Solving the empty space problem in robot path planning by mathematical morphology
Roerdink, J.B.T.M.
1993-01-01
In this paper we formulate a morphological approach to path planning problems, in particular with respect to the empty-space problem, that is, the question of finding the allowed states for an object, moving in a space with obstacles. Our approach is based upon a recent generalization of
Zamirian, M.; Kamyad, A.V.; Farahi, M.H.
2009-01-01
In this Letter a new approach for solving optimal path planning problems for a single rigid and free moving object in a two and three dimensional space in the presence of stationary or moving obstacles is presented. In this approach the path planning problems have some incompatible objectives such as the length of path that must be minimized, the distance between the path and obstacles that must be maximized and etc., then a multi-objective dynamic optimization problem (MODOP) is achieved. Considering the imprecise nature of decision maker's (DM) judgment, these multiple objectives are viewed as fuzzy variables. By determining intervals for the values of these fuzzy variables, flexible monotonic decreasing or increasing membership functions are determined as the degrees of satisfaction of these fuzzy variables on their intervals. Then, the optimal path planning policy is searched by maximizing the aggregated fuzzy decision values, resulting in a fuzzy multi-objective dynamic optimization problem (FMODOP). Using a suitable t-norm, the FMODOP is converted into a non-linear dynamic optimization problem (NLDOP). By using parametrization method and some calculations, the NLDOP is converted into the sequence of conventional non-linear programming problems (NLPP). It is proved that the solution of this sequence of the NLPPs tends to a Pareto optimal solution which, among other Pareto optimal solutions, has the best satisfaction of DM for the MODOP. Finally, the above procedure as a novel algorithm integrating parametrization method and fuzzy aggregation to solve the MODOP is proposed. Efficiency of our approach is confirmed by some numerical examples.
Visibility-Based Goal Oriented Metrics and Application to Navigation and Path Planning Problems
2017-12-14
Oriented Metrics and Application to Navigation and Path Planning Problems Report Term: 0-Other Email : ytsai@math.utexas.edu Distribution Statement: 1...error bounds that we have obtained. Report Date: 06-Dec-2017 INVESTIGATOR(S): Phone Number: 5122327757 Principal: Y Name: Yen-Hsi Tsai Email ...w1 w2 ◆ and ~z = ✓ z1 z2 ◆ . Then we can write D0 h (PN (xi,j)) = Rp (R+⌘)2+h2 + 1 2h (µ2w1 µ2z1) 0 µ2w2µ3z2 2h 0 ! . It follows that the non
Jiang Zhao
2016-01-01
Full Text Available This paper presents an improved ant colony algorithm for the path planning of the omnidirectional mobile vehicle. The purpose of the improved ant colony algorithm is to design an appropriate route to connect the starting point and ending point of the environment with obstacles. Ant colony algorithm, which is used to solve the path planning problem, is improved according to the characteristics of the omnidirectional mobile vehicle. And in the improved algorithm, the nonuniform distribution of the initial pheromone and the selection strategy with direction play a very positive role in the path search. The coverage and updating strategy of pheromone is introduced to avoid repeated search reducing the effect of the number of ants on the performance of the algorithm. In addition, the pheromone evaporation coefficient is segmented and adjusted, which can effectively balance the convergence speed and search ability. Finally, this paper provides a theoretical basis for the improved ant colony algorithm by strict mathematical derivation, and some numerical simulations are also given to illustrate the effectiveness of the theoretical results.
Path planning in changeable environments
Nieuwenhuisen, D.
2007-01-01
This thesis addresses path planning in changeable environments. In contrast to traditional path planning that deals with static environments, in changeable environments objects are allowed to change their configurations over time. In many cases, path planning algorithms must facilitate quick
2016-07-22
be reduced to TP in -D UDH for any . We then show that the 2-D disk hypergraph constructed in the proof of Theorem 1 can be modified to an exposed...transmission range that induces hy- peredge , i.e., (3) GAO et al.: THINNEST PATH PROBLEM 1181 Theorem 5 shows that the covered area of the path...representation of (the two hyperedges rooted at from the example given in Fig. 6 are illustrated in green and blue, respectively). step, we show in this
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.
Fractional path planning and path tracking
Melchior, P.; Jallouli-Khlif, R.; Metoui, B.
2011-01-01
This paper presents the main results of the application of fractional approach in path planning and path tracking. A new robust path planning design for mobile robot was studied in dynamic environment. The normalized attractive force applied to the robot is based on a fictitious fractional attractive potential. This method allows to obtain robust path planning despite robot mass variation. The danger level of each obstacles is characterized by the fractional order of the repulsive potential of the obstacles. Under these conditions, the robot dynamic behavior was studied by analyzing its X - Y path planning with dynamic target or dynamic obstacles. The case of simultaneously mobile obstacles and target is also considered. The influence of the robot mass variation is studied and the robustness analysis of the obtained path shows the robustness improvement due to the non integer order properties. Pre shaping approach is used to reduce system vibration in motion control. Desired systems inputs are altered so that the system finishes the requested move without residual vibration. This technique, developed by N.C. Singer and W.P.Seering, is used for flexible structure control, particularly in the aerospace field. In a previous work, this method was extended for explicit fractional derivative systems and applied to second generation CRONE control, the robustness was also studied. CRONE (the French acronym of C ommande Robuste d'Ordre Non Entier ) control system design is a frequency-domain based methodology using complex fractional integration.
Solving a Class of Spatial Reasoning Problems: Minimal-Cost Path Planning in the Cartesian Plane.
1987-06-01
as in Figure 72. By the Theorem of Pythagoras : Z1 <a z 2 < C Yl(bl+b 2)uI, the cost of going along (a,b,c) is greater that the...preceding lemmas to an indefinite number of boundary-crossing episodes is accomplished by the following theorems . Theorem 1 extends the result of Lemma 1... Theorem 1: Any two Snell’s-law paths within a K-explored wedge defined by Snell’s-law paths RL and R. do not intersect within the K-explored portion of
Integrated assignment and path planning
Murphey, Robert A.
2005-11-01
A surge of interest in unmanned systems has exposed many new and challenging research problems across many fields of engineering and mathematics. These systems have the potential of transforming our society by replacing dangerous and dirty jobs with networks of moving machines. This vision is fundamentally separate from the modern view of robotics in that sophisticated behavior is realizable not by increasing individual vehicle complexity, but instead through collaborative teaming that relies on collective perception, abstraction, decision making, and manipulation. Obvious examples where collective robotics will make an impact include planetary exploration, space structure assembly, remote and undersea mining, hazardous material handling and clean-up, and search and rescue. Nonetheless, the phenomenon driving this technology trend is the increasing reliance of the US military on unmanned vehicles, specifically, aircraft. Only a few years ago, following years of resistance to the use of unmanned systems, the military and civilian leadership in the United States reversed itself and have recently demonstrated surprisingly broad acceptance of increasingly pervasive use of unmanned platforms in defense surveillance, and even attack. However, as rapidly as unmanned systems have gained acceptance, the defense research community has discovered the technical pitfalls that lie ahead, especially for operating collective groups of unmanned platforms. A great deal of talent and energy has been devoted to solving these technical problems, which tend to fall into two categories: resource allocation of vehicles to objectives, and path planning of vehicle trajectories. An extensive amount of research has been conducted in each direction, yet, surprisingly, very little work has considered the integrated problem of assignment and path planning. This dissertation presents a framework for studying integrated assignment and path planning and then moves on to suggest an exact
Walking path-planning method for multiple radiation areas
Liu, Yong-kuo; Li, Meng-kun; Peng, Min-jun; Xie, Chun-li; Yuan, Cheng-qian; Wang, Shuang-yu; Chao, Nan
2016-01-01
Highlights: • Radiation environment modeling method is designed. • Path-evaluating method and segmented path-planning method are proposed. • Path-planning simulation platform for radiation environment is built. • The method avoids to be misled by minimum dose path in single area. - Abstract: Based on minimum dose path-searching method, walking path-planning method for multiple radiation areas was designed to solve minimum dose path problem in single area and find minimum dose path in the whole space in this paper. Path-planning simulation platform was built using C# programming language and DirectX engine. The simulation platform was used in simulations dealing with virtual nuclear facilities. Simulation results indicated that the walking-path planning method is effective in providing safety for people walking in nuclear facilities.
Static and Dynamic Path Planning Using Incremental Heuristic Search
Khattab, Asem
2018-01-01
Path planning is an important component in any highly automated vehicle system. In this report, the general problem of path planning is considered first in partially known static environments where only static obstacles are present but the layout of the environment is changing as the agent acquires new information. Attention is then given to the problem of path planning in dynamic environments where there are moving obstacles in addition to the static ones. Specifically, a 2D car-like agent t...
Cooperative path planning of unmanned aerial vehicles
Tsourdos, Antonios; Shanmugavel, Madhavan
2010-01-01
An invaluable addition to the literature on UAV guidance and cooperative control, Cooperative Path Planning of Unmanned Aerial Vehicles is a dedicated, practical guide to computational path planning for UAVs. One of the key issues facing future development of UAVs is path planning: it is vital that swarm UAVs/ MAVs can cooperate together in a coordinated manner, obeying a pre-planned course but able to react to their environment by communicating and cooperating. An optimized path is necessary in order to ensure a UAV completes its mission efficiently, safely, and successfully. Focussing on the path planning of multiple UAVs for simultaneous arrival on target, Cooperative Path Planning of Unmanned Aerial Vehicles also offers coverage of path planners that are applicable to land, sea, or space-borne vehicles. Cooperative Path Planning of Unmanned Aerial Vehicles is authored by leading researchers from Cranfield University and provides an authoritative resource for researchers, academics and engineers working in...
Flexible integration of path-planning capabilities
Stobie, Iain C.; Tambe, Milind; Rosenbloom, Paul S.
1993-05-01
Robots pursuing complex goals must plan paths according to several criteria of quality, including shortness, safety, speed and planning time. Many sources and kinds of knowledge, such as maps, procedures and perception, may be available or required. Both the quality criteria and sources of knowledge may vary widely over time, and in general they will interact. One approach to address this problem is to express all criteria and goals numerically in a single weighted graph, and then to search this graph to determine a path. Since this is problematic with symbolic or uncertain data and interacting criteria, we propose that what is needed instead is an integration of many kinds of planning capabilities. We describe a hybrid approach to integration, based on experiments with building simulated mobile robots using Soar, an integrated problem-solving and learning system. For flexibility, we have implemented a combination of internal planning, reactive capabilities and specialized tools. We illustrate how these components can complement each other's limitations and produce plans which integrate geometric and task knowledge.
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.
Conditionally solvable path integral problems
Grosche, C.
1995-05-01
Some specific conditionally exactly solvable potentials are discussed within the path integral formalism. They generalize the usually known potentials by the incorporation of a fractional power behaviour and strongly anharmonic terms. We find four different kinds of such potentials, the first is related to the Coulomb potential, the second is an anharmonic confinement potential, and the third and the fourth are related to the Manning-Rosen potential. (orig.)
Robotic Online Path Planning on Point Cloud.
Liu, Ming
2016-05-01
This paper deals with the path-planning problem for mobile wheeled- or tracked-robot which drive in 2.5-D environments, where the traversable surface is usually considered as a 2-D-manifold embedded in a 3-D ambient space. Specially, we aim at solving the 2.5-D navigation problem using raw point cloud as input. The proposed method is independent of traditional surface parametrization or reconstruction methods, such as a meshing process, which generally has high-computational complexity. Instead, we utilize the output of 3-D tensor voting framework on the raw point clouds. The computation of tensor voting is accelerated by optimized implementation on graphics computation unit. Based on the tensor voting results, a novel local Riemannian metric is defined using the saliency components, which helps the modeling of the latent traversable surface. Using the proposed metric, we prove that the geodesic in the 3-D tensor space leads to rational path-planning results by experiments. Compared to traditional methods, the results reveal the advantages of the proposed method in terms of smoothing the robot maneuver while considering the minimum travel distance.
Cooperative organic mine avoidance path planning
McCubbin, Christopher B.; Piatko, Christine D.; Peterson, Adam V.; Donnald, Creighton R.; Cohen, David
2005-06-01
The JHU/APL Path Planning team has developed path planning techniques to look for paths that balance the utility and risk associated with different routes through a minefield. Extending on previous years' efforts, we investigated real-world Naval mine avoidance requirements and developed a tactical decision aid (TDA) that satisfies those requirements. APL has developed new mine path planning techniques using graph based and genetic algorithms which quickly produce near-minimum risk paths for complicated fitness functions incorporating risk, path length, ship kinematics, and naval doctrine. The TDA user interface, a Java Swing application that obtains data via Corba interfaces to path planning databases, allows the operator to explore a fusion of historic and in situ mine field data, control the path planner, and display the planning results. To provide a context for the minefield data, the user interface also renders data from the Digital Nautical Chart database, a database created by the National Geospatial-Intelligence Agency containing charts of the world's ports and coastal regions. This TDA has been developed in conjunction with the COMID (Cooperative Organic Mine Defense) system. This paper presents a description of the algorithms, architecture, and application produced.
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.
Path optimization method for the sign problem
Ohnishi Akira
2018-01-01
Full Text Available We propose a path optimization method (POM to evade the sign problem in the Monte-Carlo calculations for complex actions. Among many approaches to the sign problem, the Lefschetz-thimble path-integral method and the complex Langevin method are promising and extensively discussed. In these methods, real field variables are complexified and the integration manifold is determined by the flow equations or stochastically sampled. When we have singular points of the action or multiple critical points near the original integral surface, however, we have a risk to encounter the residual and global sign problems or the singular drift term problem. One of the ways to avoid the singular points is to optimize the integration path which is designed not to hit the singular points of the Boltzmann weight. By specifying the one-dimensional integration-path as z = t +if(t(f ϵ R and by optimizing f(t to enhance the average phase factor, we demonstrate that we can avoid the sign problem in a one-variable toy model for which the complex Langevin method is found to fail. In this proceedings, we propose POM and discuss how we can avoid the sign problem in a toy model. We also discuss the possibility to utilize the neural network to optimize the path.
Path Planning Methods in an Environment with Obstacles (A Review
W. Liu
2018-01-01
Full Text Available Planning the path is the most important task in the mobile robot navigation. This task involves basically three aspects. First, the planned path must run from a given starting point to a given endpoint. Secondly, it should ensure robot’s collision-free movement. Thirdly, among all the possible paths that meet the first two requirements it must be, in a certain sense, optimal.Methods of path planning can be classified according to different characteristics. In the context of using intelligent technologies, they can be divided into traditional methods and heuristic ones. By the nature of the environment, it is possible to divide planning methods into planning methods in a static environment and in a dynamic one (it should be noted, however, that a static environment is rare. Methods can also be divided according to the completeness of information about the environment, namely methods with complete information (in this case the issue is a global path planning and methods with incomplete information (usually, this refers to the situational awareness in the immediate vicinity of the robot, in this case it is a local path planning. Note that incomplete information about the environment can be a consequence of the changing environment, i.e. in a dynamic environment, there is, usually, a local path planning.Literature offers a great deal of methods for path planning where various heuristic techniques are used, which, as a rule, result from the denotative meaning of the problem being solved. This review discusses the main approaches to the problem solution. Here we can distinguish five classes of basic methods: graph-based methods, methods based on cell decomposition, use of potential fields, optimization methods, фтв methods based on intelligent technologies.Many methods of path planning, as a result, give a chain of reference points (waypoints connecting the beginning and end of the path. This should be seen as an intermediate result. The problem
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.
Reactive Path Planning Approach for Docking Robots in Unknown Environment
Peng Cui
2017-01-01
Full Text Available Autonomous robots need to be recharged and exchange information with the host through docking in the long-distance tasks. Therefore, feasible path is required in the docking process to guide the robot and adjust its pose. However, when there are unknown obstacles in the work area, it becomes difficult to determine the feasible path for docking. This paper presents a reactive path planning approach named Dubins-APF (DAPF to solve the path planning problem for docking in unknown environment with obstacles. In this proposed approach the Dubins curves are combined with the designed obstacle avoidance potential field to plan the feasible path. Firstly, an initial path is planned and followed according to the configurations of the robot and the docking station. Then when the followed path is evaluated to be infeasible, the intermediate configuration is calculated as well as the replanned path based on the obstacle avoidance potential field. The robot will be navigated to the docking station with proper pose eventually via the DAPF approach. The proposed DAPF approach is efficient and does not require the prior knowledge about the environment. Simulation results are given to validate the effectiveness and feasibility of the proposed approach.
Modeling and Solving the Train Pathing Problem
Chuen-Yih Chen
2009-04-01
Full Text Available In a railroad system, train pathing is concerned with the assignment of trains to links and tracks, and train timetabling allocates time slots to trains. In this paper, we present an optimization heuristic to solve the train pathing and timetabling problem. This heuristic allows the dwell time of trains in a station or link to be dependent on the assigned tracks. It also allows the minimum clearance time between the trains to depend on their relative status. The heuristic generates a number of alternative paths for each train service in the initialization phase. Then it uses a neighborhood search approach to find good feasible combinations of these paths. A linear program is developed to evaluate the quality of each combination that is encountered. Numerical examples are provided.
Chiaramonte, Fran
2003-01-01
This viewgraph presentation discusses the status and goals for the NASA OBPR Physical Science Research Program. The following text was used to summarize the presentation. The OBPR Physical Sciences Research program has been comprehensively reviewed and endorsed by National Research Council. The value and need for the research have been re-affirmed. The research program has been prioritized and resource re-allocations have been carried out through an OBPR-wide process. An increasing emphasis on strategic, mission-oriented research is planned. The program will strive to maintain a balance between strategic and fundamental research. A feasible ISS flight research program fitting within the budgetary and ISS resource envelopes has been formulated for the near term (2003-2007). The current ISS research program will be significantly strengthened starting 2005 by using discipline dedicated research facility racks. A research re-planning effort has been initiated and will include active participation from the research community in the next few months. The research re-planning effort will poise PSR to increase ISS research utilization for a potential enhancement beyond ISS IP Core Complete. The Physical Sciences research program readily integrates the cross-disciplinary requirements of the NASA and OBPR strategic objectives. Each fundamental research thrust will develop a roadmap through technical workshops and Discipline Working Groups (DWGs). Most fundamental research thrusts will involve cross-disciplinary efforts. A Technology Roadmap will guide the Strategic Research for Exploration thrust. The Research Plan will integrate and coordinate fundamental Research Thrusts Roadmaps with the Technology Roadmap. The Technology Roadmap will be developed in coordination with other OBPR programs as well as other Enterprise (R,S,M,N). International Partners will contribute to the roadmaps and through research coordination. The research plan will be vetted with the discipline
Path Planning Algorithms for Autonomous Border Patrol Vehicles
Lau, George Tin Lam
This thesis presents an online path planning algorithm developed for unmanned vehicles in charge of autonomous border patrol. In this Pursuit-Evasion game, the unmanned vehicle is required to capture multiple trespassers on its own before any of them reach a target safe house where they are safe from capture. The problem formulation is based on Isaacs' Target Guarding problem, but extended to the case of multiple evaders. The proposed path planning method is based on Rapidly-exploring random trees (RRT) and is capable of producing trajectories within several seconds to capture 2 or 3 evaders. Simulations are carried out to demonstrate that the resulting trajectories approach the optimal solution produced by a nonlinear programming-based numerical optimal control solver. Experiments are also conducted on unmanned ground vehicles to show the feasibility of implementing the proposed online path planning algorithm on physical applications.
A bat algorithm with mutation for UCAV path planning.
Wang, Gaige; Guo, Lihong; Duan, Hong; Liu, Luo; Wang, Heqi
2012-01-01
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.
Learning to improve path planning performance
Chen, Pang C.
1995-04-01
In robotics, path planning refers to finding a short. collision-free path from an initial robot configuration to a desired configuratioin. It has to be fast to support real-time task-level 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 remedy this situation, we present and analyze a learning algorithm that uses past experience to increase 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 robot configurations is learned to support faster planning. More generally, the algorithm provides a speedup-learning framework in which a slow but capable planner may be improved both cost-wise and capability-wise by a faster but less capable planner coupled with experience. The basic algorithm is suitable for stationary environments, and can be extended to accommodate changing environments with on-demand experience repair and object-attached experience abstraction. To analyze the algorithm, we characterize the situations in which the adaptive planner is useful, provide quantitative bounds to predict its behavior, and confirm our theoretical results with experiments in path planning of manipulators. Our algorithm and analysis are sufficiently, general that they may also be applied to other planning domains in which experience is useful
Path integral solution of the Dirichlet problem
LaChapelle, J.
