿真研究中通过与传统TSP问题遗传求解算法的比较,证明了本方法的有效性和可行性.
Generalized Ensemble Sampling of Enzyme Reaction Free Energy Pathways
Wu, Dongsheng; Fajer, Mikolai I.; Cao, Liaoran; Cheng, Xiaolin; Yang, Wei
2016-01-01
Free energy path sampling plays an essential role in computational understanding of chemical reactions, particularly those occurring in enzymatic environments. Among a variety of molecular dynamics simulation approaches, the generalized ensemble sampling strategy is uniquely attractive for the fact that it not only can enhance the sampling of rare chemical events but also can naturally ensure consistent exploration of environmental degrees of freedom. In this review, we plan to provide a tutorial-like tour on an emerging topic: generalized ensemble sampling of enzyme reaction free energy path. The discussion is largely focused on our own studies, particularly ones based on the metadynamics free energy sampling method and the on-the-path random walk path sampling method. We hope that this mini presentation will provide interested practitioners some meaningful guidance for future algorithm formulation and application study. PMID:27498634
Strategic Team AI Path Plans: Probabilistic Pathfinding
Tng C. H. John
2008-01-01
Full Text Available This paper proposes a novel method to generate strategic team AI pathfinding plans for computer games and simulations using probabilistic pathfinding. This method is inspired by genetic algorithms (Russell and Norvig, 2002, in that, a fitness function is used to test the quality of the path plans. The method generates high-quality path plans by eliminating the low-quality ones. The path plans are generated by probabilistic pathfinding, and the elimination is done by a fitness test of the path plans. This path plan generation method has the ability to generate variation or different high-quality paths, which is desired for games to increase replay values. This work is an extension of our earlier work on team AI: probabilistic pathfinding (John et al., 2006. We explore ways to combine probabilistic pathfinding and genetic algorithm to create a new method to generate strategic team AI pathfinding plans.
An adaptive multi-level simulation algorithm for stochastic biological systems.
Lester, C; Yates, C A; Giles, M B; Baker, R E
2015-01-14
Discrete-state, continuous-time Markov models are widely used in the modeling of biochemical reaction networks. Their complexity often precludes analytic solution, and we rely on stochastic simulation algorithms (SSA) to estimate system statistics. The Gillespie algorithm is exact, but computationally costly as it simulates every single reaction. As such, approximate stochastic simulation algorithms such as the tau-leap algorithm are often used. Potentially computationally more efficient, the system statistics generated suffer from significant bias unless tau is relatively small, in which case the computational time can be comparable to that of the Gillespie algorithm. The multi-level method [Anderson and Higham, "Multi-level Monte Carlo for continuous time Markov chains, with applications in biochemical kinetics," SIAM Multiscale Model. Simul. 10(1), 146-179 (2012)] tackles this problem. A base estimator is computed using many (cheap) sample paths at low accuracy. The bias inherent in this estimator is then reduced using a number of corrections. Each correction term is estimated using a collection of paired sample paths where one path of each pair is generated at a higher accuracy compared to the other (and so more expensive). By sharing random variables between these paired paths, the variance of each correction estimator can be reduced. This renders the multi-level method very efficient as only a relatively small number of paired paths are required to calculate each correction term. In the original multi-level method, each sample path is simulated using the tau-leap algorithm with a fixed value of τ. This approach can result in poor performance when the reaction activity of a system changes substantially over the timescale of interest. By introducing a novel adaptive time-stepping approach where τ is chosen according to the stochastic behaviour of each sample path, we extend the applicability of the multi-level method to such cases. We demonstrate the
An adaptive multi-level simulation algorithm for stochastic biological systems
Lester, C., E-mail: lesterc@maths.ox.ac.uk; Giles, M. B.; Baker, R. E. [Mathematical Institute, Woodstock Road, Oxford OX2 6GG (United Kingdom); Yates, C. A. [Department of Mathematical Sciences, University of Bath, Bath BA2 7AY (United Kingdom)
2015-01-14