1997-01-01
A scheme for functional integration developed by Cartier/DeWitt-Morette is first reviewed and then employed to construct the path integral representation for the solution of the Dirichlet problem in terms of first exit time. The path integral solution is then applied to calculate the fixed-energy point-to-point transition amplitude both in configuration and phase space. The path integral solution can also be derived using physical principles based on Feynman close-quote s original reasoning. We check that the Fourier transform in energy of the fixed-energy point-to-point transition amplitude gives the well known time-dependent transition amplitude, and calculate the WKB approximation. copyright 1997 Academic Press, Inc
Aircraft path planning with the use of smooth trajectories
Belokon', S. A.; Zolotukhin, Yu. N.; Nesterov, A. A.
2017-01-01
A simplified method of plane trajectory calculation is proposed for solving the problem of planning a path defined by a sequence of waypoints. The trajectory consists of oriented segments of straight lines joined by clothoids (Cornu spirals). The efficiency of the method is validated by means of numerical simulations in the MATLAB/Simulink environment.
Robust Path Planning for Space Exploration Rovers
National Aeronautics and Space Administration — Motion planning considers the problem of moving a system from a starting position to a desired goal position. This problem has been shown to be a computationally...
Robust Path Planning and Feedback Design Under Stochastic Uncertainty
Blackmore, Lars
2008-01-01
Autonomous vehicles require optimal path planning algorithms to achieve mission goals while avoiding obstacles and being robust to uncertainties. The uncertainties arise from exogenous disturbances, modeling errors, and sensor noise, which can be characterized via stochastic models. Previous work defined a notion of robustness in a stochastic setting by using the concept of chance constraints. This requires that mission constraint violation can occur with a probability less than a prescribed value.In this paper we describe a novel method for optimal chance constrained path planning with feedback design. The approach optimizes both the reference trajectory to be followed and the feedback controller used to reject uncertainty. Our method extends recent results in constrained control synthesis based on convex optimization to solve control problems with nonconvex constraints. This extension is essential for path planning problems, which inherently have nonconvex obstacle avoidance constraints. Unlike previous approaches to chance constrained path planning, the new approach optimizes the feedback gain as wellas the reference trajectory.The key idea is to couple a fast, nonconvex solver that does not take into account uncertainty, with existing robust approaches that apply only to convex feasible regions. By alternating between robust and nonrobust solutions, the new algorithm guarantees convergence to a global optimum. We apply the new method to an unmanned aircraft and show simulation results that demonstrate the efficacy of the approach.
The Unplanned Paths of Planning Schools.
Alonso, William
1986-01-01
Describes the evolving emphasis of schools of urban planning from concentration on scientific management, beautifying cities, and educating the public in the 1920s to solving the social problems in the 1960s. Calls for a collaboration of business and other professional schools to redefine the function and purpose of urban planning schools to…
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.
Special cases of the quadratic shortest path problem
Sotirov, Renata; Hu, Hao
2017-01-01
The quadratic shortest path problem (QSPP) is the problem of finding a path with prespecified start vertex s and end vertex t in a digraph such that the sum of weights of arcs and the sum of interaction costs over all pairs of arcs on the path is minimized. We first consider a variant of the QSPP
Shortest Path Problems in a Stochastic and Dynamic Environment
Cho, Jae
2003-01-01
.... Particularly, we develop a variety of algorithms to solve the expected shortest path problem in addition to techniques for computing the total travel time distribution along a path in the network...
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.
An Approximation Approach for Solving the Subpath Planning Problem
Safilian, Masoud; Tashakkori, S. Mehdi; Eghbali, Sepehr; Safilian, Aliakbar
2016-01-01
The subpath planning problem is a branch of the path planning problem, which has widespread applications in automated manufacturing process as well as vehicle and robot navigation. This problem is to find the shortest path or tour subject for travelling a set of given subpaths. The current approaches for dealing with the subpath planning problem are all based on meta-heuristic approaches. It is well-known that meta-heuristic based approaches have several deficiencies. To address them, we prop...
Minimum dose method for walking-path planning of nuclear facilities
Liu, Yong-kuo; Li, Meng-kun; Xie, Chun-li; Peng, Min-jun; Wang, Shuang-yu; Chao, Nan; Liu, Zhong-kun
2015-01-01
Highlights: • For radiation environment, the environment model is proposed. • For the least dose walking path problem, a path-planning method is designed. • The path-planning virtual–real mixed simulation program is developed. • The program can plan walking path and simulate. - Abstract: A minimum dose method based on staff walking road network model was proposed for the walking-path planning in nuclear facilities. A virtual–reality simulation program was developed using C# programming language and Direct X engine. The simulation program was used in simulations dealing with virtual nuclear facilities. Simulation results indicated that the walking-path planning method was effective in providing safety for people walking in nuclear facilities
Visibility-based optimal path and motion planning
Wang, Paul Keng-Chieh
2015-01-01
This monograph deals with various visibility-based path and motion planning problems motivated by real-world applications such as exploration and mapping planetary surfaces, environmental surveillance using stationary or mobile robots, and imaging of global air/pollutant circulation. The formulation and solution of these problems call for concepts and methods from many areas of applied mathematics including computational geometry, set-covering, non-smooth optimization, combinatorial optimization and optimal control. Emphasis is placed on the formulation of new problems and methods of approach to these problems. Since geometry and visualization play important roles in the understanding of these problems, intuitive interpretations of the basic concepts are presented before detailed mathematical development. The development of a particular topic begins with simple cases illustrated by specific examples, and then progresses forward to more complex cases. The intended readers of this monograph are primarily studen...
Cooperative Path-Planning for Multi-Vehicle Systems
Qichen Wang
2014-11-01
Full Text Available In this paper, we propose a collision avoidance algorithm for multi-vehicle systems, which is a common problem in many areas, including navigation and robotics. In dynamic environments, vehicles may become involved in potential collisions with each other, particularly when the vehicle density is high and the direction of travel is unrestricted. Cooperatively planning vehicle movement can effectively reduce and fairly distribute the detour inconvenience before subsequently returning vehicles to their intended paths. We present a novel method of cooperative path planning for multi-vehicle systems based on reinforcement learning to address this problem as a decision process. A dynamic system is described as a multi-dimensional space formed by vectors as states to represent all participating vehicles’ position and orientation, whilst considering the kinematic constraints of the vehicles. Actions are defined for the system to transit from one state to another. In order to select appropriate actions whilst satisfying the constraints of path smoothness, constant speed and complying with a minimum distance between vehicles, an approximate value function is iteratively developed to indicate the desirability of every state-action pair from the continuous state space and action space. The proposed scheme comprises two phases. The convergence of the value function takes place in the former learning phase, and it is then used as a path planning guideline in the subsequent action phase. This paper summarizes the concept and methodologies used to implement this online cooperative collision avoidance algorithm and presents results and analysis regarding how this cooperative scheme improves upon two baseline schemes where vehicles make movement decisions independently.
Toward solving the sign problem with path optimization method
Mori, Yuto; Kashiwa, Kouji; Ohnishi, Akira
2017-12-01
We propose a new approach to circumvent the sign problem in which the integration path is optimized to control the sign problem. We give a trial function specifying the integration path in the complex plane and tune it to optimize the cost function which represents the seriousness of the sign problem. We call it the path optimization method. In this method, we do not need to solve the gradient flow required in the Lefschetz-thimble method and then the construction of the integration-path contour arrives at the optimization problem where several efficient methods can be applied. In a simple model with a serious sign problem, the path optimization method is demonstrated to work well; the residual sign problem is resolved and precise results can be obtained even in the region where the global sign problem is serious.
Knowledge-inducing Global Path Planning for Robots in Environment with Hybrid Terrain
Yi-nan Guo
2010-09-01
Full Text Available In complex environment with hybrid terrain, different regions may have different terrain. Path planning for robots in such environment is an open NP-complete problem, which lacks effective methods. The paper develops a novel global path planning method based on common sense and evolution knowledge by adopting dual evolution structure in culture algorithms. Common sense describes terrain information and feasibility of environment, which is used to evaluate and select the paths. Evolution knowledge describes the angle relationship between the path and the obstacles, or the common segments of paths, which is used to judge and repair infeasible individuals. Taken two types of environments with different obstacles and terrain as examples, simulation results indicate that the algorithm can effectively solve path planning problem in complex environment and decrease the computation complexity for judgment and repair of infeasible individuals. It also can improve the convergence speed and have better computation stability.
1982-10-01
Artificial Intelig ~ence (Vol. III, edited by Paul R. Cohen and’ Edward A.. Feigenbaum)’, The chapter was written B’ Paul Cohen, with contributions... Artificial Intelligence (Vol. III, edited by Paul R. Cohen and EdWard A. Feigenbaum). The chapter was written by Paul R. Cohen, with contributions by Stephen...Wheevoats"EntermdI’ Planning and Problem ’Solving by Paul R. Cohen Chaptb-rXV-of Volumec III’of the Handbook of Artificial Intelligence edited by Paul R
Heuristic methods for shared backup path protection planning
Haahr, Jørgen Thorlund; Stidsen, Thomas Riis; Zachariasen, Martin
2012-01-01
schemes are employed. In contrast to manual intervention, automatic protection schemes such as Shared Backup Path Protection (SBPP) can recover from failure quickly and efficiently. SBPP is a simple but efficient protection scheme that can be implemented in backbone networks with technology available...... present heuristic algorithms and lower bound methods for the SBPP planning problem. Experimental results show that the heuristic algorithms are able to find good quality solutions in minutes. A solution gap of less than 3.5% was achieved for more than half of the benchmark instances (and a gap of less...
Path planning in uncertain flow fields using ensemble method
Wang, Tong
2016-08-20
An ensemble-based approach is developed to conduct optimal path planning in unsteady ocean currents under uncertainty. We focus our attention on two-dimensional steady and unsteady uncertain flows, and adopt a sampling methodology that is well suited to operational forecasts, where an ensemble of deterministic predictions is used to model and quantify uncertainty. In an operational setting, much about dynamics, topography, and forcing of the ocean environment is uncertain. To address this uncertainty, the flow field is parametrized using a finite number of independent canonical random variables with known densities, and the ensemble is generated by sampling these variables. For each of the resulting realizations of the uncertain current field, we predict the path that minimizes the travel time by solving a boundary value problem (BVP), based on the Pontryagin maximum principle. A family of backward-in-time trajectories starting at the end position is used to generate suitable initial values for the BVP solver. This allows us to examine and analyze the performance of the sampling strategy and to develop insight into extensions dealing with general circulation ocean models. In particular, the ensemble method enables us to perform a statistical analysis of travel times and consequently develop a path planning approach that accounts for these statistics. The proposed methodology is tested for a number of scenarios. We first validate our algorithms by reproducing simple canonical solutions, and then demonstrate our approach in more complex flow fields, including idealized, steady and unsteady double-gyre flows.
A New Method of Global Path Planning for AGV
SHI En-xiu; HUANG Yu-mei
2006-01-01
Path planning is important in the research of a mobile robot (MR). Methods for it have been used in different applications. An automated guided vehicle(AGV), which is a kind of MR, is used in a flexible manufacturing system(FMS). Path planning for it is essential to improve the efficiency of FMS. A new method was proposed with known obstacle space FMS in this paper. FMS is described by the Augmented Pos Matrix of a Machine (APMM) and Relative Pos Matrix of Machines (RPMM), which is smaller. The optimum path can be obtained according to the probability of the path and the maximal probability path. The suggested algorithm of path planning was good performance through simulation result: simplicity, saving time and reliability.
Analysis of construction dynamic plan using fuzzy critical path method
Kurij Kazimir V.
2014-01-01
Full Text Available Critical Path Method (CPM technique has become widely recognized as valuable tool for the planning and scheduling large construction projects. The aim of this paper is to present an analytical method for finding the Critical Path in the precedence network diagram where the duration of each activity is represented by a trapezoidal fuzzy number. This Fuzzy Critical Path Method (FCPM uses a defuzzification formula for trapezoidal fuzzy number and applies it on the total float (slack time for each activity in the fuzzy precedence network to find the critical path. The method presented in this paper is very effective in determining the critical activities and finding the critical paths.
Multi-AGV path planning with double-path constraints by using an improved genetic algorithm.
Zengliang Han
Full Text Available This paper investigates an improved genetic algorithm on multiple automated guided vehicle (multi-AGV path planning. The innovations embody in two aspects. First, three-exchange crossover heuristic operators are used to produce more optimal offsprings for getting more information than with the traditional two-exchange crossover heuristic operators in the improved genetic algorithm. Second, double-path constraints of both minimizing the total path distance of all AGVs and minimizing single path distances of each AGV are exerted, gaining the optimal shortest total path distance. The simulation results show that the total path distance of all AGVs and the longest single AGV path distance are shortened by using the improved genetic algorithm.
Global optimal path planning of an autonomous vehicle for overtaking a moving obstacle
B. Mashadi
Full Text Available In this paper, the global optimal path planning of an autonomous vehicle for overtaking a moving obstacle is proposed. In this study, the autonomous vehicle overtakes a moving vehicle by performing a double lane-change maneuver after detecting it in a proper distance ahead. The optimal path of vehicle for performing the lane-change maneuver is generated by a path planning program in which the sum of lateral deviation of the vehicle from a reference path and the rate of steering angle become minimum while the lateral acceleration of vehicle does not exceed a safe limit value. A nonlinear optimal control theory with the lateral vehicle dynamics equations and inequality constraint of lateral acceleration are used to generate the path. The indirect approach for solving the optimal control problem is used by applying the calculus of variation and the Pontryagin's Minimum Principle to obtain first-order necessary conditions for optimality. The optimal path is generated as a global optimal solution and can be used as the benchmark of the path generated by the local motion planning of autonomous vehicles. A full nonlinear vehicle model in CarSim software is used for path following simulation by importing path data from the MATLAB code. The simulation results show that the generated path for the autonomous vehicle satisfies all vehicle dynamics constraints and hence is a suitable overtaking path for the following vehicle.
Singularities of robot mechanisms numerical computation and avoidance path planning
Bohigas, Oriol; Ros, Lluís
2017-01-01
This book presents the singular configurations associated with a robot mechanism, together with robust methods for their computation, interpretation, and avoidance path planning. Having such methods is essential as singularities generally pose problems to the normal operation of a robot, but also determine the workspaces and motion impediments of its underlying mechanical structure. A distinctive feature of this volume is that the methods are applicable to nonredundant mechanisms of general architecture, defined by planar or spatial kinematic chains interconnected in an arbitrary way. Moreover, singularities are interpreted as silhouettes of the configuration space when seen from the input or output spaces. This leads to a powerful image that explains the consequences of traversing singular configurations, and all the rich information that can be extracted from them. The problems are solved by means of effective branch-and-prune and numerical continuation methods that are of independent interest in themselves...
Memristor-based memory: The sneak paths problem and solutions
Zidan, Mohammed A.
2012-10-29
In this paper, we investigate the read operation of memristor-based memories. We analyze the sneak paths problem and provide a noise margin metric to compare the various solutions proposed in the literature. We also analyze the power consumption associated with these solutions. Moreover, we study the effect of the aspect ratio of the memory array on the sneak paths. Finally, we introduce a new technique for solving the sneak paths problem by gating the memory cell using a three-terminal memistor device.
Memristor-based memory: The sneak paths problem and solutions
Zidan, Mohammed A.; Fahmy, Hossam A.H.; Hussain, Muhammad Mustafa; Salama, Khaled N.
2012-01-01
In this paper, we investigate the read operation of memristor-based memories. We analyze the sneak paths problem and provide a noise margin metric to compare the various solutions proposed in the literature. We also analyze the power consumption associated with these solutions. Moreover, we study the effect of the aspect ratio of the memory array on the sneak paths. Finally, we introduce a new technique for solving the sneak paths problem by gating the memory cell using a three-terminal memistor device.
A Hybrid 3D Path Planning Method for UAVs
Ortiz-Arroyo, Daniel
2015-01-01
This paper presents a hybrid method for path planning in 3D spaces. We propose an improvement to a near-optimal 2D off-line algorithm and a ﬂexible normalized on-line fuzzy controller to ﬁnd shortest paths. Our method, targeted to low altitude domains, is simple and efﬁcient. Our preliminary resu...
Partial Path Column Generation for the Vehicle Routing Problem
Jepsen, Mads Kehlet; Petersen, Bjørn
This paper presents a column generation algorithm for the Capacitated Vehicle Routing Problem (CVRP) and the Vehicle Routing Problem with Time Windows (VRPTW). Traditionally, column generation models of the CVRP and VRPTW have consisted of a Set Partitioning master problem with each column...... of the giant tour’; a so-called partial path, i.e., not necessarily starting and ending in the depot. This way, the length of the partial path can be bounded and a better control of the size of the solution space for the pricing problem can be obtained....
Interactive multi-objective path planning through a palette-based user interface
Shaikh, Meher T.; Goodrich, Michael A.; Yi, Daqing; Hoehne, Joseph
2016-05-01
n a problem where a human uses supervisory control to manage robot path-planning, there are times when human does the path planning, and if satisfied commits those paths to be executed by the robot, and the robot executes that plan. In planning a path, the robot often uses an optimization algorithm that maximizes or minimizes an objective. When a human is assigned the task of path planning for robot, the human may care about multiple objectives. This work proposes a graphical user interface (GUI) designed for interactive robot path-planning when an operator may prefer one objective over others or care about how multiple objectives are traded off. The GUI represents multiple objectives using the metaphor of an artist's palette. A distinct color is used to represent each objective, and tradeoffs among objectives are balanced in a manner that an artist mixes colors to get the desired shade of color. Thus, human intent is analogous to the artist's shade of color. We call the GUI an "Adverb Palette" where the word "Adverb" represents a specific type of objective for the path, such as the adverbs "quickly" and "safely" in the commands: "travel the path quickly", "make the journey safely". The novel interactive interface provides the user an opportunity to evaluate various alternatives (that tradeoff between different objectives) by allowing her to visualize the instantaneous outcomes that result from her actions on the interface. In addition to assisting analysis of various solutions given by an optimization algorithm, the palette has additional feature of allowing the user to define and visualize her own paths, by means of waypoints (guiding locations) thereby spanning variety for planning. The goal of the Adverb Palette is thus to provide a way for the user and robot to find an acceptable solution even though they use very different representations of the problem. Subjective evaluations suggest that even non-experts in robotics can carry out the planning tasks with a
Active Path Planning for Drones in Object Search
Wang, Zeyangyi
2017-01-01
Object searching is one of the most popular applications of unmanned aerial vehicles. Low cost small drones are particularly suited for surveying tasks in difficult conditions. With their limited on-board processing power and battery life, there is a need for more efficient search algorithm. The proposed path planning algorithm utilizes AZ-net, a deep learning network to process images captured on drones for adaptive flight path planning. Search simulation based on videos and actual experimen...
Path Planning Method in Multi-obstacle Marine Environment
Zhang, Jinpeng; Sun, Hanxv
2017-12-01
In this paper, an improved algorithm for particle swarm optimization is proposed for the application of underwater robot in the complex marine environment. Not only did consider to avoid obstacles when path planning, but also considered the current direction and the size effect on the performance of the robot dynamics. The algorithm uses the trunk binary tree structure to construct the path search space and A * heuristic search method is used in the search space to find a evaluation standard path. Then the particle swarm algorithm to optimize the path by adjusting evaluation function, which makes the underwater robot in the current navigation easier to control, and consume less energy.
Points-Based Safe Path Planning of Continuum Robots
Khuram Shahzad
2015-07-01
Full Text Available Continuum robots exhibit great potential in a number of challenging applications where traditional rigid link robots pose certain limitations, e.g., working in unstructured environments. In order to enable the usage of continuum robots in safety-critical applications, such as surgery and nuclear decontamination, it is extremely important to ensure a safe path for the robot's movement. Existing algorithms for continuum robot path planning have certain limitations that need to be addressed. These include the fact that none of the algorithms provide safety assurance parameters and control for path planning. They are computationally expensive, applicable to a specific type of continuum robots, and mostly they do not incorporate design and kinematics constraints. In this paper, we propose a points-based path planning (PoPP algorithm for continuum robots that computes the path by imposing safety constraints and improves upon the limitations of existing approaches. In the algorithm, we exploit the constant curvature-bending property of continuum robots in their path planning process. The algorithm is computationally efficient and provides a good tradeoff between accuracy and efficiency that can be implemented to enable the safety-critical application of continuum robots. This algorithm also provides information regarding path volume and flexibility in movement. Simulation results confirm that the algorithm possesses promising potential for all types of continuum robots (following the constant curvature-bending property. We believe that this effectively balances the desired safety and efficiency requirements.
Constraint-Based Local Search for Constrained Optimum Paths Problems
Pham, Quang Dung; Deville, Yves; van Hentenryck, Pascal
Constrained Optimum Path (COP) problems arise in many real-life applications and are ubiquitous in communication networks. They have been traditionally approached by dedicated algorithms, which are often hard to extend with side constraints and to apply widely. This paper proposes a constraint-based local search (CBLS) framework for COP applications, bringing the compositionality, reuse, and extensibility at the core of CBLS and CP systems. The modeling contribution is the ability to express compositional models for various COP applications at a high level of abstraction, while cleanly separating the model and the search procedure. The main technical contribution is a connected neighborhood based on rooted spanning trees to find high-quality solutions to COP problems. The framework, implemented in COMET, is applied to Resource Constrained Shortest Path (RCSP) problems (with and without side constraints) and to the edge-disjoint paths problem (EDP). Computational results show the potential significance of the approach.
Hierarchical path planning and control of a small fixed-wing UAV: Theory and experimental validation
Jung, Dongwon
2007-12-01
Recently there has been a tremendous growth of research emphasizing control of unmanned aerial vehicles (UAVs) either in isolation or in teams. As a matter of fact, UAVs increasingly find their way into military and law enforcement applications (e.g., reconnaissance, remote delivery of urgent equipment/material, resource assessment, environmental monitoring, battlefield monitoring, ordnance delivery, etc.). This trend will continue in the future, as UAVs are poised to replace the human-in-the-loop during dangerous missions. Civilian applications of UAVs are also envisioned such as crop dusting, geological surveying, search and rescue operations, etc. In this thesis we propose a new online multiresolution path planning algorithm for a small UAV with limited on-board computational resources. The proposed approach assumes that the UAV has detailed information of the environment and the obstacles only in its vicinity. Information about far-away obstacles is also available, albeit less accurately. The proposed algorithm uses the fast lifting wavelet transform (FLWT) to get a multiresolution cell decomposition of the environment, whose dimension is commensurate to the on-board computational resources. A topological graph representation of the multiresolution cell decomposition is constructed efficiently, directly from the approximation and detail wavelet coefficients. Dynamic path planning is sequentially executed for an optimal path using the A* algorithm over the resulting graph. The proposed path planning algorithm is implemented on-line on a small autopilot. Comparisons with the standard D*-lite algorithm are also presented. We also investigate the problem of generating a smooth, planar reference path from a discrete optimal path. Upon the optimal path being represented as a sequence of cells in square geometry, we derive a smooth B-spline path that is constrained inside a channel that is induced by the geometry of the cells. To this end, a constrained optimization
Ni, Jianjun; Wu, Liuying; Shi, Pengfei; Yang, Simon X
2017-01-01
Real-time path planning for autonomous underwater vehicle (AUV) is a very difficult and challenging task. Bioinspired neural network (BINN) has been used to deal with this problem for its many distinct advantages: that is, no learning process is needed and realization is also easy. However, there are some shortcomings when BINN is applied to AUV path planning in a three-dimensional (3D) unknown environment, including complex computing problem when the environment is very large and repeated path problem when the size of obstacles is bigger than the detection range of sensors. To deal with these problems, an improved dynamic BINN is proposed in this paper. In this proposed method, the AUV is regarded as the core of the BINN and the size of the BINN is based on the detection range of sensors. Then the BINN will move with the AUV and the computing could be reduced. A virtual target is proposed in the path planning method to ensure that the AUV can move to the real target effectively and avoid big-size obstacles automatically. Furthermore, a target attractor concept is introduced to improve the computing efficiency of neural activities. Finally, some experiments are conducted under various 3D underwater environments. The experimental results show that the proposed BINN based method can deal with the real-time path planning problem for AUV efficiently.
Rapidly Exploring Random Trees Used for Mobile Robots Path Planning
Krejsa, Jiří; Věchet, S.
2005-01-01
Roč. 12, č. 4 (2005), s. 231-238 ISSN 1802-1484. [Mechatronics, Robotics and Biomechanics 2005. Třešť, 26.09.2005-29.09.2005] Institutional research plan: CEZ:AV0Z20760514 Keywords : path planning * mobile robot Subject RIV: JD - Computer Applications, Robotics
Minimum Time Path Planning for Robotic Manipulator in Drilling/ Spot Welding Tasks
Qiang Zhang
2016-04-01
Full Text Available In this paper, a minimum time path planning strategy is proposed for multi points manufacturing problems in drilling/spot welding tasks. By optimizing the travelling schedule of the set points and the detailed transfer path between points, the minimum time manufacturing task is realized under fully utilizing the dynamic performance of robotic manipulator. According to the start-stop movement in drilling/spot welding task, the path planning problem can be converted into a traveling salesman problem (TSP and a series of point to point minimum time transfer path planning problems. Cubic Hermite interpolation polynomial is used to parameterize the transfer path and then the path parameters are optimized to obtain minimum point to point transfer time. A new TSP with minimum time index is constructed by using point-point transfer time as the TSP parameter. The classical genetic algorithm (GA is applied to obtain the optimal travelling schedule. Several minimum time drilling tasks of a 3-DOF robotic manipulator are used as examples to demonstrate the effectiveness of the proposed approach.
2017-01-02
heuristic , which is a local search heuristic . We start with a partition S1, . . . , SA of the requirements, where Sa represents the requirements...in what order the aircraft will pickup and deliver its assigned requirements), using a combination of heuristics and column generation. Through...priority and short-notice missions. The planning of airlift missions is of critical importance to USTRANSCOM, for two reasons. First, due to the time
Mobile Robots Path Planning Using the Overall Conflict Resolution and Time Baseline Coordination
Yong Ma
2014-01-01
Full Text Available This paper aims at resolving the path planning problem in a time-varying environment based on the idea of overall conflict resolution and the algorithm of time baseline coordination. The basic task of the introduced path planning algorithms is to fulfill the automatic generation of the shortest paths from the defined start poses to their end poses with consideration of generous constraints for multiple mobile robots. Building on this, by using the overall conflict resolution, within the polynomial based paths, we take into account all the constraints including smoothness, motion boundary, kinematics constraints, obstacle avoidance, and safety constraints among robots together. And time baseline coordination algorithm is proposed to process the above formulated problem. The foremost strong point is that much time can be saved with our approach. Numerical simulations verify the effectiveness of our approach.
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.
Aircraft path planning for optimal imaging using dynamic cost functions
Christie, Gordon; Chaudhry, Haseeb; Kochersberger, Kevin
2015-05-01
Unmanned aircraft development has accelerated with recent technological improvements in sensing and communications, which has resulted in an "applications lag" for how these aircraft can best be utilized. The aircraft are becoming smaller, more maneuverable and have longer endurance to perform sensing and sampling missions, but operating them aggressively to exploit these capabilities has not been a primary focus in unmanned systems development. This paper addresses a means of aerial vehicle path planning to provide a realistic optimal path in acquiring imagery for structure from motion (SfM) reconstructions and performing radiation surveys. This method will allow SfM reconstructions to occur accurately and with minimal flight time so that the reconstructions can be executed efficiently. An assumption is made that we have 3D point cloud data available prior to the flight. A discrete set of scan lines are proposed for the given area that are scored based on visibility of the scene. Our approach finds a time-efficient path and calculates trajectories between scan lines and over obstacles encountered along those scan lines. Aircraft dynamics are incorporated into the path planning algorithm as dynamic cost functions to create optimal imaging paths in minimum time. Simulations of the path planning algorithm are shown for an urban environment. We also present our approach for image-based terrain mapping, which is able to efficiently perform a 3D reconstruction of a large area without the use of GPS data.
Ma, Yong; Wang, Hongwei; Zamirian, M.
2012-01-01
We present a new approach containing two steps to determine conflict-free paths for mobile objects in two and three dimensions with moving obstacles. Firstly, the shortest path of each object is set as goal function which is subject to collision-avoidance criterion, path smoothness, and velocity and acceleration constraints. This problem is formulated as calculus of variation problem (CVP). Using parametrization method, CVP is converted to time-varying nonlinear programming problems (TNLPP) and then resolved. Secondly, move sequence of object is assigned by priority scheme; conflicts are resolved by multilevel conflict resolution strategy. Approach efficiency is confirmed by numerical examples. -- Highlights: ► Approach with parametrization method and conflict resolution strategy is proposed. ► Approach fits for multi-object paths planning in two and three dimensions. ► Single object path planning and multi-object conflict resolution are orderly used. ► Path of each object obtained with parameterization method in the first phase. ► Conflict-free paths gained by multi-object conflict resolution in the second phase.
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.
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-l......-like reference algorithm. Experiments are run on a distributed-memory MIMD class Meiko parallel computer....
Mission-directed path planning for planetary rover exploration
Tompkins, Paul
2005-07-01
Robotic rovers uniquely benefit planetary exploration---they enable regional exploration with the precision of in-situ measurements, a combination impossible from an orbiting spacecraft or fixed lander. Mission planning for planetary rover exploration currently utilizes sophisticated software for activity planning and scheduling, but simplified path planning and execution approaches tailored for localized operations to individual targets. This approach is insufficient for the investigation of multiple, regionally distributed targets in a single command cycle. Path planning tailored for this task must consider the impact of large scale terrain on power, speed and regional access; the effect of route timing on resource availability; the limitations of finite resource capacity and other operational constraints on vehicle range and timing; and the mutual influence between traverses and upstream and downstream stationary activities. Encapsulating this reasoning in an efficient autonomous planner would allow a rover to continue operating rationally despite significant deviations from an initial plan. This research presents mission-directed path planning that enables an autonomous, strategic reasoning capability for robotic explorers. Planning operates in a space of position, time and energy. Unlike previous hierarchical approaches, it treats these dimensions simultaneously to enable globally-optimal solutions. The approach calls on a near incremental search algorithm designed for planning and re-planning under global constraints, in spaces of higher than two dimensions. Solutions under this method specify routes that avoid terrain obstacles, optimize the collection and use of rechargable energy, satisfy local and global mission constraints, and account for the time and energy of interleaved mission activities. Furthermore, the approach efficiently re-plans in response to updates in vehicle state and world models, and is well suited to online operation aboard a robot
Solving a Hamiltonian Path Problem with a bacterial computer
Baumgardner, Jordan; Acker, Karen; Adefuye, Oyinade; Crowley, Samuel Thomas; DeLoache, Will; Dickson, James O; Heard, Lane; Martens, Andrew T; Morton, Nickolaus; Ritter, Michelle; Shoecraft, Amber; Treece, Jessica; Unzicker, Matthew; Valencia, Amanda; Waters, Mike; Campbell, A Malcolm; Heyer, Laurie J; Poet, Jeffrey L; Eckdahl, Todd T
2009-01-01
Background The Hamiltonian Path Problem asks whether there is a route in a directed graph from a beginning node to an ending node, visiting each node exactly once. The Hamiltonian Path Problem is NP complete, achieving surprising computational complexity with modest increases in size. This challenge has inspired researchers to broaden the definition of a computer. DNA computers have been developed that solve NP complete problems. Bacterial computers can be programmed by constructing genetic circuits to execute an algorithm that is responsive to the environment and whose result can be observed. Each bacterium can examine a solution to a mathematical problem and billions of them can explore billions of possible solutions. Bacterial computers can be automated, made responsive to selection, and reproduce themselves so that more processing capacity is applied to problems over time. Results We programmed bacteria with a genetic circuit that enables them to evaluate all possible paths in a directed graph in order to find a Hamiltonian path. We encoded a three node directed graph as DNA segments that were autonomously shuffled randomly inside bacteria by a Hin/hixC recombination system we previously adapted from Salmonella typhimurium for use in Escherichia coli. We represented nodes in the graph as linked halves of two different genes encoding red or green fluorescent proteins. Bacterial populations displayed phenotypes that reflected random ordering of edges in the graph. Individual bacterial clones that found a Hamiltonian path reported their success by fluorescing both red and green, resulting in yellow colonies. We used DNA sequencing to verify that the yellow phenotype resulted from genotypes that represented Hamiltonian path solutions, demonstrating that our bacterial computer functioned as expected. Conclusion We successfully designed, constructed, and tested a bacterial computer capable of finding a Hamiltonian path in a three node directed graph. This proof
Solving a Hamiltonian Path Problem with a bacterial computer
Treece Jessica
2009-07-01
Full Text Available Abstract Background The Hamiltonian Path Problem asks whether there is a route in a directed graph from a beginning node to an ending node, visiting each node exactly once. The Hamiltonian Path Problem is NP complete, achieving surprising computational complexity with modest increases in size. This challenge has inspired researchers to broaden the definition of a computer. DNA computers have been developed that solve NP complete problems. Bacterial computers can be programmed by constructing genetic circuits to execute an algorithm that is responsive to the environment and whose result can be observed. Each bacterium can examine a solution to a mathematical problem and billions of them can explore billions of possible solutions. Bacterial computers can be automated, made responsive to selection, and reproduce themselves so that more processing capacity is applied to problems over time. Results We programmed bacteria with a genetic circuit that enables them to evaluate all possible paths in a directed graph in order to find a Hamiltonian path. We encoded a three node directed graph as DNA segments that were autonomously shuffled randomly inside bacteria by a Hin/hixC recombination system we previously adapted from Salmonella typhimurium for use in Escherichia coli. We represented nodes in the graph as linked halves of two different genes encoding red or green fluorescent proteins. Bacterial populations displayed phenotypes that reflected random ordering of edges in the graph. Individual bacterial clones that found a Hamiltonian path reported their success by fluorescing both red and green, resulting in yellow colonies. We used DNA sequencing to verify that the yellow phenotype resulted from genotypes that represented Hamiltonian path solutions, demonstrating that our bacterial computer functioned as expected. Conclusion We successfully designed, constructed, and tested a bacterial computer capable of finding a Hamiltonian path in a three node
The shortest-path problem analysis and comparison of methods
Ortega-Arranz, Hector; Gonzalez-Escribano, Arturo
2014-01-01
Many applications in different domains need to calculate the shortest-path between two points in a graph. In this paper we describe this shortest path problem in detail, starting with the classic Dijkstra's algorithm and moving to more advanced solutions that are currently applied to road network routing, including the use of heuristics and precomputation techniques. Since several of these improvements involve subtle changes to the search space, it may be difficult to appreciate their benefits in terms of time or space requirements. To make methods more comprehensive and to facilitate their co
Safe Maritime Autonomous Path Planning in a High Sea State
Ono, Masahiro; Quadrelli, Marco; Huntsberger, Terrance L.
2014-01-01
This paper presents a path planning method for sea surface vehicles that prevents capsizing and bow-diving in a high sea-state. A key idea is to use response amplitude operators (RAOs) or, in control terminology, the transfer functions from a sea state to a vessel's motion, in order to find a set of speeds and headings that results in excessive pitch and roll oscillations. This information is translated to arithmetic constraints on the ship's velocity, which are passed to a model predictive control (MPC)-based path planner to find a safe and optimal path that achieves specified goals. An obstacle avoidance capability is also added to the path planner. The proposed method is demonstrated by simulations.
Reasoning on the Self-Organizing Incremental Associative Memory for Online Robot Path Planning
Kawewong, Aram; Honda, Yutaro; Tsuboyama, Manabu; Hasegawa, Osamu
Robot path-planning is one of the important issues in robotic navigation. This paper presents a novel robot path-planning approach based on the associative memory using Self-Organizing Incremental Neural Networks (SOINN). By the proposed method, an environment is first autonomously divided into a set of path-fragments by junctions. Each fragment is represented by a sequence of preliminarily generated common patterns (CPs). In an online manner, a robot regards the current path as the associative path-fragments, each connected by junctions. The reasoning technique is additionally proposed for decision making at each junction to speed up the exploration time. Distinct from other methods, our method does not ignore the important information about the regions between junctions (path-fragments). The resultant number of path-fragments is also less than other method. Evaluation is done via Webots physical 3D-simulated and real robot experiments, where only distance sensors are available. Results show that our method can represent the environment effectively; it enables the robot to solve the goal-oriented navigation problem in only one episode, which is actually less than that necessary for most of the Reinforcement Learning (RL) based methods. The running time is proved finite and scales well with the environment. The resultant number of path-fragments matches well to the environment.
Domokos Kiss
2017-01-01
Full Text Available In this paper we introduce a novel method for obtaining good quality paths for autonomous road vehicles (e.g., cars or buses in narrow environments. There are many traffic situations in urban scenarios where nontrivial maneuvering in narrow places is necessary. Navigating in cluttered parking lots or having to avoid obstacles blocking the way and finding a detour even in narrow streets are challenging, especially if the vehicle has large dimensions like a bus. We present a combined approximation-based approach to solve the path planning problem in such situations. Our approach consists of a global planner which generates a preliminary path consisting of straight and turning-in-place primitives and a local planner which is used to make the preliminary path feasible to car-like vehicles. The approximation methodology is well known in the literature; however, both components proposed in this paper differ from existing similar planning methods. The approximation process with the proposed local planner is proven to be convergent for any preliminary global paths. The resulting path has continuous curvature which renders our method well suited for application on real vehicles. Simulation experiments show that the proposed method outperforms similar approaches in terms of path quality in complicated planning tasks.
Path Planning & Measurement Registration for Robotic Structural Asset Monitoring
Pierce , Stephen Gareth; Macleod , Charles Norman; Dobie , Gordon; Summan , Rahul
2014-01-01
International audience; The move to increased levels of autonomy for robotic delivery of inspection for asset monitoring, demands a structured approach to path planning and measurement data presentation that greatly surpasses the more ad‐,hoc approach typically employed by remotely controlled, but manually driven robotic inspection vehicles. The authors describe a traditional CAD/CAM approach to motion planning (as used in machine tool operation) which has numerous benefits including the...
Sensor-Oriented Path Planning for Multiregion Surveillance with a Single Lightweight UAV SAR.
Li, Jincheng; Chen, Jie; Wang, Pengbo; Li, Chunsheng
2018-02-11
In the surveillance of interested regions by unmanned aerial vehicle (UAV), system performance relies greatly on the motion control strategy of the UAV and the operation characteristics of the onboard sensors. This paper investigates the 2D path planning problem for the lightweight UAV synthetic aperture radar (SAR) system in an environment of multiple regions of interest (ROIs), the sizes of which are comparable to the radar swath width. Taking into account the special requirements of the SAR system on the motion of the platform, we model path planning for UAV SAR as a constrained multiobjective optimization problem (MOP). Based on the fact that the UAV route can be designed in the map image, an image-based path planner is proposed in this paper. First, the neighboring ROIs are merged by the morphological operation. Then, the parts of routes for data collection of the ROIs can be located according to the geometric features of the ROIs and the observation geometry of UAV SAR. Lastly, the route segments for ROIs surveillance are connected by a path planning algorithm named the sampling-based sparse A* search (SSAS) algorithm. Simulation experiments in real scenarios demonstrate that the proposed sensor-oriented path planner can improve the reconnaissance performance of lightweight UAV SAR greatly compared with the conventional zigzag path planner.
Sensor-Oriented Path Planning for Multiregion Surveillance with a Single Lightweight UAV SAR
Li, Jincheng; Chen, Jie; Wang, Pengbo; Li, Chunsheng
2018-01-01
In the surveillance of interested regions by unmanned aerial vehicle (UAV), system performance relies greatly on the motion control strategy of the UAV and the operation characteristics of the onboard sensors. This paper investigates the 2D path planning problem for the lightweight UAV synthetic aperture radar (SAR) system in an environment of multiple regions of interest (ROIs), the sizes of which are comparable to the radar swath width. Taking into account the special requirements of the SAR system on the motion of the platform, we model path planning for UAV SAR as a constrained multiobjective optimization problem (MOP). Based on the fact that the UAV route can be designed in the map image, an image-based path planner is proposed in this paper. First, the neighboring ROIs are merged by the morphological operation. Then, the parts of routes for data collection of the ROIs can be located according to the geometric features of the ROIs and the observation geometry of UAV SAR. Lastly, the route segments for ROIs surveillance are connected by a path planning algorithm named the sampling-based sparse A* search (SSAS) algorithm. Simulation experiments in real scenarios demonstrate that the proposed sensor-oriented path planner can improve the reconnaissance performance of lightweight UAV SAR greatly compared with the conventional zigzag path planner. PMID:29439447
Nonlinear radiation transport problems involving widely varying mean free paths
Chapline, G. Jr.; Wood, L.
1976-01-01
In this report a method is given for modifying the Monte-Carlo approach so that one can accurately treat problems that involve both large and small mean free paths. This method purports to offer the advantages of the general Monte Carlo technique as far as relatively great accuracy of simulation of microscopic physical phenomena is concerned, and the advantage of a diffusion theory approach as far as decent time steps in thick problems are concerned; it does suffer from something of the statistical fluctuation problems of the Monte Carlo, although in analytically attenuated and modified form
The problem of the driverless vehicle specified path stability control
Buznikov, S. E.; Endachev, D. V.; Elkin, D. S.; Strukov, V. O.