Discrete-state, continuous-time Markov models are widely used in the modeling of biochemical reaction networks. Their complexity often precludes analytic solution, and we rely on stochastic simulation algorithms (SSA) to estimate system statistics. The Gillespie algorithm is exact, but computationally costly as it simulates every single reaction. As such, approximate stochastic simulation algorithms such as the tau-leap algorithm are often used. Potentially computationally more efficient, the system statistics generated suffer from significant bias unless tau is relatively small, in which case the computational time can be comparable to that of the Gillespie algorithm. The multi-level method [Anderson and Higham, “Multi-level Monte Carlo for continuous time Markov chains, with applications in biochemical kinetics,” SIAM Multiscale Model. Simul. 10(1), 146–179 (2012)] tackles this problem. A base estimator is computed using many (cheap) sample paths at low accuracy. The bias inherent in this estimator is then reduced using a number of corrections. Each correction term is estimated using a collection of paired sample paths where one path of each pair is generated at a higher accuracy compared to the other (and so more expensive). By sharing random variables between these paired paths, the variance of each correction estimator can be reduced. This renders the multi-level method very efficient as only a relatively small number of paired paths are required to calculate each correction term. In the original multi-level method, each sample path is simulated using the tau-leap algorithm with a fixed value of τ. This approach can result in poor performance when the reaction activity of a system changes substantially over the timescale of interest. By introducing a novel adaptive time-stepping approach where τ is chosen according to the stochastic behaviour of each sample path, we extend the applicability of the multi-level method to such cases. We demonstrate the
姚靖靖; 邱于兵; 敖俊宇
2011-01-01
针对路径规划中的大型障碍物,机器人、障碍物与目标点三者一线,以及局部最小值等困难问题,提出了相应的改进人工势场算法.针对大型障碍物问题,采用障碍物边界斥力算法改进传统人工势场斥力函数,确保算法的实用性.针对机器人、障碍物与目标点三者在同一条直线时目标不可达问题,应用虚拟子目标引力算法,确保目标点是机器人的势场全局最小点,使得机器人能顺利到达目标点.针对在障碍物环境下的局部最小值问题,采用区域隔离障碍物的方法,使机器人快速走出局部最小值区域.仿真结果验证了改进算法的有效性.%Aims to solve difficult problems in mobile robot obstacle avoidance path planning based on improved artificial potential field (IAPF) algorithm, an obstacle boundary repulsion algorithm is designed to improve the performance of traditional artificial potential field algorithm for large obstacles.For the problem that robot, obstacle and target are located in the same line, a virtual sub-target gravity algorithm is proposed to ensure that the target is the global minimum of the robot potential field, and therefore the robot can arrive at the goal point.An obstacle isolation method is used for T-type obstacle situation which can solve the local minimum problem of potential field and help the robot go through quickly.Experiments are carried out by simulation to verify the effectiveness of the improved artificial potential field algorithm.
Nonadiabatic transition path sampling
Sherman, M. C.; Corcelli, S. A.
2016-07-01
Fewest-switches surface hopping (FSSH) is combined with transition path sampling (TPS) to produce a new method called nonadiabatic path sampling (NAPS). The NAPS method is validated on a model electron transfer system coupled to a Langevin bath. Numerically exact rate constants are computed using the reactive flux (RF) method over a broad range of solvent frictions that span from the energy diffusion (low friction) regime to the spatial diffusion (high friction) regime. The NAPS method is shown to quantitatively reproduce the RF benchmark rate constants over the full range of solvent friction. Integrating FSSH within the TPS framework expands the applicability of both approaches and creates a new method that will be helpful in determining detailed mechanisms for nonadiabatic reactions in the condensed-phase.
Competition for shortest paths on sparse graphs.
Yeung, Chi Ho; Saad, David
2012-05-18
Optimal paths connecting randomly selected network nodes and fixed routers are studied analytically in the presence of a nonlinear overlap cost that penalizes congestion. Routing becomes more difficult as the number of selected nodes increases and exhibits ergodicity breaking in the case of multiple routers. The ground state of such systems reveals nonmonotonic complex behaviors in average path length and algorithmic convergence, depending on the network topology, and densities of communicating nodes and routers. A distributed linearly scalable routing algorithm is also devised.