2018-02-01
Currently the effort of many leading foreign companies is focused on creation of driverless transport for transportation of cargo and passengers. Among many practical problems arising while creating driverless vehicles, the problem of the specified path stability control occupies a central place. The purpose of this paper is formalization of the problem in question in terms of the quadratic functional of the control quality, the comparative analysis of the possible solutions and justification of the choice of the optimum technical solution. As square value of the integral of the deviation from the specified path is proposed as the quadratic functional of the control quality. For generation of the set of software and hardware solution variants the Zwicky “morphological box” method is used within the hardware and software environments. The heading control algorithms use the wheel steering angle data and the deviation from the lane centerline (specified path) calculated based on the navigation data and the data from the video system. Where the video system does not detect the road marking, the control is carried out based on the wheel navigation system data and where recognizable road marking exits - based on to the video system data. The analysis of the test results allows making the conclusion that the application of the combined navigation system algorithms that provide quasi-optimum solution of the problem while meeting the strict functional limits for the technical and economic indicators of the driverless vehicle control system under development is effective.
Solving fuzzy shortest path problem by genetic algorithm
Syarif, A.; Muludi, K.; Adrian, R.; Gen, M.
2018-03-01
Shortest Path Problem (SPP) is known as one of well-studied fields in the area Operations Research and Mathematical Optimization. It has been applied for many engineering and management designs. The objective is usually to determine path(s) in the network with minimum total cost or traveling time. In the past, the cost value for each arc was usually assigned or estimated as a deteministic value. For some specific real world applications, however, it is often difficult to determine the cost value properly. One way of handling such uncertainty in decision making is by introducing fuzzy approach. With this situation, it will become difficult to solve the problem optimally. This paper presents the investigations on the application of Genetic Algorithm (GA) to a new SPP model in which the cost values are represented as Triangular Fuzzy Number (TFN). We adopts the concept of ranking fuzzy numbers to determine how good the solutions. Here, by giving his/her degree value, the decision maker can determine the range of objective value. This would be very valuable for decision support system in the real world applications.Simulation experiments were carried out by modifying several test problems with 10-25 nodes. It is noted that the proposed approach is capable attaining a good solution with different degree of optimism for the tested problems.
Tsauo, Jiaywei, E-mail: 80732059@qq.com; Luo, Xuefeng, E-mail: luobo-913@126.com [West China Hospital of Sichuan University, Institute of Interventional Radiology (China); Ye, Linchao, E-mail: linchao.ye@siemens.com [Siemens Ltd, Healthcare Sector (China); Li, Xiao, E-mail: simonlixiao@gmail.com [West China Hospital of Sichuan University, Institute of Interventional Radiology (China)
2015-06-15
PurposeThis study was designed to report our results with a modified technique of three-dimensional (3D) path planning software assisted transjugular intrahepatic portosystemic shunt (TIPS).Methods3D path planning software was recently developed to facilitate TIPS creation by using two carbon dioxide portograms acquired at least 20° apart to generate a 3D path for overlay needle guidance. However, one shortcoming is that puncturing along the overlay would be technically impossible if the angle of the liver access set and the angle of the 3D path are not the same. To solve this problem, a prototype 3D path planning software was fitted with a utility to calculate the angle of the 3D path. Using this, we modified the angle of the liver access set accordingly during the procedure in ten patients.ResultsFailure for technical reasons occurred in three patients (unsuccessful wedged hepatic venography in two cases, software technical failure in one case). The procedure was successful in the remaining seven patients, and only one needle pass was required to obtain portal vein access in each case. The course of puncture was comparable to the 3D path in all patients. No procedure-related complication occurred following the procedures.ConclusionsAdjusting the angle of the liver access set to match the angle of the 3D path determined by the software appears to be a favorable modification to the technique of 3D path planning software assisted TIPS.
Image-based path planning for automated virtual colonoscopy navigation
Hong, Wei
2008-03-01
Virtual colonoscopy (VC) is a noninvasive method for colonic polyp screening, by reconstructing three-dimensional models of the colon using computerized tomography (CT). In virtual colonoscopy fly-through navigation, it is crucial to generate an optimal camera path for efficient clinical examination. In conventional methods, the centerline of the colon lumen is usually used as the camera path. In order to extract colon centerline, some time consuming pre-processing algorithms must be performed before the fly-through navigation, such as colon segmentation, distance transformation, or topological thinning. In this paper, we present an efficient image-based path planning algorithm for automated virtual colonoscopy fly-through navigation without the requirement of any pre-processing. Our algorithm only needs the physician to provide a seed point as the starting camera position using 2D axial CT images. A wide angle fisheye camera model is used to generate a depth image from the current camera position. Two types of navigational landmarks, safe regions and target regions are extracted from the depth images. Camera position and its corresponding view direction are then determined using these landmarks. The experimental results show that the generated paths are accurate and increase the user comfort during the fly-through navigation. Moreover, because of the efficiency of our path planning algorithm and rendering algorithm, our VC fly-through navigation system can still guarantee 30 FPS.
Cai, Wenyu; Zhang, Meiyan; Zheng, Yahong Rosa
2017-07-11
This paper investigates the task assignment and path planning problem for multiple AUVs in three dimensional (3D) underwater wireless sensor networks where nonholonomic motion constraints of underwater AUVs in 3D space are considered. The multi-target task assignment and path planning problem is modeled by the Multiple Traveling Sales Person (MTSP) problem and the Genetic Algorithm (GA) is used to solve the MTSP problem with Euclidean distance as the cost function and the Tour Hop Balance (THB) or Tour Length Balance (TLB) constraints as the stop criterion. The resulting tour sequences are mapped to 2D Dubins curves in the X - Y plane, and then interpolated linearly to obtain the Z coordinates. We demonstrate that the linear interpolation fails to achieve G 1 continuity in the 3D Dubins path for multiple targets. Therefore, the interpolated 3D Dubins curves are checked against the AUV dynamics constraint and the ones satisfying the constraint are accepted to finalize the 3D Dubins curve selection. Simulation results demonstrate that the integration of the 3D Dubins curve with the MTSP model is successful and effective for solving the 3D target assignment and path planning problem.
Wenyu Cai
2017-07-01
Full Text Available This paper investigates the task assignment and path planning problem for multiple AUVs in three dimensional (3D underwater wireless sensor networks where nonholonomic motion constraints of underwater AUVs in 3D space are considered. The multi-target task assignment and path planning problem is modeled by the Multiple Traveling Sales Person (MTSP problem and the Genetic Algorithm (GA is used to solve the MTSP problem with Euclidean distance as the cost function and the Tour Hop Balance (THB or Tour Length Balance (TLB constraints as the stop criterion. The resulting tour sequences are mapped to 2D Dubins curves in the X − Y plane, and then interpolated linearly to obtain the Z coordinates. We demonstrate that the linear interpolation fails to achieve G 1 continuity in the 3D Dubins path for multiple targets. Therefore, the interpolated 3D Dubins curves are checked against the AUV dynamics constraint and the ones satisfying the constraint are accepted to finalize the 3D Dubins curve selection. Simulation results demonstrate that the integration of the 3D Dubins curve with the MTSP model is successful and effective for solving the 3D target assignment and path planning problem.
Path planning in uncertain flow fields using ensemble method
Wang, Tong; Le Maî tre, Olivier P.; Hoteit, Ibrahim; Knio, Omar
2016-01-01
, we predict the path that minimizes the travel time by solving a boundary value problem (BVP), based on the Pontryagin maximum principle. A family of backward-in-time trajectories starting at the end position is used to generate suitable initial values
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.
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.
Energy-Aware Path Planning for UAS Persistent Sampling and Surveillance
Shaw-Cortez, Wenceslao
The focus of this work is to develop an energy-aware path planning algorithm that maximizes UAS endurance, while performing sampling and surveillance missions in a known, stationary wind environment. The energy-aware aspect is specifically tailored to extract energy from the wind to reduce thrust use, thereby increasing aircraft endurance. Wind energy extraction is performed by static soaring and dynamic soaring. Static soaring involves using upward wind currents to increase altitude and potential energy. Dynamic soaring involves taking advantage of wind gradients to exchange potential and kinetic energy. The path planning algorithm developed in this work uses optimization to combine these soaring trajectories with the overarching sampling and surveillance mission. The path planning algorithm uses a simplified aircraft model to tractably optimize soaring trajectories. This aircraft model is presented and along with the derivation of the equations of motion. A nonlinear program is used to create the soaring trajectories based on a given optimization problem. This optimization problem is defined using a heuristic decision tree, which defines appropriate problems given a sampling and surveillance mission and a wind model. Simulations are performed to assess the path planning algorithm. The results are used to identify properties of soaring trajectories as well as to determine what wind conditions support minimal thrust soaring. Additional results show how the path planning algorithm can be tuned between maximizing aircraft endurance and performing the sampling and surveillance mission. A means of trajectory stitching is demonstrated to show how the periodic soaring segments can be combined together to provide a full solution to an infinite/long horizon problem.
Research on Navigation Path Planning for An Underground Load Haul Dump
Qi Yulong
2015-11-01
Full Text Available The improved A * algorithm is a method of navigation path planning for articulated underground scrapers. Firstly, an environment model based on a mining Geographic Information System (GIS map is established, and then combined with improved A * algorithm, the underground global path planning problem of the intelligent Load Haul Dump (LHD is solved. In this paper, for the articulated structure, the method of expanding nodes by articulation angle is adopted to make expanded nodes meet the trajectory characteristics. In addition, collision threat cost is introduced in the evaluation function to avoid collisions between the LHD and the tunnel walls. As peran analysis of the simulation test to verify the effectiveness of the improved A * algorithm and a comparison with the traditional A * algorithm, the improved A * algorithm can enhance search efficiency. Acontrast of multiple sets of test parameters suggests that when the price weighted coefficient of collision is 0.2, the shortest path can be derived to avoid impact. Finally, tracking results indicate that the proposed algorithm for navigation path planning can maintain the tracking error to within 0.2 m in line with the structural characteristics of the scraper in the laboratory environment to realize the path planning of unmanned scrapers and trajectory tracking. Moreover, the algorithm can enhance the safety of scrapers and prevent roadway collisions. The feasibility and practicality of the proposed method is verified in this work.
Globally Optimal Path Planning with Anisotropic Running Costs
2013-03-01
Eikonal equation and has numerous applications, for exam- ple, in path planning, computational geometry, computer vision, and image enhancement...Sethian 1999b]. Numerical methods for solving the Eikonal equation include Tsitsiklis’ control-theoretic algorithm [Tsitsiklis 1995], Fast Marching Methods...methods for Eikonal equations on triangular meshes, SIAM J. Numer. Anal. 45(1), 83—107. Rowe, M. P., Sidhu, H. S. & Mercer, G. N. (2009) Military
Imen Chaari
2017-03-01
Full Text Available This article presents the results of the 2-year iroboapp research project that aims at devising path planning algorithms for large grid maps with much faster execution times while tolerating very small slacks with respect to the optimal path. We investigated both exact and heuristic methods. We contributed with the design, analysis, evaluation, implementation and experimentation of several algorithms for grid map path planning for both exact and heuristic methods. We also designed an innovative algorithm called relaxed A-star that has linear complexity with relaxed constraints, which provides near-optimal solutions with an extremely reduced execution time as compared to A-star. We evaluated the performance of the different algorithms and concluded that relaxed A-star is the best path planner as it provides a good trade-off among all the metrics, but we noticed that heuristic methods have good features that can be exploited to improve the solution of the relaxed exact method. This led us to design new hybrid algorithms that combine our relaxed A-star with heuristic methods which improve the solution quality of relaxed A-star at the cost of slightly higher execution time, while remaining much faster than A* for large-scale problems. Finally, we demonstrate how to integrate the relaxed A-star algorithm in the robot operating system as a global path planner and show that it outperforms its default path planner with an execution time 38% faster on average.
Shore-based Path Planning for Marine Vehicles Using a Model of Ocean Currents
National Aeronautics and Space Administration — Develop path planning methods that incorporate an approximate model of ocean currents in path planning for a range of autonomous marine vehicles such as surface...
Planning of optimal work path for minimizing exposure dose during radiation work in radwaste storage
Kim, Yoon Hyuk; Park, Won Man; Kim, Kyung Soo; Whang, Joo Ho
2005-01-01
Since the safety of nuclear power plant has been becoming a big social issue, the exposure dose of radiation for workers has been one of the important factors concerning the safety problem. The existing calculation methods of radiation dose used in the planning of radiation work assume that dose rate dose not depend on the location within a work space, thus the variation of exposure dose by different work path is not considered. In this study, a modified numerical method was presented to estimate the exposure dose during radiation work in radwaste storage considering the effects of the distance between a worker and sources. And a new numerical algorithm was suggested to search the optimal work path minimizing the exposure dose in pre-defined work space with given radiation sources. Finally, a virtual work simulation program was developed to visualize the exposure dose of radiation during radiation works in radwaste storage and provide the capability of simulation for work planning. As a numerical example, a test radiation work was simulated under given space and two radiation sources, and the suggested optimal work path was compared with three predefined work paths. The optimal work path obtained in the study could reduce the exposure dose for the given test work. Based on the results, the developed numerical method and simulation program could be useful tools in the planning of radiation work
PSO-Based Robot Path Planning for Multisurvivor Rescue in Limited Survival Time
N. Geng
2014-01-01
Full Text Available Since the strength of a trapped person often declines with time in urgent and dangerous circumstances, adopting a robot to rescue as many survivors as possible in limited time is of considerable significance. However, as one key issue in robot navigation, how to plan an optimal rescue path of a robot has not yet been fully solved. This paper studies robot path planning for multisurvivor rescue in limited survival time using a representative heuristic, particle swarm optimization (PSO. First, the robot path planning problem including multiple survivors is formulated as a discrete optimization one with high constraint, where the number of rescued persons is taken as the unique objective function, and the strength of a trapped person is used to constrain the feasibility of a path. Then, a new integer PSO algorithm is presented to solve the mathematical model, and several new operations, such as the update of a particle, the insertion and inversion operators, and the rapidly local search method, are incorporated into the proposed algorithm to improve its effectiveness. Finally, the simulation results demonstrate the capacity of our method in generating optimal paths with high quality.
Urban Planning Problems of Agglomerations
Olenkov, V. D.; Tazeev, N. T.
2017-11-01
The article explores the state of the air basin of the Chelyabinsk agglomeration and gives the examples of solutions for the pollution problems from the point of view of city planning. The main features and structure of the modern urban agglomerations are considered, the methods for determining their boundaries are studied and the main problems are identified. The study of the boundaries and territorial structure of the Chelyabinsk urban agglomeration is conducted, and a general description of the territory is given. The data on the change in the volume of pollutant emissions into the atmosphere and the index of atmospheric pollution for the period 2003-2015 are given basing on the annual comprehensive reports regarding the state of the environment. The review of the world experience of city-planning actions on the decision of ecological problems is carried out. The most suitable ways for the ecological problems solving in the Chelyabinsk agglomeration are considered. The authors give recommendations for the ecological situation improving in the territory of the Chelyabinsk agglomeration.
Robot path planning using expert systems and machine vision
Malone, Denis E.; Friedrich, Werner E.
1992-02-01
This paper describes a system developed for the robotic processing of naturally variable products. In order to plan the robot motion path it was necessary to use a sensor system, in this case a machine vision system, to observe the variations occurring in workpieces and interpret this with a knowledge based expert system. The knowledge base was acquired by carrying out an in-depth study of the product using examination procedures not available in the robotic workplace and relates the nature of the required path to the information obtainable from the machine vision system. The practical application of this system to the processing of fish fillets is described and used to illustrate the techniques.
A constraint programming solution for the military unit path finding problem
Leenen, L
2012-01-01
Full Text Available In this chapter the authors present an algorithm to solve the Dynamic Military Unit Path Finding Problem (DMUPFP) which is based on Stentz’s well-known D* algorithm to solve dynamic path finding problems. The Military Unit Path Finding Problem...
Research and Implementation of Robot Path Planning Based onVSLAM
Wang Zi-Qiang
2018-01-01
Full Text Available In order to solve the problem of warehouse logistics robots planpath in different scenes, this paper proposes a method based on visual simultaneous localization and mapping (VSLAM to build grid map of different scenes and use A* algorithm to plan path on the grid map. Firstly, we use VSLAMto reconstruct the environment in three-dimensionally. Secondly, based on the three-dimensional environment data, we calculate the accessibility of each grid to prepare occupied grid map (OGM for terrain description. Rely on the terrain information, we use the A* algorithm to solve path planning problem. We also optimize the A* algorithm and improve algorithm efficiency. Lastly, we verify the effectiveness and reliability of the proposed method by simulation and experimental results.
Strategic Path Planning by Sequential Parametric Bayesian Decisions
Baro Hyun
2013-11-01
Full Text Available The objective of this research is to generate a path for a mobile agent that carries sensors used for classification, where the path is to optimize strategic objectives that account for misclassification and the consequences of misclassification, and where the weights assigned to these consequences are chosen by a strategist. We propose a model that accounts for the interaction between the agent kinematics (i.e., the ability to move, informatics (i.e., the ability to process data to information, classification (i.e., the ability to classify objects based on the information, and strategy (i.e., the mission objective. Within this model, we pose and solve a sequential decision problem that accounts for strategist preferences and the solution to the problem yields a sequence of kinematic decisions of a moving agent. The solution of the sequential decision problem yields the following flying tactics: “approach only objects whose suspected identity matters to the strategy”. These tactics are numerically illustrated in several scenarios.
The Robot Path Planning Based on Improved Artificial Fish Swarm Algorithm
Yi Zhang
2016-01-01
Full Text Available Path planning is critical to the efficiency and fidelity of robot navigation. The solution of robot path planning is to seek a collision-free and the shortest path from the start node to target node. In this paper, we propose a new improved artificial fish swarm algorithm (IAFSA to process the mobile robot path planning problem in a real environment. In IAFSA, an attenuation function is introduced to improve the visual of standard AFSA and get the balance of global search and local search; also, an adaptive operator is introduced to enhance the adaptive ability of step. Besides, a concept of inertia weight factor is proposed in IAFSA inspired by PSO intelligence algorithm to improve the convergence rate and accuracy of IAFSA. Five unconstrained optimization test functions are given to illustrate the strong searching ability and ideal convergence of IAFSA. Finally, the ROS (robot operation system based experiment is carried out on a Pioneer 3-DX mobile robot; the experiment results also show the superiority of IAFSA.
Disordered and Multiple Destinations Path Planning Methods for Mobile Robot in Dynamic Environment
Yong-feng Dong
2016-01-01
Full Text Available In the smart home environment, aiming at the disordered and multiple destinations path planning, the sequencing rule is proposed to determine the order of destinations. Within each branching process, the initial feasible path set is generated according to the law of attractive destination. A sinusoidal adaptive genetic algorithm is adopted. It can calculate the crossover probability and mutation probability adaptively changing with environment at any time. According to the cultural-genetic algorithm, it introduces the concept of reducing turns by parallelogram and reducing length by triangle in the belief space, which can improve the quality of population. And the fallback strategy can help to jump out of the “U” trap effectively. The algorithm analyses the virtual collision in dynamic environment with obstacles. According to the different collision types, different strategies are executed to avoid obstacles. The experimental results show that cultural-genetic algorithm can overcome the problems of premature and convergence of original algorithm effectively. It can avoid getting into the local optimum. And it is more effective for mobile robot path planning. Even in complex environment with static and dynamic obstacles, it can avoid collision safely and plan an optimal path rapidly at the same time.
Solving the replacement paths problem for planar directed graphs in O(n logn) time
Wulff-Nilsen, Christian
2010-01-01
In a graph G with non-negative edge lengths, let P be a shortest path from a vertex s to a vertex t. We consider the problem of computing, for each edge e on P, the length of a shortest path in G from s to t that avoids e. This is known as the replacement paths problem. We give a linearspace...
Autonomous path planning solution for industrial robot manipulator using backpropagation algorithm
PeiJiang Yuan
2015-12-01
Full Text Available Here, we propose an autonomous path planning solution using backpropagation algorithm. The mechanism of movement used by humans in controlling their arms is analyzed and then applied to control a robot manipulator. Autonomous path planning solution is a numerical method. The model of industrial robot manipulator used in this article is a KUKA KR 210 R2700 EXTRA robot. In order to show the performance of the autonomous path planning solution, an experiment validation of path tracking is provided. Experiment validation consists of implementation of the autonomous path planning solution and the control of physical robot. The process of converging to target solution is provided. The mean absolute error of position for tool center point is also analyzed. Comparison between autonomous path planning solution and the numerical methods based on Newton–Raphson algorithm is provided to demonstrate the efficiency and accuracy of the autonomous path planning solution.
Path planning of master-slave manipulator using graphic simulator
Lee, J. Y.; Kim, S. H.; Song, T. K.; Park, B. S.; Yoon, J. S.
2002-01-01
To handle the high level radioactive materials such as spent fuels remotely, the master-slave manipulator is generally used as a remote handling equipment in the hot cell. To analyze the motion and to implement the training system by virtual reality technology, the simulator for M-S manipulator using the computer graphics is developed. The parts are modelled in 3-D graphics, assembled, and kinematics are assigned. The inverse kinematics of the manipulator is defined, and the slave of manipulator is coupled with master by the manipulator's specification. Also, the virtual work cell is implemented in the graphical environment which is the same as the real environment and the path planning method using the function of the collision detection for a manipulator are proposed. This graphic simulator of manipulator can be effectively used in designing of the maintenance processes for the hot cell equipment and enhance the reliability of the spent fuel management
Autonomous guided vehicles methods and models for optimal path planning
Fazlollahtabar, Hamed
2015-01-01
This book provides readers with extensive information on path planning optimization for both single and multiple Autonomous Guided Vehicles (AGVs), and discusses practical issues involved in advanced industrial applications of AGVs. After discussing previously published research in the field and highlighting the current gaps, it introduces new models developed by the authors with the goal of reducing costs and increasing productivity and effectiveness in the manufacturing industry. The new models address the increasing complexity of manufacturing networks, due for example to the adoption of flexible manufacturing systems that involve automated material handling systems, robots, numerically controlled machine tools, and automated inspection stations, while also considering the uncertainty and stochastic nature of automated equipment such as AGVs. The book discusses and provides solutions to important issues concerning the use of AGVs in the manufacturing industry, including material flow optimization with A...
Making planned paths look more human-like in humanoid robot manipulation planning
Zacharias, F.; Schlette, C.; Schmidt, F.
2011-01-01
It contradicts the human's expectations when humanoid robots move awkwardly during manipulation tasks. The unnatural motion may be caused by awkward start or goal configurations or by probabilistic path planning processes that are often used. This paper shows that the choice of an arm's target...... for the robot arm....
Mathematical optimization for planning and design of cycle paths
LiÑan Ruiz, R.J.; Perez Aracil, J.; Cabrera Cañizares, V.
2016-07-01
The daily need for citizens to move for different activities, whatever its nature, has been greatly affected by the changes. The advantages resulting from the inclusion of the bicycle as a mode of transport and the proliferation of its use among citizens are numerous and extend both in the field of urban mobility and sustainable development.Currently, there are a number of programs for the implementation, promotion or increased public participation related to cycling in cities. But ultimately, each and every one of these initiatives have the same goal, to create a mesh of effective, useful and cycling trails that allow the use of bicycles in preferred routes with high guarantees of security, incorporating bicycle model intermodal urban transport.With the gradual implementation of bike lanes, many people have begun to use them to get around the city. But everything again needs a period of adaptation, and the reality is that the road network for these vehicles is full of obstacles to the rider. The current situation has led to the proposal that many kilometers of cycle paths needed to supply the demand of this mode of transport and, if implemented and planned are correct and sufficient.This paper presents a mathematical programming model for optimal design of a network for cyclists is presented. Specifically, the model determines a network of bicycle infrastructure, appropriate to the characteristics of a network of existing roads.As an application of the proposed model, the result of these experiments give a number of useful conclusions for planning and designing networks of cycle paths from a social perspective, applied to the case in the city of Malaga. (Author)
A new multiple robot path planning algorithm: dynamic distributed particle swarm optimization.
Ayari, Asma; Bouamama, Sadok
2017-01-01
Multiple robot systems have become a major study concern in the field of robotic research. Their control becomes unreliable and even infeasible if the number of robots increases. In this paper, a new dynamic distributed particle swarm optimization (D 2 PSO) algorithm is proposed for trajectory path planning of multiple robots in order to find collision-free optimal path for each robot in the environment. The proposed approach consists in calculating two local optima detectors, LOD pBest and LOD gBest . Particles which are unable to improve their personal best and global best for predefined number of successive iterations would be replaced with restructured ones. Stagnation and local optima problems would be avoided by adding diversity to the population, without losing the fast convergence characteristic of PSO. Experiments with multiple robots are provided and proved effectiveness of such approach compared with the distributed PSO.
System Design and Implementation of Intelligent Fire Engine Path Planning based on SAT Algorithm
CAI Li-sha[1; ZENG Wei-peng[1; HAN Bao-ru[1
2016-01-01
In this paper, in order to make intelligent fi re car complete autonomy path planning in simulation map. Proposed system design of intelligent fi re car path planning based on SAT. The system includes a planning module, a communication module, a control module. Control module via the communication module upload the initial state and the goal state to planning module. Planning module solve this planning solution,and then download planning solution to control module, control the movement of the car fi re. Experiments show this the system is tracking short time, higher planning effi ciency.
Robust path planning for flexible needle insertion using Markov decision processes.
Tan, Xiaoyu; Yu, Pengqian; Lim, Kah-Bin; Chui, Chee-Kong
2018-05-11
Flexible needle has the potential to accurately navigate to a treatment region in the least invasive manner. We propose a new planning method using Markov decision processes (MDPs) for flexible needle navigation that can perform robust path planning and steering under the circumstance of complex tissue-needle interactions. This method enhances the robustness of flexible needle steering from three different perspectives. First, the method considers the problem caused by soft tissue deformation. The method then resolves the common needle penetration failure caused by patterns of targets, while the last solution addresses the uncertainty issues in flexible needle motion due to complex and unpredictable tissue-needle interaction. Computer simulation and phantom experimental results show that the proposed method can perform robust planning and generate a secure control policy for flexible needle steering. Compared with a traditional method using MDPs, the proposed method achieves higher accuracy and probability of success in avoiding obstacles under complicated and uncertain tissue-needle interactions. Future work will involve experiment with biological tissue in vivo. The proposed robust path planning method can securely steer flexible needle within soft phantom tissues and achieve high adaptability in computer simulation.
Adel Akbarimajd
2012-02-01
Full Text Available A path planning method for mobile robots based on two dimensional cellular automata is proposed. The method can be applied for environments with both concave and convex obstacles. It is also appropriate for multi-robot problems as well as dynamic environments. In order to develop the planning method, environment of the robot is decomposed to a rectangular grid and the automata is defined with four states including Robot cell, Free cell, Goal cell and Obstacle cell. Evolution rules of automata are proposed in order to direct the robot toward its goal. CA based path planner method is afterwards modified by a colony technique to be applicable for concave obstacles. Then a layered architecture is proposed to autonomously implement the planning algorithm. The architecture employs an abstraction approach which makes the complexity manageable. An important feature of the architecture is internal artifacts that have some beliefs about the world. Most actions of the robot are planned and performed with respect to these artifacts.
Kaijun Zhou
2017-09-01
Full Text Available The Jump Point Search (JPS algorithm is adopted for local path planning of the driverless car under urban environment, and it is a fast search method applied in path planning. Firstly, a vector Geographic Information System (GIS map, including Global Positioning System (GPS position, direction, and lane information, is built for global path planning. Secondly, the GIS map database is utilized in global path planning for the driverless car. Then, the JPS algorithm is adopted to avoid the front obstacle, and to find an optimal local path for the driverless car in the urban environment. Finally, 125 different simulation experiments in the urban environment demonstrate that JPS can search out the optimal and safety path successfully, and meanwhile, it has a lower time complexity compared with the Vector Field Histogram (VFH, the Rapidly Exploring Random Tree (RRT, A*, and the Probabilistic Roadmaps (PRM algorithms. Furthermore, JPS is validated usefully in the structured urban environment.
Path planning for persistent surveillance applications using fixed-wing unmanned aerial vehicles
Keller, James F.
This thesis addresses coordinated path planning for fixed-wing Unmanned Aerial Vehicles (UAVs) engaged in persistent surveillance missions. While uniquely suited to this mission, fixed wing vehicles have maneuver constraints that can limit their performance in this role. Current technology vehicles are capable of long duration flight with a minimal acoustic footprint while carrying an array of cameras and sensors. Both military tactical and civilian safety applications can benefit from this technology. We make three main contributions: C1 A sequential path planner that generates a C 2 flight plan to persistently acquire a covering set of data over a user designated area of interest. The planner features the following innovations: • A path length abstraction that embeds kino-dynamic motion constraints to estimate feasible path length. • A Traveling Salesman-type planner to generate a covering set route based on the path length abstraction. • A smooth path generator that provides C 2 routes that satisfy user specified curvature constraints. C2 A set of algorithms to coordinate multiple UAVs, including mission commencement from arbitrary locations to the start of a coordinated mission and de-confliction of paths to avoid collisions with other vehicles and fixed obstacles. C3 A numerically robust toolbox of spline-based algorithms tailored for vehicle routing validated through flight test experiments on multiple platforms. A variety of tests and platforms are discussed. The algorithms presented are based on a technical approach with approximately equal emphasis on analysis, computation, dynamic simulation, and flight test experimentation. Our planner (C1) directly takes into account vehicle maneuverability and agility constraints that could otherwise render simple solutions infeasible. This is especially important when surveillance objectives elevate the importance of optimized paths. Researchers have developed a diverse range of solutions for persistent
The time-varying shortest path problem with fuzzy transit costs and speedup
Rezapour Hassan
2016-08-01
Full Text Available In this paper, we focus on the time-varying shortest path problem, where the transit costs are fuzzy numbers. Moreover, we consider this problem in which the transit time can be shortened at a fuzzy speedup cost. Speedup may also be a better decision to find the shortest path from a source vertex to a specified vertex.
Vahid Behravesh
2012-08-01
Full Text Available Presented article is studying the issue of path navigating for numerous robots. Our presented approach is based on both priority and the robust method for path finding in repetitive dynamic. Presented model can be generally implementable and useable: We do not assume any restriction regarding the quantity of levels of freedom for robots, and robots of diverse kinds can be applied at the same time. We proposed a random method and hill-climbing technique in the area based on precedence plans, which is used to determine a solution to a given trajectory planning problem and to make less the extent of total track. Our method plans trajectories for particular robots in the setting-time scope. Therefore, in order to specifying the interval of constant objects similar to other robots and the extent of the tracks which is traversed. For measuring the hazard for robots to conflict with each other it applied a method based on probability of the movements of robots. This algorithm applied to real robots with successful results. The proposed method performed and judged on both real robots and in simulation. We performed sequence of100tests with 8 robots for comparing with coordination method and current performances are effective. However, maximizing the performance is still possible. These performances estimations performed on Windows operating system and 3GHz Intel Pentium IV with and compiles with GCC 3.4. We used our PCGA robot for all experiments. For a large environment of 19×15m2where we accomplished 40tests, our model is competent to plan high-quality paths in a severely short time (less than a second. Moreover, this article utilized lookup tables to keep expenses the formerly navigated robots made, increasing the number of robots don’t expand computation time.
Cooperative path planning for multi-USV based on improved artificial bee colony algorithm
Cao, Lu; Chen, Qiwei
2018-03-01
Due to the complex constraints, more uncertain factors and critical real-time demand of path planning for multiple unmanned surface vehicle (multi-USV), an improved artificial bee colony (I-ABC) algorithm were proposed to solve the model of cooperative path planning for multi-USV. First the Voronoi diagram of battle field space is conceived to generate the optimal area of USVs paths. Then the chaotic searching algorithm is used to initialize the collection of paths, which is regard as foods of the ABC algorithm. With the limited data, the initial collection can search the optimal area of paths perfectly. Finally simulations of the multi-USV path planning under various threats have been carried out. Simulation results verify that the I-ABC algorithm can improve the diversity of nectar source and the convergence rate of algorithm. It can increase the adaptability of dynamic battlefield and unexpected threats for USV.
Vocational teacher career planning : needs and problems
Sajienė, Laima
2009-01-01
The article analyses a contradiction between vocational teacher ability to plan his/her career and requirements for the teacher professional development set by the system of education. It aims at providing theoretical and empirical justification for vocational teacher need to develop career planning skills and identify problems. The concept and objectives of vocational teacher career planning as well as career planning skills that vocational teachers should develop are defined in the article.
Hen, Itay; Rieffel, Eleanor G.; Do, Minh; Venturelli, Davide
2014-01-01
There are two common ways to evaluate algorithms: performance on benchmark problems derived from real applications and analysis of performance on parametrized families of problems. The two approaches complement each other, each having its advantages and disadvantages. The planning community has concentrated on the first approach, with few ways of generating parametrized families of hard problems known prior to this work. Our group's main interest is in comparing approaches to solving planning problems using a novel type of computational device - a quantum annealer - to existing state-of-the-art planning algorithms. Because only small-scale quantum annealers are available, we must compare on small problem sizes. Small problems are primarily useful for comparison only if they are instances of parametrized families of problems for which scaling analysis can be done. In this technical report, we discuss our approach to the generation of hard planning problems from classes of well-studied NP-complete problems that map naturally to planning problems or to aspects of planning problems that many practical planning problems share. These problem classes exhibit a phase transition between easy-to-solve and easy-to-show-unsolvable planning problems. The parametrized families of hard planning problems lie at the phase transition. The exponential scaling of hardness with problem size is apparent in these families even at very small problem sizes, thus enabling us to characterize even very small problems as hard. The families we developed will prove generally useful to the planning community in analyzing the performance of planning algorithms, providing a complementary approach to existing evaluation methods. We illustrate the hardness of these problems and their scaling with results on four state-of-the-art planners, observing significant differences between these planners on these problem families. Finally, we describe two general, and quite different, mappings of planning
Time-optimal path planning in uncertain flow fields using ensemble method
Wang, Tong
2016-01-06
An ensemble-based approach is developed to conduct time-optimal path planning in unsteady ocean currents under uncertainty. We focus our attention on two-dimensional steady and unsteady uncertain flows, and adopt a sampling methodology that is well suited to operational forecasts, where a set deterministic predictions is used to model and quantify uncertainty in the predictions. In the operational setting, much about dynamics, topography and forcing of the ocean environment is uncertain, and as a result a single path produced by a model simulation has limited utility. To overcome this limitation, we rely on a finitesize ensemble of deterministic forecasts to quantify the impact of variability in the dynamics. The uncertainty of flow field is parametrized using a finite number of independent canonical random variables with known densities, and the ensemble is generated by sampling these variables. For each the resulting realizations of the uncertain current field, we predict the optimal path by solving a boundary value problem (BVP), based on the Pontryagin maximum principle. A family of backward-in-time trajectories starting at the end position is used to generate suitable initial values for the BVP solver. This allows us to examine and analyze the performance of sampling strategy, and develop insight into extensions dealing with regional or general circulation models. In particular, the ensemble method enables us to perform a statistical analysis of travel times, and consequently develop a path planning approach that accounts for these statistics. The proposed methodology is tested for a number of scenarios. We first validate our algorithms by reproducing simple canonical solutions, and then demonstrate our approach in more complex flow fields, including idealized, steady and unsteady double-gyre flows.
The Global Optimal Algorithm of Reliable Path Finding Problem Based on Backtracking Method
Liang Shen
2017-01-01
Full Text Available There is a growing interest in finding a global optimal path in transportation networks particularly when the network suffers from unexpected disturbance. This paper studies the problem of finding a global optimal path to guarantee a given probability of arriving on time in a network with uncertainty, in which the travel time is stochastic instead of deterministic. Traditional path finding methods based on least expected travel time cannot capture the network user’s risk-taking behaviors in path finding. To overcome such limitation, the reliable path finding algorithms have been proposed but the convergence of global optimum is seldom addressed in the literature. This paper integrates the K-shortest path algorithm into Backtracking method to propose a new path finding algorithm under uncertainty. The global optimum of the proposed method can be guaranteed. Numerical examples are conducted to demonstrate the correctness and efficiency of the proposed algorithm.
Vandewouw, Marlee M., E-mail: marleev@mie.utoronto.ca; Aleman, Dionne M. [Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Ontario M5S 3G8 (Canada); Jaffray, David A. [Radiation Medicine Program, Princess Margaret Cancer Centre, Toronto, Ontario M5G 2M9 (Canada)
2016-08-15
Purpose: Continuous dose delivery in radiation therapy treatments has been shown to decrease total treatment time while improving the dose conformity and distribution homogeneity over the conventional step-and-shoot approach. The authors develop an inverse treatment planning method for Gamma Knife® Perfexion™ that continuously delivers dose along a path in the target. Methods: The authors’ method is comprised of two steps: find a path within the target, then solve a mixed integer optimization model to find the optimal collimator configurations and durations along the selected path. Robotic path-finding techniques, specifically, simultaneous localization and mapping (SLAM) using an extended Kalman filter, are used to obtain a path that travels sufficiently close to selected isocentre locations. SLAM is novelly extended to explore a 3D, discrete environment, which is the target discretized into voxels. Further novel extensions are incorporated into the steering mechanism to account for target geometry. Results: The SLAM method was tested on seven clinical cases and compared to clinical, Hamiltonian path continuous delivery, and inverse step-and-shoot treatment plans. The SLAM approach improved dose metrics compared to the clinical plans and Hamiltonian path continuous delivery plans. Beam-on times improved over clinical plans, and had mixed performance compared to Hamiltonian path continuous plans. The SLAM method is also shown to be robust to path selection inaccuracies, isocentre selection, and dose distribution. Conclusions: The SLAM method for continuous delivery provides decreased total treatment time and increased treatment quality compared to both clinical and inverse step-and-shoot plans, and outperforms existing path methods in treatment quality. It also accounts for uncertainty in treatment planning by accommodating inaccuracies.
Vandewouw, Marlee M.; Aleman, Dionne M.; Jaffray, David A.
2016-01-01
Purpose: Continuous dose delivery in radiation therapy treatments has been shown to decrease total treatment time while improving the dose conformity and distribution homogeneity over the conventional step-and-shoot approach. The authors develop an inverse treatment planning method for Gamma Knife® Perfexion™ that continuously delivers dose along a path in the target. Methods: The authors’ method is comprised of two steps: find a path within the target, then solve a mixed integer optimization model to find the optimal collimator configurations and durations along the selected path. Robotic path-finding techniques, specifically, simultaneous localization and mapping (SLAM) using an extended Kalman filter, are used to obtain a path that travels sufficiently close to selected isocentre locations. SLAM is novelly extended to explore a 3D, discrete environment, which is the target discretized into voxels. Further novel extensions are incorporated into the steering mechanism to account for target geometry. Results: The SLAM method was tested on seven clinical cases and compared to clinical, Hamiltonian path continuous delivery, and inverse step-and-shoot treatment plans. The SLAM approach improved dose metrics compared to the clinical plans and Hamiltonian path continuous delivery plans. Beam-on times improved over clinical plans, and had mixed performance compared to Hamiltonian path continuous plans. The SLAM method is also shown to be robust to path selection inaccuracies, isocentre selection, and dose distribution. Conclusions: The SLAM method for continuous delivery provides decreased total treatment time and increased treatment quality compared to both clinical and inverse step-and-shoot plans, and outperforms existing path methods in treatment quality. It also accounts for uncertainty in treatment planning by accommodating inaccuracies.
Curvature-Continuous 3D Path-Planning Using QPMI Method
Seong-Ryong Chang
2015-06-01
Full Text Available It is impossible to achieve vertex movement and rapid velocity control in aerial robots and aerial vehicles because of momentum from the air. A continuous-curvature path ensures such robots and vehicles can fly with stable and continuous movements. General continuous path-planning methods use spline interpolation, for example B-spline and Bézier curves. However, these methods cannot be directly applied to continuous path planning in a 3D space. These methods use a subset of the waypoints to decide curvature and some waypoints are not included in the planned path. This paper proposes a method for constructing a curvature-continuous path in 3D space that includes every waypoint. The movements in each axis, x, y and z, are separated by the parameter u. Waypoint groups are formed, each with its own continuous path derived using quadratic polynomial interpolation. The membership function then combines each continuous path into one continuous path. The continuity of the path is verified and the curvature-continuous path is produced using the proposed method.
An adaptive dual-optimal path-planning technique for unmanned air vehicles
Whitfield Clifford A.
2016-01-01
Full Text Available A multi-objective technique for unmanned air vehicle path-planning generation through task allocation has been developed. The dual-optimal path-planning technique generates real-time adaptive flight paths based on available flight windows and environmental influenced objectives. The environmentally-influenced flight condition determines the aircraft optimal orientation within a downstream virtual window of possible vehicle destinations that is based on the vehicle’s kinematics. The intermittent results are then pursued by a dynamic optimization technique to determine the flight path. This path-planning technique is a multi-objective optimization procedure consisting of two goals that do not require additional information to combine the conflicting objectives into a single-objective. The technique was applied to solar-regenerative high altitude long endurance flight which can benefit significantly from an adaptive real-time path-planning technique. The objectives were to determine the minimum power required flight paths while maintaining maximum solar power for continual surveillance over an area of interest (AOI. The simulated path generation technique prolonged the flight duration over a sustained turn loiter flight path by approximately 2 months for a year of flight. The potential for prolonged solar powered flight was consistent for all latitude locations, including 2 months of available flight at 60° latitude, where sustained turn flight was no longer capable.
An Adaptive Multi-Objective Particle Swarm Optimization Algorithm for Multi-Robot Path Planning
Nizar Hadi Abbas
2016-07-01
Full Text Available This paper discusses an optimal path planning algorithm based on an Adaptive Multi-Objective Particle Swarm Optimization Algorithm (AMOPSO for two case studies. First case, single robot wants to reach a goal in the static environment that contain two obstacles and two danger source. The second one, is improving the ability for five robots to reach the shortest way. The proposed algorithm solves the optimization problems for the first case by finding the minimum distance from initial to goal position and also ensuring that the generated path has a maximum distance from the danger zones. And for the second case, finding the shortest path for every robot and without any collision between them with the shortest time. In order to evaluate the proposed algorithm in term of finding the best solution, six benchmark test functions are used to make a comparison between AMOPSO and the standard MOPSO. The results show that the AMOPSO has a better ability to get away from local optimums with a quickest convergence than the MOPSO. The simulation results using Matlab 2014a, indicate that this methodology is extremely valuable for every robot in multi-robot framework to discover its own particular proper path from the start to the destination position with minimum distance and time.
Planning paths through a spatial hierarchy - Eliminating stair-stepping effects
Slack, Marc G.
1989-01-01
Stair-stepping effects are a result of the loss of spatial continuity resulting from the decomposition of space into a grid. This paper presents a path planning algorithm which eliminates stair-stepping effects induced by the grid-based spatial representation. The algorithm exploits a hierarchical spatial model to efficiently plan paths for a mobile robot operating in dynamic domains. The spatial model and path planning algorithm map to a parallel machine, allowing the system to operate incrementally, thereby accounting for unexpected events in the operating space.
Problems of energy supply planning
Lelek, V.
2009-01-01
The International Project on Innovative Nuclear Reactors and Fuel Cycles (INPRO), existing within IAEA Vienna decided to prepare energy and nuclear vision of 21st century. We were asked on behalf of AER Working Group F - 'Spent Fuel Transmutations' and INPRO IAEA collaborative project RMI 'Meeting energy needs in the period of raw materials insufficiency during the 21st century' to prepare material about the situations, reasons and expected time table concerning future nuclear fuel cycle closing and influences of fossil raw materials deficiencies, expected during the coming century. Material does not content, specially in the second part complete solution and partially is only formulating extremely complex problems of mutual interaction of technologies, raw materials availability and economy needs, together with political demands of non-proliferation of nuclear weapons and ecology, taking into account equal rights to have electricity and further services using nuclear energy. (author)
Path inequalities for the vehicle routing problem with time windows
Kallehauge, Brian; Boland, Natashia; Madsen, Oli B.G.
2007-01-01
In this paper we introduce a new formulation of the vehicle routing problem with time windows (VRPTW) involving only binary variables. The new formulation is based on the formulation of the asymmetric traveling salesman problem with time windows by Ascheuer et al. (Networks 36 (2000) 69-79) and has...
Rowe, Neil C.; Lewis, David H.
1989-01-01
Path planning is an important issue for space robotics. Finding safe and energy-efficient paths in the presence of obstacles and other constraints can be complex although important. High-level (large-scale) path planning for robotic vehicles was investigated in three-dimensional space with obstacles, accounting for: (1) energy costs proportional to path length; (2) turn costs where paths change trajectory abruptly; and (3) safety costs for the danger associated with traversing a particular path due to visibility or invisibility from a fixed set of observers. Paths optimal with respect to these cost factors are found. Autonomous or semi-autonomous vehicles were considered operating either in a space environment around satellites and space platforms, or aircraft, spacecraft, or smart missiles operating just above lunar and planetary surfaces. One class of applications concerns minimizing detection, as for example determining the best way to make complex modifications to a satellite without being observed by hostile sensors; another example is verifying there are no paths (holes) through a space defense system. Another class of applications concerns maximizing detection, as finding a good trajectory between mountain ranges of a planet while staying reasonably close to the surface, or finding paths for a flight between two locations that maximize the average number of triangulation points available at any time along the path.
Hameed, Ibahim
2014-01-01
Field operations should be done in a manner that minimizes time and travels over the field surface. Automated and intelligent path planning can help to find the best coverage path so that costs of various field operations can be minimized. The algorithms for generating an optimized field coverage...
Probabilistic Path Planning of Montgolfier Balloons in Strong, Uncertain Wind Fields
Wolf, Michael; Blackmore, James C.; Kuwata, Yoshiaki
2011-01-01
Lighter-than-air vehicles such as hot-air balloons have been proposed for exploring Saturn s moon Titan, as well as other bodies with significant atmospheres. For these vehicles to navigate effectively, it is critical to incorporate the effects of surrounding wind fields, especially as these winds will likely be strong relative to the control authority of the vehicle. Predictive models of these wind fields are available, and previous research has considered problems of planning paths subject to these predicted forces. However, such previous work has considered the wind fields as known a priori, whereas in practical applications, the actual wind vector field is not known exactly and may deviate significantly from the wind velocities estimated by the model. A probabilistic 3D path-planning algorithm was developed for balloons to use uncertain wind models to generate time-efficient paths. The nominal goal of the algorithm is to determine what altitude and what horizontal actuation, if any is available on the vehicle, to use to reach a particular goal location in the least expected time, utilizing advantageous winds. The solution also enables one to quickly evaluate the expected time-to-goal from any other location and to avoid regions of large uncertainty. This method is designed for balloons in wind fields but may be generalized for any buoyant vehicle operating in a vector field. To prepare the planning problem, the uncertainty in the wind field is modeled. Then, the problem of reaching a particular goal location is formulated as a Markov decision process (MDP) using a discretized space approach. Solving the MDP provides a policy of what actuation option (how much buoyancy change and, if applicable, horizontal actuation) should be selected at any given location to minimize the expected time-to-goal. The results provide expected time-to-goal values from any given location on the globe in addition to the action policy. This stochastic approach can also provide
Path Planning for Non-Circular, Non-Holonomic Robots in Highly Cluttered Environments.
Samaniego, Ricardo; Lopez, Joaquin; Vazquez, Fernando
2017-08-15
This paper presents an algorithm for finding a solution to the problem of planning a feasible path for a slender autonomous mobile robot in a large and cluttered environment. The presented approach is based on performing a graph search on a kinodynamic-feasible lattice state space of high resolution; however, the technique is applicable to many search algorithms. With the purpose of allowing the algorithm to consider paths that take the robot through narrow passes and close to obstacles, high resolutions are used for the lattice space and the control set. This introduces new challenges because one of the most computationally expensive parts of path search based planning algorithms is calculating the cost of each one of the actions or steps that could potentially be part of the trajectory. The reason for this is that the evaluation of each one of these actions involves convolving the robot's footprint with a portion of a local map to evaluate the possibility of a collision, an operation that grows exponentially as the resolution is increased. The novel approach presented here reduces the need for these convolutions by using a set of offline precomputed maps that are updated, by means of a partial convolution, as new information arrives from sensors or other sources. Not only does this improve run-time performance, but it also provides support for dynamic search in changing environments. A set of alternative fast convolution methods are also proposed, depending on whether the environment is cluttered with obstacles or not. Finally, we provide both theoretical and experimental results from different experiments and applications.
Hurezeanu, Vlad
2000-01-01
.... This vehicle performs tasks to include surveying fields, laying mines, and teleoperation. The capability of the vehicle will be increased if its supporting software plans paths that take into account the terrain features...
A Distributed Framework for Real Time Path Planning in Practical Multi-agent Systems
Abdelkader, Mohamed; Jaleel, Hassan; Shamma, Jeff S.
2017-01-01
We present a framework for distributed, energy efficient, and real time implementable algorithms for path planning in multi-agent systems. The proposed framework is presented in the context of a motivating example of capture the flag which
Cooperative Path Planning and Constraints Analysis for Master-Slave Industrial Robots
Yahui Gan
2012-09-01
Full Text Available A strategy of cooperative path planning for a master-slave multiple robot system is presented in this paper. The path planning method is based on motion constraints between the end-effectors of cooperative robots. Cooperation motions have been classified into three types by relative motions between end-effectors of master and slave robots, which is concurrent cooperation, coupled synchronous cooperation and combined synchronous cooperation. Based on this classification, position /orientation constraints and joint velocity constraints are explored in-depth here. In order to validate the path planning method and the theoretical developments in motion constraints analysis, representative experiments based on two industrial robots, Motoman VA1400 and HP20, are provided at the end of the paper. The experimental results have proved both the effectiveness of the path planning method and the correctness of the constraints analysis.
Time-optimal path planning in uncertain flow fields using ensemble method
Wang, Tong; Le Maitre, Olivier; Hoteit, Ibrahim; Knio, Omar
2016-01-01
the performance of sampling strategy, and develop insight into extensions dealing with regional or general circulation models. In particular, the ensemble method enables us to perform a statistical analysis of travel times, and consequently develop a path planning
Generalized production planning problem under interval uncertainty
Samir A. Abass
2010-06-01
Full Text Available Data in many real life engineering and economical problems suffer from inexactness. Herein we assume that we are given some intervals in which the data can simultaneously and independently perturb. We consider the generalized production planning problem with interval data. The interval data are in both of the objective function and constraints. The existing results concerning the qualitative and quantitative analysis of basic notions in parametric production planning problem. These notions are the set of feasible parameters, the solvability set and the stability set of the first kind.
Sales plan generation problem on TV broadcasting
Özlem Cosgun; İlkay Gultas
2016-01-01
Major advertisers and/or advertisement agencies purchase hundreds of slots during a given broadcast period. Deterministic optimization approaches have been well developed for the problem of meeting client requests. The challenging task for the academic research currently is to address optimization problem under uncertainty. This paper is concerned with the sales plan generation problem when the audience levels of advertisement slots are random variables with known probability distributions. T...
视觉移动机器人的模糊智能路径规划%Intelligent Path Planning of Vision- Based Mobile Robot with Fuzzy Approach
张一巍; 黄源清
2002-01-01
The path planning problem for intelligent mobile robots inwbves two main problems: the represent of task emionment including obstacles and the development of a strategy to determine a collision - free route. In this paper, new approaches have been developed to solve these problems .The first problem was solve using the fuzzy system approach, which represent obstacles with a circle. The other problem was overcome throughthe use of a strategy selector, which chooses the best stategy between velocity control strategy and direction control strategy.
Optimized path planning for soft tissue resection via laser vaporization
Ross, Weston; Cornwell, Neil; Tucker, Matthew; Mann, Brian; Codd, Patrick
2018-02-01
Robotic and robotic-assisted surgeries are becoming more prevalent with the promise of improving surgical outcomes through increased precision, reduced operating times, and minimally invasive procedures. The handheld laser scalpel in neurosurgery has been shown to provide a more gentle approach to tissue manipulation on or near critical structures over classical tooling, though difficulties of control have prevented large scale adoption of the tool. This paper presents a novel approach to generating a cutting path for the volumetric resection of tissue using a computer-guided laser scalpel. A soft tissue ablation simulator is developed and used in conjunction with an optimization routine to select parameters which maximize the total resection of target tissue while minimizing the damage to surrounding tissue. The simulator predicts the ablative properties of tissue from an interrogation cut for tuning and simulates the removal of a tumorous tissue embedded on the surface of healthy tissue using a laser scalpel. We demonstrate the ability to control depth and smoothness of cut using genetic algorithms to optimize the ablation parameters and cutting path. The laser power level, cutting rate and spacing between cuts are optimized over multiple surface cuts to achieve the desired resection volumes.
Employing Multiple Unmanned Aerial Vehicles for Co-Operative Path Planning
Durdana Habib
2013-05-01
Full Text Available Abstract In this paper, we work to develop a path planning solution for a group of Unmanned Aerial Vehicles (UAVs using a Mixed Integer Linear Programming (MILP approach. Co-operation among team members not only helps reduce mission time, it makes the execution more robust in dynamic environments. However, the problem becomes more challenging as it requires optimal resource allocation and is NP-hard. Since UAVs may be lost or may suffer significant damage during the course of the mission, plans may need to be modified in real-time as the mission proceeds. Therefore, multiple UAVs have a better chance of completing a mission in the face of failures. Such military operations can be treated as a variant of the Multiple Depot Vehicle Routing Problem (MDVRP. The proposed solution must be such that m UAVs start from multiple source locations to visit n targets and return to a set of destination locations such that (1 each target is visited exactly by one of the chosen UAVs (2 the total distance travelled by the group is minimized and (3 the number of targets that each UAV visits may not be less than K or greater than L.
Sales plan generation problem on TV broadcasting
Özlem Cosgun
2016-07-01
Full Text Available Major advertisers and/or advertisement agencies purchase hundreds of slots during a given broadcast period. Deterministic optimization approaches have been well developed for the problem of meeting client requests. The challenging task for the academic research currently is to address optimization problem under uncertainty. This paper is concerned with the sales plan generation problem when the audience levels of advertisement slots are random variables with known probability distributions. There are several constraints the TV networks must meet including client budget, product category and demographic information, plan weighting by week, program mix requirements, and the lengths of advertisement slots desired by the client. We formulate the problem as a chance constrained goal program and we demonstrate that it provides a robust solution with a user specified level of reliability.
A Local Search Modeling for Constrained Optimum Paths Problems (Extended Abstract
Quang Dung Pham
2009-10-01
Full Text Available Constrained Optimum Path (COP problems appear in many real-life applications, especially on communication networks. Some of these problems have been considered and solved by specific techniques which are usually difficult to extend. In this paper, we introduce a novel local search modeling for solving some COPs by local search. The modeling features the compositionality, modularity, reuse and strengthens the benefits of Constrained-Based Local Search. We also apply the modeling to the edge-disjoint paths problem (EDP. We show that side constraints can easily be added in the model. Computational results show the significance of the approach.
The Resource constrained shortest path problem implemented in a lazy functional language
Hartel, Pieter H.; Glaser, Hugh
The resource constrained shortest path problem is an NP-hard problem for which many ingenious algorithms have been developed. These algorithms are usually implemented in Fortran or another imperative programming language. We have implemented some of the simpler algorithms in a lazy functional
Comparison of some evolutionary algorithms for optimization of the path synthesis problem
Grabski, Jakub Krzysztof; Walczak, Tomasz; Buśkiewicz, Jacek; Michałowska, Martyna
2018-01-01
The paper presents comparison of the results obtained in a mechanism synthesis by means of some selected evolutionary algorithms. The optimization problem considered in the paper as an example is the dimensional synthesis of the path generating four-bar mechanism. In order to solve this problem, three different artificial intelligence algorithms are employed in this study.
Kenneth J. Ruzicka; Deanna H. Olson; Klaus J. Puettmann
2013-01-01
Initiated simultaneously, the Density Management and Riparian Buff er Study of western Oregon and the Northwest Forest Plan have had intertwining paths related to federal forest management and policy changes in the Pacifi c Northwest over the last 15 to 20 years. We briefl y discuss the development of the Northwest Forest Plan and how it changed the way forest policy...
Problem-Solving Strategies for Career Planning.
McBryde, Merry J.; Karr-Kidwell, PJ
The need for new expertise in problem solving in the work setting has emerged as a woman's issue because work outside the home has become a primary means for personal goal attainment for about half the women in the United States and because traditional career patterns and norms are ineffective. Career planning is the process of individual career…
Organisational Problems in Planning Educational Development.
Organisation for Economic Cooperation and Development, Paris (France). Directorate for Scientific Affairs.
Papers submitted to a meeting of economists, educators, and government officials discuss the organizational implications of the link between education and economic growth. Following an introduction by Henning Friis, the authors and titles of the papers are (1) Necat Erder, "Some Administrative Problems in Educational Planning," (2) Raymond…
Zheng Zhang
2013-03-01
Full Text Available In a hybrid wireless sensor network with mobile and static nodes, which have no prior geographical knowledge, successful navigation for mobile robots is one of the main challenges. In this paper, we propose two novel navigation algorithms for outdoor environments, which permit robots to travel from one static node to another along a planned path in the sensor field, namely the RAC and the IMAP algorithms. Using this, the robot can navigate without the help of a map, GPS or extra sensor modules, only using the received signal strength indication (RSSI and odometry. Therefore, our algorithms have the advantage of being cost-effective. In addition, a path planning algorithm to schedule mobile robots' travelling paths is presented, which focuses on shorter distances and robust paths for robots by considering the RSSI-Distance characteristics. The simulations and experiments conducted with an autonomous mobile robot show the effectiveness of the proposed algorithms in an outdoor environment.
Partial path column generation for the vehicle routing problem with time windows
Petersen, Bjørn; Jepsen, Mads Kehlet
2009-01-01
This paper presents a column generation algorithm for the Vehicle Routing Problem with Time Windows (VRPTW). Traditionally, column generation models of the VRPTW have consisted of a Set Partitioning master problem with each column representing a route, i.e., a resource feasible path starting...... and ending at the depot. Elementary routes (no customer visited more than once) have shown superior results on difficult instances (less restrictive capacity and time windows). However, the pricing problems do not scale well when the number of feasible routes increases, i.e., when a route may contain a large...... number of customers. We suggest to relax that ‘each column is a route’ into ‘each column is a part of the giant tour’; a so-called partial path, i.e., not necessarily starting and ending in the depot. This way, the length of the partial path can be bounded and a better control of the size of the solution...
Shortest path problem on a grid network with unordered intermediate points
Saw, Veekeong; Rahman, Amirah; Eng Ong, Wen
2017-10-01
We consider a shortest path problem with single cost factor on a grid network with unordered intermediate points. A two stage heuristic algorithm is proposed to find a feasible solution path within a reasonable amount of time. To evaluate the performance of the proposed algorithm, computational experiments are performed on grid maps of varying size and number of intermediate points. Preliminary results for the problem are reported. Numerical comparisons against brute forcing show that the proposed algorithm consistently yields solutions that are within 10% of the optimal solution and uses significantly less computation time.
[Some psychological problems in family planning work].
Chen, J
1983-11-29
Psychology has significance in family planning work, because it may promote the scientific nature of family planning work and thus increase its effectiveness. Since people have some common aspects in their psychological process, family planning workers should master some common rules of the people's psychological process in order to understand psychological trends and possible behavior. Through this method, family planning workers may find how to adjust to problems they may encounter in their daily work, such as the worries about a single child being too lonely, spoiled, and hard to handle for the parents, the traditional belief that more children represent good fortune, and more male children may provide security for one's old age. Traditionally, the Chinese people believed that only male children can carry on the family line and that more children will provide a larger labor force, which is beneficial to a family's financial situation. In family planning work, all such incorrect ways of thinking should be corrected and revised. Studies of children's psychology should also be developed so that children may develop a healthy mentality. All these are crucial to the success of family planning work and the promotion of population quality.
Prograph Based Analysis of Single Source Shortest Path Problem with Few Distinct Positive Lengths
B. Bhowmik
2011-08-01
Full Text Available In this paper we propose an experimental study model S3P2 of a fast fully dynamic programming algorithm design technique in finite directed graphs with few distinct nonnegative real edge weights. The Bellman-Ford’s approach for shortest path problems has come out in various implementations. In this paper the approach once again is re-investigated with adjacency matrix selection in associate least running time. The model tests proposed algorithm against arbitrarily but positive valued weighted digraphs introducing notion of Prograph that speeds up finding the shortest path over previous implementations. Our experiments have established abstract results with the intention that the proposed algorithm can consistently dominate other existing algorithms for Single Source Shortest Path Problems. A comparison study is also shown among Dijkstra’s algorithm, Bellman-Ford algorithm, and our algorithm.
Evolutionistic or revolutionary paths? A PACS maturity model for strategic situational planning.
van de Wetering, Rogier; Batenburg, Ronald; Lederman, Reeva
2010-07-01
While many hospitals are re-evaluating their current Picture Archiving and Communication System (PACS), few have a mature strategy for PACS deployment. Furthermore, strategies for implementation, strategic and situational planning methods for the evolution of PACS maturity are scarce in the scientific literature. Consequently, in this paper we propose a strategic planning method for PACS deployment. This method builds upon a PACS maturity model (PMM), based on the elaboration of the strategic alignment concept and the maturity growth path concept previously developed in the PACS domain. First, we review the literature on strategic planning for information systems and information technology and PACS maturity. Secondly, the PMM is extended by applying four different strategic perspectives of the Strategic Alignment Framework whereupon two types of growth paths (evolutionistic and revolutionary) are applied that focus on a roadmap for PMM. This roadmap builds a path to get from one level of maturity and evolve to the next. An extended method for PACS strategic planning is developed. This method defines eight distinctive strategies for PACS strategic situational planning that allow decision-makers in hospitals to decide which approach best suits their hospitals' current situation and future ambition and what in principle is needed to evolve through the different maturity levels. The proposed method allows hospitals to strategically plan for PACS maturation. It is situational in that the required investments and activities depend on the alignment between the hospital strategy and the selected growth path. The inclusion of both strategic alignment and maturity growth path concepts make the planning method rigorous, and provide a framework for further empirical research and clinical practice.
Bakar, Sumarni Abu; Ibrahim, Milbah
2017-08-01
The shortest path problem is a popular problem in graph theory. It is about finding a path with minimum length between a specified pair of vertices. In any network the weight of each edge is usually represented in a form of crisp real number and subsequently the weight is used in the calculation of shortest path problem using deterministic algorithms. However, due to failure, uncertainty is always encountered in practice whereby the weight of edge of the network is uncertain and imprecise. In this paper, a modified algorithm which utilized heuristic shortest path method and fuzzy approach is proposed for solving a network with imprecise arc length. Here, interval number and triangular fuzzy number in representing arc length of the network are considered. The modified algorithm is then applied to a specific example of the Travelling Salesman Problem (TSP). Total shortest distance obtained from this algorithm is then compared with the total distance obtained from traditional nearest neighbour heuristic algorithm. The result shows that the modified algorithm can provide not only on the sequence of visited cities which shown to be similar with traditional approach but it also provides a good measurement of total shortest distance which is lesser as compared to the total shortest distance calculated using traditional approach. Hence, this research could contribute to the enrichment of methods used in solving TSP.
Hu, Xuemin; Chen, Long; Tang, Bo; Cao, Dongpu; He, Haibo
2018-02-01
This paper presents a real-time dynamic path planning method for autonomous driving that avoids both static and moving obstacles. The proposed path planning method determines not only an optimal path, but also the appropriate acceleration and speed for a vehicle. In this method, we first construct a center line from a set of predefined waypoints, which are usually obtained from a lane-level map. A series of path candidates are generated by the arc length and offset to the center line in the s - ρ coordinate system. Then, all of these candidates are converted into Cartesian coordinates. The optimal path is selected considering the total cost of static safety, comfortability, and dynamic safety; meanwhile, the appropriate acceleration and speed for the optimal path are also identified. Various types of roads, including single-lane roads and multi-lane roads with static and moving obstacles, are designed to test the proposed method. The simulation results demonstrate the effectiveness of the proposed method, and indicate its wide practical application to autonomous driving.
Analysis of an Automated Vehicle Routing Problem in Logistics considering Path Interruption
Yong Zhang
2017-01-01
Full Text Available The application of automated vehicles in logistics can efficiently reduce the cost of logistics and reduce the potential risks in the last mile. Considering the path restriction in the initial stage of the application of automated vehicles in logistics, the conventional model for a vehicle routing problem (VRP is modified. Thus, the automated vehicle routing problem with time windows (AVRPTW model considering path interruption is established. Additionally, an improved particle swarm optimisation (PSO algorithm is designed to solve this problem. Finally, a case study is undertaken to test the validity of the model and the algorithm. Four automated vehicles are designated to execute all delivery tasks required by 25 stores. Capacities of all of the automated vehicles are almost fully utilised. It is of considerable significance for the promotion of automated vehicles in last-mile situations to develop such research into real problems arising in the initial period.
Current-Sensitive Path Planning for an Underactuated Free-Floating Ocean Sensorweb
Dahl, Kristen P.; Thompson, David R.; McLaren, David; Chao, Yi; Chien, Steve
2011-01-01
This work investigates multi-agent path planning in strong, dynamic currents using thousands of highly under-actuated vehicles. We address the specific task of path planning for a global network of ocean-observing floats. These submersibles are typified by the Argo global network consisting of over 3000 sensor platforms. They can control their buoyancy to float at depth for data collection or rise to the surface for satellite communications. Currently, floats drift at a constant depth regardless of the local currents. However, accurate current forecasts have become available which present the possibility of intentionally controlling floats' motion by dynamically commanding them to linger at different depths. This project explores the use of these current predictions to direct float networks to some desired final formation or position. It presents multiple algorithms for such path optimization and demonstrates their advantage over the standard approach of constant-depth drifting.
Search Problems in Mission Planning and Navigation of Autonomous Aircraft. M.S. Thesis
Krozel, James A.
1988-01-01
An architecture for the control of an autonomous aircraft is presented. The architecture is a hierarchical system representing an anthropomorphic breakdown of the control problem into planner, navigator, and pilot systems. The planner system determines high level global plans from overall mission objectives. This abstract mission planning is investigated by focusing on the Traveling Salesman Problem with variations on local and global constraints. Tree search techniques are applied including the breadth first, depth first, and best first algorithms. The minimum-column and row entries for the Traveling Salesman Problem cost matrix provides a powerful heuristic to guide these search techniques. Mission planning subgoals are directed from the planner to the navigator for planning routes in mountainous terrain with threats. Terrain/threat information is abstracted into a graph of possible paths for which graph searches are performed. It is shown that paths can be well represented by a search graph based on the Voronoi diagram of points representing the vertices of mountain boundaries. A comparison of Dijkstra's dynamic programming algorithm and the A* graph search algorithm from artificial intelligence/operations research is performed for several navigation path planning examples. These examples illustrate paths that minimize a combination of distance and exposure to threats. Finally, the pilot system synthesizes the flight trajectory by creating the control commands to fly the aircraft.
The force control and path planning of electromagnetic induction-based massage robot.
Wang, Wendong; Zhang, Lei; Li, Jinzhe; Yuan, Xiaoqing; Shi, Yikai; Jiang, Qinqin; He, Lijing
2017-07-20
Massage robot is considered as an effective physiological treatment to relieve fatigue, improve blood circulation, relax muscle tone, etc. The simple massage equipment quickly spread into market due to low cost, but they are not widely accepted due to restricted massage function. Complicated structure and high cost caused difficulties for developing multi-function massage equipment. This paper presents a novel massage robot which can achieve tapping, rolling, kneading and other massage operations, and proposes an improved reciprocating path planning algorithm to improve massage effect. The number of coil turns, the coil current and the distance between massage head and yoke were chosen to investigate the influence on massage force by finite element method. The control system model of the wheeled massage robot was established, including control subsystem of the motor, path algorithm control subsystem, parameter module of the massage robot and virtual reality interface module. The improved reciprocating path planning algorithm was proposed to improve regional coverage rate and massage effect. The influence caused by coil current, the number of coil turns and the distance between massage head and yoke were simulated in Maxwell. It indicated that coil current has more important influence compared to the other two factors. The path planning simulation of the massage robot was completed in Matlab, and the results show that the improved reciprocating path planning algorithm achieved higher coverage rate than the traditional algorithm. With the analysis of simulation results, it can be concluded that the number of coil turns and the distance between the moving iron core and the yoke could be determined prior to coil current, and the force can be controllable by optimizing structure parameters of massage head and adjusting coil current. Meanwhile, it demonstrates that the proposed algorithm could effectively improve path coverage rate during massage operations, therefore
The graph-theoretic minimum energy path problem for ionic conduction
Ippei Kishida
2015-10-01
Full Text Available A new computational method was developed to analyze the ionic conduction mechanism in crystals through graph theory. The graph was organized into nodes, which represent the crystal structures modeled by ionic site occupation, and edges, which represent structure transitions via ionic jumps. We proposed a minimum energy path problem, which is similar to the shortest path problem. An effective algorithm to solve the problem was established. Since our method does not use randomized algorithm and time parameters, the computational cost to analyze conduction paths and a migration energy is very low. The power of the method was verified by applying it to α-AgI and the ionic conduction mechanism in α-AgI was revealed. The analysis using single point calculations found the minimum energy path for long-distance ionic conduction, which consists of 12 steps of ionic jumps in a unit cell. From the results, the detailed theoretical migration energy was calculated as 0.11 eV by geometry optimization and nudged elastic band method. Our method can refine candidates for possible jumps in crystals and it can be adapted to other computational methods, such as the nudged elastic band method. We expect that our method will be a powerful tool for analyzing ionic conduction mechanisms, even for large complex crystals.
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…
Hybrid path planning for non-holonomic autonomous vehicles: An experimental evaluation
Esposto, F.; Goos, J.; Teerhuis, A.; Alirezaei, M.
2017-01-01
Path planning of an autonomous vehicle as a non-holonomic system is an essential part for many automated driving applications. Parking a car into a parking lot and maneuvering it through a narrow corridor would be a common driving scenarios in an urban environment. In this study a hybrid approach
Complete coverage path planning of a random polygon - A FroboMind component
Aslund, Sebastian; Jensen, Kjeld; Jørgensen, Rasmus Nyholm
solution where all the steps in the process is included: Segmentation of a data set, creation of a configuration space, decomposition of a polygon, global and local path planning. To achieve this, a series of known algorithms are used including some tweaks and improvements to create a solid foundation...
Optimization of path length stretching in Monte Carlo calculations for non-leakage problems
Hoogenboom, J.E. [Delft Univ. of Technology (Netherlands)
2005-07-01
Path length stretching (or exponential biasing) is a well known variance reduction technique in Monte Carlo calculations. It can especially be useful in shielding problems where particles have to penetrate a lot of material before being tallied. Several authors sought for optimization of the path length stretching parameter for detection of the leakage of neutrons from a slab. Here the adjoint function behaves as a single exponential function and can well be used to determine the stretching parameter. In this paper optimization is sought for a detector embedded in the system, which changes the adjoint function in the detector drastically. From literature it is known that the combination of path length stretching and angular biasing can result in appreciable variance reduction. However, angular biasing is not generally available in general purpose Monte Carlo codes and therefore we want to restrict ourselves to the application of pure path length stretching and finding optimum parameters for that. Nonetheless, the starting point for our research is the zero-variance scheme. In order to study the solution in detail the simplified monoenergetic two-direction model is adopted, which allows analytical solutions and can still be used in a Monte Carlo simulation. Knowing the zero-variance solution analytically, it is shown how optimum path length stretching parameters can be derived from it. It results in path length shrinking in the detector. Results for the variance in the detector response are shown in comparison with other patterns for the stretching parameter. The effect of anisotropic scattering on the path length stretching parameter is taken into account. (author)
Methodology for using root locus technique for mobile robots path planning
Mario Ricardo Arbulú Saavedra
2015-11-01
Full Text Available This paper shows the analysis and the implementation methodology of the technique of dynamic systems roots location used in free-obstacle path planning for mobile robots. First of all, the analysis and morphologic behavior identification of the paths depending on roots location in complex plane are performed, where paths type and their attraction and repulsion features in the presence of other roots similarly to the obtained with artificial potential fields are identified. An implementation methodology for this technique of mobile robots path planning is proposed, starting from three different methods of roots location for obstacles in the scene. Those techniques change depending on the obstacle key points selected for roots, such as borders, crossing points with original path, center and vertices. Finally, a behavior analysis of general technique and the effectiveness of each tried method is performed, doing 20 tests for each one, obtaining a value of 65% for the selected method. Modifications and possible improvements to this methodology are also proposed.
A Distributed Framework for Real Time Path Planning in Practical Multi-agent Systems
Abdelkader, Mohamed
2017-10-19
We present a framework for distributed, energy efficient, and real time implementable algorithms for path planning in multi-agent systems. The proposed framework is presented in the context of a motivating example of capture the flag which is an adversarial game played between two teams of autonomous agents called defenders and attackers. We start with the centralized formulation of the problem as a linear program because of its computational efficiency. Then we present an approximation framework in which each agent solves a local version of the centralized linear program by communicating with its neighbors only. The premise in this work is that for practical multi-agent systems, real time implementability of distributed algorithms is more crucial then global optimality. Thus, instead of verifying the proposed framework by performing offline simulations in MATLAB, we run extensive simulations in a robotic simulator V-REP, which includes a detailed dynamic model of quadrotors. Moreover, to create a realistic scenario, we allow a human operator to control the attacker quadrotor through a joystick in a single attacker setup. These simulations authenticate that the proposed framework is real time implementable and results in a performance that is comparable with the global optimal solution under the considered scenarios.
Buschbaum, Jan; Fremd, Rainer; Pohlemann, Tim; Kristen, Alexander
2017-08-01
Reduction is a crucial step in the surgical treatment of bone fractures. Finding an optimal path for restoring anatomical alignment is considered technically demanding because collisions as well as high forces caused by surrounding soft tissues can avoid desired reduction movements. The repetition of reduction movements leads to a trial-and-error process which causes a prolonged duration of surgery. By planning an appropriate reduction path-an optimal sequence of target-directed movements-these problems should be overcome. For this purpose, a computer-based method has been developed. Using the example of simple femoral shaft fractures, 3D models are generated out of CT images. A reposition algorithm aligns both fragments by reconstructing their broken edges. According to the criteria of a deduced planning strategy, a modified A*-algorithm searches collision-free route of minimal force from the dislocated into the computed target position. Muscular forces are considered using a musculoskeletal reduction model (OpenSim model), and bone collisions are detected by an appropriate method. Five femoral SYNBONE models were broken into different fracture classification types and were automatically reduced from ten randomly selected displaced positions. Highest mean translational and rotational error for achieving target alignment is [Formula: see text] and [Formula: see text]. Mean value and standard deviation of occurring forces are [Formula: see text] for M. tensor fasciae latae and [Formula: see text] for M. semitendinosus over all trials. These pathways are precise, collision-free, required forces are minimized, and thus regarded as optimal paths. A novel method for planning reduction paths under consideration of collisions and muscular forces is introduced. The results deliver additional knowledge for an appropriate tactical reduction procedure and can provide a basis for further navigated or robotic-assisted developments.
A Dynamic Hidden Forwarding Path Planning Method Based on Improved Q-Learning in SDN Environments
Yun Chen
2018-01-01
Full Text Available Currently, many methods are available to improve the target network’s security. The vast majority of them cannot obtain an optimal attack path and interdict it dynamically and conveniently. Almost all defense strategies aim to repair known vulnerabilities or limit services in target network to improve security of network. These methods cannot response to the attacks in real-time because sometimes they need to wait for manufacturers releasing corresponding countermeasures to repair vulnerabilities. In this paper, we propose an improved Q-learning algorithm to plan an optimal attack path directly and automatically. Based on this path, we use software-defined network (SDN to adjust routing paths and create hidden forwarding paths dynamically to filter vicious attack requests. Compared to other machine learning algorithms, Q-learning only needs to input the target state to its agents, which can avoid early complex training process. We improve Q-learning algorithm in two aspects. First, a reward function based on the weights of hosts and attack success rates of vulnerabilities is proposed, which can adapt to different network topologies precisely. Second, we remove the actions and merge them into every state that reduces complexity from O(N3 to O(N2. In experiments, after deploying hidden forwarding paths, the security of target network is boosted significantly without having to repair network vulnerabilities immediately.
The Shortest Path Problems in Battery-Electric Vehicle Dispatching with Battery Renewal
Minfang Huang
2016-06-01
Full Text Available Electric vehicles play a key role for developing an eco-sustainable transport system. One critical component of an electric vehicle is its battery, which can be quickly charged or exchanged before it runs out. The problem of electric vehicle dispatching falls into the category of the shortest path problem with resource renewal. In this paper, we study the shortest path problems in (1 electric transit bus scheduling and (2 electric truck routing with time windows. In these applications, a fully-charged battery allows running a limited operational distance, and the battery before depletion needs to be quickly charged or exchanged with a fully-charged one at a battery management facility. The limited distance and battery renewal result in a shortest path problem with resource renewal. We develop a label-correcting algorithm with state space relaxation to find optimal solutions. In the computational experiments, real-world road geometry data are used to generate realistic travel distances, and other types of data are obtained from the real world or randomly generated. The computational results show that the label-correcting algorithm performs very well.
Kalaji, AS; Hierons, RM; Swift, S
2009-01-01
The extended finite state machine (EFSM) is a powerful approach for modeling state-based systems. However, testing from EFSMs is complicated by the existence of infeasible paths. One important problem is the existence of a transition with a guard that references a counter variable whose value depends on previous transitions. The presence of such transitions in paths often leads to infeasible paths. This paper proposes a novel approach to bypass the counter problem. The proposed approach is ev...
TP-Space RRT – Kinematic Path Planning of Non-Holonomic Any-Shape Vehicles
Jose Luis Blanco
2015-05-01
Full Text Available The autonomous navigation of vehicles typically combines two kinds of methods: a path is first planned, and then the robot is driven by a local obstacle-avoidance controller. The present work, which focuses on path planning, proposes an extension to the well-known rapidly-exploring random tree (RRT algorithm to allow its integration with a trajectory parameter-space (TP-space as an efficient method to detect collision-free, kinematically-feasible paths for arbitrarily-shaped vehicles. In contrast to original RRT, this proposal generates navigation trees, with poses as nodes, whose edges are all kinematically-feasible paths, suitable to being accurately followed by vehicles driven by pure reactive algorithms. Initial experiments demonstrate the suitability of the method with an Ackermann-steering vehicle model whose severe kinematic constraints cannot be obviated. An important result that sets this work apart from previous research is the finding that employing several families of potential trajectories to expand the tree, which can be done efficiently under the TP-space formalism, improves the optimality of the planned trajectories. A reference C++ implementation has been released as open-source.
Path Planning Method for UUV Homing and Docking in Movement Disorders Environment
Zheping Yan
2014-01-01
Full Text Available Path planning method for unmanned underwater vehicles (UUV homing and docking in movement disorders environment is proposed in this paper. Firstly, cost function is proposed for path planning. Then, a novel particle swarm optimization (NPSO is proposed and applied to find the waypoint with minimum value of cost function. Then, a strategy for UUV enters into the mother vessel with a fixed angle being proposed. Finally, the test function is introduced to analyze the performance of NPSO and compare with basic particle swarm optimization (BPSO, inertia weight particle swarm optimization (LWPSO, EPSO, and time-varying acceleration coefficient (TVAC. It has turned out that, for unimodal functions, NPSO performed better searching accuracy and stability than other algorithms, and, for multimodal functions, the performance of NPSO is similar to TVAC. Then, the simulation of UUV path planning is presented, and it showed that, with the strategy proposed in this paper, UUV can dodge obstacles and threats, and search for the efficiency path.
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.
Task path planning, scheduling and learning for free-ranging robot systems
Wakefield, G. Steve
1987-01-01
The development of robotics applications for space operations is often restricted by the limited movement available to guided robots. Free ranging robots can offer greater flexibility than physically guided robots in these applications. Presented here is an object oriented approach to path planning and task scheduling for free-ranging robots that allows the dynamic determination of paths based on the current environment. The system also provides task learning for repetitive jobs. This approach provides a basis for the design of free-ranging robot systems which are adaptable to various environments and tasks.
PRELIMINARY PROJECT PLAN FOR LANSCE INTEGRATED FLIGHT PATHS 11A, 11B, 12, and 13
Bultman, D. H.; Weinacht, D.
2000-01-01
This Preliminary Project Plan Summarizes the Technical, Cost, and Schedule baselines for an integrated approach to developing several flight paths at the Manual Lujan Jr. Neutron Scattering Center at the Los Alamos Neutron Science Center. For example, the cost estimate is intended to serve only as a rough order of magnitude assessment of the cost that might be incurred as the flight paths are developed. Further refinement of the requirements and interfaces for each beamline will permit additional refinement and confidence in the accuracy of all three baselines (Technical, Cost, Schedule)
Pose estimation-based path planning for a tracked mobile robot traversing uneven terrains
Jun , Jae-Yun; Saut , Jean-Philippe; Benamar , Faïz
2015-01-01
International audience; A novel path-planning algorithm is proposed for a tracked mobile robot to traverse uneven terrains, which can efficiently search for stability sub-optimal paths. This algorithm consists of combining two RRT-like algorithms (the Transition-based RRT (T-RRT) and the Dynamic-Domain RRT (DD-RRT) algorithms) bidirectionally and of representing the robot-terrain interaction with the robot’s quasi-static tip-over stability measure (assuming that the robot traverses uneven ter...
Path Planning of Free-Floating Robot in Cartesian Space Using Direct Kinematics
Wenfu Xu
2007-03-01
Full Text Available Dynamic singularities make it difficult to plan the Cartesian path of free-floating robot. In order to avoid its effect, the direct kinematic equations are used for path planning in the paper. Here, the joint position, rate and acceleration are bounded. Firstly, the joint trajectories are parameterized by polynomial or sinusoidal functions. And the two parametric functions are compared in details. It is the first contribution of the paper that polynomial functions can be used when the joint angles are limited(In the similar work of other researchers, only sinusoidla functions could be used. Secondly, the joint functions are normalized and the system of equations about the parameters is established by integrating the differential kinematics equations. Normalization is another contribution of the paper. After normalization, the boundary of the parameters is determined beforehand, and the general criterion to assign the initial guess of the unknown parameters is supplied. The criterion is independent on the planning conditions such as the total time tf. Finally, the parametes are solved by the iterative Newtonian method. Modification of tf may not result in the recalculation of the parameters. Simulation results verify the path planning method.
Path Planning of Free-Floating Robot in Cartesian Space Using Direct Kinematics
Wenfu Xu
2008-11-01
Full Text Available Dynamic singularities make it difficult to plan the Cartesian path of freefloating robot. In order to avoid its effect, the direct kinematic equations are used for path planning in the paper. Here, the joint position, rate and acceleration are bounded. Firstly, the joint trajectories are parameterized by polynomial or sinusoidal functions. And the two parametric functions are compared in details. It is the first contribution of the paper that polynomial functions can be used when the joint angles are limited(In the similar work of other researchers, only sinusoidla functions could be used. Secondly, the joint functions are normalized and the system of equations about the parameters is established by integrating the differential kinematics equations. Normalization is another contribution of the paper. After normalization, the boundary of the parameters is determined beforehand, and the general criterion to assign the initial guess of the unknown parameters is supplied. The criterion is independent on the planning conditions such as the total time tf. Finally, the parametes are solved by the iterative Newtonian method. Modification of tf may not result in the recalculation of the parameters. Simulation results verify the path planning method.
Construction of Optimal-Path Maps for Homogeneous-Cost-Region Path-Planning Problems
1989-09-01
of Artificial Inteligence , 9%,4. 24. Kirkpatrick, S., Gelatt Jr., C. D., and Vecchi, M. P., "Optinization by Sinmulated Ani- nealing", Science, Vol...studied in depth by researchers in such fields as artificial intelligence, robot;cs, and computa- tional geometry. Most methods require homogeneous...the results of the research. 10 U. L SLEVANT RESEARCH A. APPLICABLE CONCEPTS FROM ARTIFICIAL INTELLIGENCE 1. Search Methods One of the central
IRIS Assessment Plan for Uranium (Scoping and Problem Formulation Materials)
In January 2018, EPA released the IRIS Assessment Plan for Uranium (Oral Reference Dose) (Scoping and Problem Formulation Materials). An IRIS Assessment Plan (IAP) communicates to the public the plan for assessing each individual chemical and includes summary informatio...
Evaluation of a New Backtrack Free Path Planning Algorithm for Manipulators
Islam, Md. Nazrul; Tamura, Shinsuke; Murata, Tomonari; Yanase, Tatsuro
This paper evaluates a newly proposed backtrack free path planning algorithm (BFA) for manipulators. BFA is an exact algorithm, i.e. it is resolution complete. Different from existing resolution complete algorithms, its computation time and memory space are proportional to the number of arms. Therefore paths can be calculated within practical and predetermined time even for manipulators with many arms, and it becomes possible to plan complicated motions of multi-arm manipulators in fully automated environments. The performance of BFA is evaluated for 2-dimensional environments while changing the number of arms and obstacle placements. Its performance under locus and attitude constraints is also evaluated. Evaluation results show that the computation volume of the algorithm is almost the same as the theoretical one, i.e. it increases linearly with the number of arms even in complicated environments. Moreover BFA achieves the constant performance independent of environments.
Optimal path planning for a mobile robot using cuckoo search algorithm
Mohanty, Prases K.; Parhi, Dayal R.
2016-03-01
The shortest/optimal path planning is essential for efficient operation of autonomous vehicles. In this article, a new nature-inspired meta-heuristic algorithm has been applied for mobile robot path planning in an unknown or partially known environment populated by a variety of static obstacles. This meta-heuristic algorithm is based on the levy flight behaviour and brood parasitic behaviour of cuckoos. A new objective function has been formulated between the robots and the target and obstacles, which satisfied the conditions of obstacle avoidance and target-seeking behaviour of robots present in the terrain. Depending upon the objective function value of each nest (cuckoo) in the swarm, the robot avoids obstacles and proceeds towards the target. The smooth optimal trajectory is framed with this algorithm when the robot reaches its goal. Some simulation and experimental results are presented at the end of the paper to show the effectiveness of the proposed navigational controller.
An Efficient Energy Constraint Based UAV Path Planning for Search and Coverage
German Gramajo
2017-01-01
Full Text Available A path planning strategy for a search and coverage mission for a small UAV that maximizes the area covered based on stored energy and maneuverability constraints is presented. The proposed formulation has a high level of autonomy, without requiring an exact choice of optimization parameters, and is appropriate for real-time implementation. The computed trajectory maximizes spatial coverage while closely satisfying terminal constraints on the position of the vehicle and minimizing the time of flight. Comparisons of this formulation to a path planning algorithm based on those with time constraint show equivalent coverage performance but improvement in prediction of overall mission duration and accuracy of the terminal position of the vehicle.
A minimum resource neural network framework for solving multiconstraint shortest path problems.
Zhang, Junying; Zhao, Xiaoxue; He, Xiaotao
2014-08-01
Characterized by using minimum hard (structural) and soft (computational) resources, a novel parameter-free minimal resource neural network (MRNN) framework is proposed for solving a wide range of single-source shortest path (SP) problems for various graph types. The problems are the k-shortest time path problems with any combination of three constraints: time, hop, and label constraints, and the graphs can be directed, undirected, or bidirected with symmetric and/or asymmetric traversal time, which can be real and time dependent. Isomorphic to the graph where the SP is to be sought, the network is activated by generating autowave at source neuron and the autowave travels automatically along the paths with the speed of a hop in an iteration. Properties of the network are studied, algorithms are presented, and computation complexity is analyzed. The framework guarantees globally optimal solutions of a series of problems during the iteration process of the network, which provides insight into why even the SP is still too long to be satisfied. The network facilitates very large scale integrated circuit implementation and adapt to very large scale problems due to its massively parallel processing and minimum resource utilization. When implemented in a sequentially processing computer, experiments on synthetic graphs, road maps of cities of the USA, and vehicle routing with time windows indicate that the MRNN is especially efficient for large scale sparse graphs and even dense graphs with some constraints, e.g., the CPU time taken and the iteration number used for the road maps of cities of the USA is even less than ∼ 2% and 0.5% that of the Dijkstra's algorithm.
An Efficient Energy Constraint Based UAV Path Planning for Search and Coverage
Gramajo, German; Shankar, Praveen
2017-01-01
A path planning strategy for a search and coverage mission for a small UAV that maximizes the area covered based on stored energy and maneuverability constraints is presented. The proposed formulation has a high level of autonomy, without requiring an exact choice of optimization parameters, and is appropriate for real-time implementation. The computed trajectory maximizes spatial coverage while closely satisfying terminal constraints on the position of the vehicle and minimizing the time of ...
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.
PATH1 self-teaching curriculum: example problems for Pathways-to-Man Model
Helton, J.C.; Finley, N.C.
1982-10-01
The Pathways-to-Man Model was developed at Sandia National Laboratories to represent the environmental movement and human uptake of radionuclides. This model is implemented by the computer program PATH1. The purpose of this document is to present a sequence of examples of facilitate use of the model and the computer program which implements it. Each example consists of a brief description of the problem under consideration, a discussion of the data cards required to input the problem to PATH1, and the resultant program output. These examples are intended for use in conjunction with the technical report which describes the model and the computer progam which implements it (NUREG/CR-1636, Vol 1; SAND78-1711). In addition, a sequence of appendices provides the following: a description of a surface hydrologic system used in constructing several of the examples, a discussion of mixed-cell models, and a discussion of selected mathematical topics related to the Pathways Model. A copy of the program PATH1 is included with the report
Path planning for first responders in the presence of moving obstacles
Zhiyong Wang
2015-06-01
Full Text Available Navigation services have gained much importance for all kinds of human activities ranging from tourist navigation to support of rescue teams in disaster management. However, despite the considerable amount of route guidance research that has been performed, many issues that are related to navigation for first responders still need to be addressed. During disasters, emergencies can result in different types of moving obstacles (e.g., fires, plumes, floods, which make some parts of the road network temporarily unavailable. After such incidents occur, responders have to go to different destinations to perform their tasks in the environment affected by the disaster. Therefore they need a path planner that is capable of dealing with such moving obstacles, as well as generating and coordinating their routes quickly and efficiently. During the past decades, more and more hazard simulations, which can modify the models with incorporation of dynamic data from the field, have been developed. These hazard simulations use methods such as data assimilation, stochastic estimation, and adaptive measurement techniques, and are able to generate more reliable results of hazards. This would allow the hazard simulation models to provide valuable information regarding the state of road networks affected by hazards, which supports path planning for first responders among the moving obstacles. The objective of this research is to develop an integrated navigation system for first responders in the presence of moving obstacles. Such system should be able to navigate one or more responders to one or multiple destinations avoiding the moving obstacles, using the predicted information of the moving obstacles generated from by hazard simulations. In this dissertation, the objective we have is expressed as the following research question: How do we safely and efficiently navigate one or more first responders to one or more destinations avoiding moving obstacles? To address
Yueyue Deng
2013-01-01
Full Text Available Dynamic and unstructured multiple cooperative autonomous underwater vehicle (AUV missions are highly complex operations, and task allocation and path planning are made significantly more challenging under realistic underwater acoustic communication constraints. This paper presents a solution for the task allocation and path planning for multiple AUVs under marginal acoustic communication conditions: a location-aided task allocation framework (LAAF algorithm for multitarget task assignment and the grid-based multiobjective optimal programming (GMOOP mathematical model for finding an optimal vehicle command decision given a set of objectives and constraints. Both the LAAF and GMOOP algorithms are well suited in poor acoustic network condition and dynamic environment. Our research is based on an existing mobile ad hoc network underwater acoustic simulator and blind flooding routing protocol. Simulation results demonstrate that the location-aided auction strategy performs significantly better than the well-accepted auction algorithm developed by Bertsekas in terms of task-allocation time and network bandwidth consumption. We also demonstrate that the GMOOP path-planning technique provides an efficient method for executing multiobjective tasks by cooperative agents with limited communication capabilities. This is in contrast to existing multiobjective action selection methods that are limited to networks where constant, reliable communication is assumed to be available.
High-order Path Integral Monte Carlo methods for solving strongly correlated fermion problems
Chin, Siu A.
2015-03-01
In solving for the ground state of a strongly correlated many-fermion system, the conventional second-order Path Integral Monte Carlo method is plagued with the sign problem. This is due to the large number of anti-symmetric free fermion propagators that are needed to extract the square of the ground state wave function at large imaginary time. In this work, I show that optimized fourth-order Path Integral Monte Carlo methods, which uses no more than 5 free-fermion propagators, in conjunction with the use of the Hamiltonian energy estimator, can yield accurate ground state energies for quantum dots with up to 20 polarized electrons. The correlations are directly built-in and no explicit wave functions are needed. This work is supported by the Qatar National Research Fund NPRP GRANT #5-674-1-114.
GRASP with path-relinking for the selective pickup and delivery problem
Ho, Sin C.; Szeto, W. Y.
2016-01-01
Bike sharing systems are very popular nowadays. One of the characteristics is that bikes are picked up from some surplus bike stations and transported to all deficit bike stations by a repositioning vehicle with limited capacity to satisfy the demand of deficit bike stations. Motivated by this real...... world bicycle repositioning problem, we study the selective pickup and delivery problem, where demand at every delivery node has to be satisfied by the supply collected from a subset of pickup nodes. The objective is to minimize the total travel cost incurred from visiting the nodes. We present a GRASP...... with path-relinking for solving the described problem. Experimental results show that this simple heuristic improves the existing results in the literature with an average improvement of 5.72% using small computing times. The proposed heuristic can contribute to the development of effective and efficient...
Wang, Po-Jen; Keyawa, Nicholas R.; Euler, Craig
2012-01-01
In order to achieve highly accurate motion control and path planning for a mobile robot, an obstacle avoidance algorithm that provided a desired instantaneous turning radius and velocity was generated. This type of obstacle avoidance algorithm, which has been implemented in California State University Northridge's Intelligent Ground Vehicle (IGV), is known as Radial Polar Histogram (RPH). The RPH algorithm utilizes raw data in the form of a polar histogram that is read from a Laser Range Finder (LRF) and a camera. A desired open block is determined from the raw data utilizing a navigational heading and an elliptical approximation. The left and right most radii are determined from the calculated edges of the open block and provide the range of possible radial paths the IGV can travel through. In addition, the calculated obstacle edge positions allow the IGV to recognize complex obstacle arrangements and to slow down accordingly. A radial path optimization function calculates the best radial path between the left and right most radii and is sent to motion control for speed determination. Overall, the RPH algorithm allows the IGV to autonomously travel at average speeds of 3mph while avoiding all obstacles, with a processing time of approximately 10ms.
Integrated flight path planning system and flight control system for unmanned helicopters.
Jan, Shau Shiun; Lin, Yu Hsiang
2011-01-01
This paper focuses on the design of an integrated navigation and guidance system for unmanned helicopters. The integrated navigation system comprises two systems: the Flight Path Planning System (FPPS) and the Flight Control System (FCS). The FPPS finds the shortest flight path by the A-Star (A*) algorithm in an adaptive manner for different flight conditions, and the FPPS can add a forbidden zone to stop the unmanned helicopter from crossing over into dangerous areas. In this paper, the FPPS computation time is reduced by the multi-resolution scheme, and the flight path quality is improved by the path smoothing methods. Meanwhile, the FCS includes the fuzzy inference systems (FISs) based on the fuzzy logic. By using expert knowledge and experience to train the FIS, the controller can operate the unmanned helicopter without dynamic models. The integrated system of the FPPS and the FCS is aimed at providing navigation and guidance to the mission destination and it is implemented by coupling the flight simulation software, X-Plane, and the computing software, MATLAB. Simulations are performed and shown in real time three-dimensional animations. Finally, the integrated system is demonstrated to work successfully in controlling the unmanned helicopter to operate in various terrains of a digital elevation model (DEM).
Integrated Flight Path Planning System and Flight Control System for Unmanned Helicopters
Jan, Shau Shiun; Lin, Yu Hsiang
2011-01-01
This paper focuses on the design of an integrated navigation and guidance system for unmanned helicopters. The integrated navigation system comprises two systems: the Flight Path Planning System (FPPS) and the Flight Control System (FCS). The FPPS finds the shortest flight path by the A-Star (A*) algorithm in an adaptive manner for different flight conditions, and the FPPS can add a forbidden zone to stop the unmanned helicopter from crossing over into dangerous areas. In this paper, the FPPS computation time is reduced by the multi-resolution scheme, and the flight path quality is improved by the path smoothing methods. Meanwhile, the FCS includes the fuzzy inference systems (FISs) based on the fuzzy logic. By using expert knowledge and experience to train the FIS, the controller can operate the unmanned helicopter without dynamic models. The integrated system of the FPPS and the FCS is aimed at providing navigation and guidance to the mission destination and it is implemented by coupling the flight simulation software, X-Plane, and the computing software, MATLAB. Simulations are performed and shown in real time three-dimensional animations. Finally, the integrated system is demonstrated to work successfully in controlling the unmanned helicopter to operate in various terrains of a digital elevation model (DEM). PMID:22164029
Jean Chamberlain Chedjou
2015-01-01
Full Text Available This paper develops a flexible analytical concept for robust shortest path detection in dynamically reconfigurable graphs. The concept is expressed by a mathematical model representing the shortest path problem solver. The proposed mathematical model is characterized by three fundamental parameters expressing (a the graph topology (through the “incidence matrix”, (b the edge weights (with dynamic external weights’ setting capability, and (c the dynamic reconfigurability through external input(s of the source-destination nodes pair. In order to demonstrate the universality of the developed concept, a general algorithm is proposed to determine the three fundamental parameters (of the mathematical model developed for all types of graphs regardless of their topology, magnitude, and size. It is demonstrated that the main advantage of the developed concept is that arc costs, the origin-destination pair setting, and the graph topology are dynamically provided by external commands, which are inputs of the shortest path solver model. This enables high flexibility and full reconfigurability of the developed concept, without any retraining need. To validate the concept developed, benchmarking is performed leading to a comparison of its performance with the performances of two well-known concepts based on neural networks.
Calzetta, E.; Hu, B.L.
1987-01-01
We discuss the generalization to curved spacetime of a path-integral formalism of quantum field theory based on the sum over paths first going forward in time in the presence of one external source from an in vacuum to a state defined on a hypersurface of constant time in the future, and then backwards in time in the presence of a different source to the same in vacuum. This closed-time-path formalism which generalizes the conventional method based on in-out vacuum persistence amplitudes yields real and causal effective actions, field equations, and expectation values. We apply this method to two problems in semiclassical cosmology. First we study the back reaction of particle production in a radiation-filled Bianchi type-I universe with a conformal scalar field. Unlike the in-out formalism which yields complex geometries the real and causal effective action here yields equations for real effective geometries, with more readily interpretable results. It also provides a clear identification of particle production as a dissipative process in semiclassical theories. In the second problem we calculate the vacuum expectation value of the stress-energy tensor for a nonconformal massive λphi 4 theory in a Robertson-Walker universe. This study serves to illustrate the use of Feynman diagrams and higher-loop calculations in this formalism. It also demonstrates the economy of this method in the calculation of expectation values over the mode-sum Bogolubov transformation methods ordinarily applied to matrix elements calculated in the conventional in-out approach
Mário Mestria
2013-08-01
Full Text Available The Clustered Traveling Salesman Problem (CTSP is a generalization of the Traveling Salesman Problem (TSP in which the set of vertices is partitioned into disjoint clusters and objective is to find a minimum cost Hamiltonian cycle such that the vertices of each cluster are visited contiguously. The CTSP is NP-hard and, in this context, we are proposed heuristic methods for the CTSP using GRASP, Path Relinking and Variable Neighborhood Descent (VND. The heuristic methods were tested using Euclidean instances with up to 2000 vertices and clusters varying between 4 to 150 vertices. The computational tests were performed to compare the performance of the heuristic methods with an exact algorithm using the Parallel CPLEX software. The computational results showed that the hybrid heuristic method using VND outperforms other heuristic methods.
Enroute flight-path planning - Cooperative performance of flight crews and knowledge-based systems
Smith, Philip J.; Mccoy, Elaine; Layton, Chuck; Galdes, Deb
1989-01-01
Interface design issues associated with the introduction of knowledge-based systems into the cockpit are discussed. Such issues include not only questions about display and control design, they also include deeper system design issues such as questions about the alternative roles and responsibilities of the flight crew and the computer system. In addition, the feasibility of using enroute flight path planning as a context for exploring such research questions is considered. In particular, the development of a prototyping shell that allows rapid design and study of alternative interfaces and system designs is discussed.
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.
Optimal multi-agent path planning for fast inverse modeling in UAV-based flood sensing applications
Abdelkader, Mohamed
2014-05-01
Floods are the most common natural disasters, causing thousands of casualties every year in the world. In particular, flash flood events are particularly deadly because of the short timescales on which they occur. Unmanned air vehicles equipped with mobile microsensors could be capable of sensing flash floods in real time, saving lives and greatly improving the efficiency of the emergency response. However, of the main issues arising with sensing floods is the difficulty of planning the path of the sensing agents in advance so as to obtain meaningful data as fast as possible. In this particle, we present a fast numerical scheme to quickly compute the trajectories of a set of UAVs in order to maximize the accuracy of model parameter estimation over a time horizon. Simulation results are presented, a preliminary testbed is briefly described, and future research directions and problems are discussed. © 2014 IEEE.
Wei, Kun; Ren, Bingyin
2018-02-13
In a future intelligent factory, a robotic manipulator must work efficiently and safely in a Human-Robot collaborative and dynamic unstructured environment. Autonomous path planning is the most important issue which must be resolved first in the process of improving robotic manipulator intelligence. Among the path-planning methods, the Rapidly Exploring Random Tree (RRT) algorithm based on random sampling has been widely applied in dynamic path planning for a high-dimensional robotic manipulator, especially in a complex environment because of its probability completeness, perfect expansion, and fast exploring speed over other planning methods. However, the existing RRT algorithm has a limitation in path planning for a robotic manipulator in a dynamic unstructured environment. Therefore, an autonomous obstacle avoidance dynamic path-planning method for a robotic manipulator based on an improved RRT algorithm, called Smoothly RRT (S-RRT), is proposed. This method that targets a directional node extends and can increase the sampling speed and efficiency of RRT dramatically. A path optimization strategy based on the maximum curvature constraint is presented to generate a smooth and curved continuous executable path for a robotic manipulator. Finally, the correctness, effectiveness, and practicability of the proposed method are demonstrated and validated via a MATLAB static simulation and a Robot Operating System (ROS) dynamic simulation environment as well as a real autonomous obstacle avoidance experiment in a dynamic unstructured environment for a robotic manipulator. The proposed method not only provides great practical engineering significance for a robotic manipulator's obstacle avoidance in an intelligent factory, but also theoretical reference value for other type of robots' path planning.
Tuvshinjargal, Doopalam; Lee, Deok Jin [Kunsan National University, Gunsan (Korea, Republic of)
2015-06-15
In this paper, an efficient dynamic reactive motion planning method for an autonomous vehicle in a dynamic environment is proposed. The purpose of the proposed method is to improve the robustness of autonomous robot motion planning capabilities within dynamic, uncertain environments by integrating a virtual plane-based reactive motion planning technique with a sensor fusion-based obstacle detection approach. The dynamic reactive motion planning method assumes a local observer in the virtual plane, which allows the effective transformation of complex dynamic planning problems into simple stationary ones proving the speed and orientation information between the robot and obstacles. In addition, the sensor fusion-based obstacle detection technique allows the pose estimation of moving obstacles using a Kinect sensor and sonar sensors, thus improving the accuracy and robustness of the reactive motion planning approach. The performance of the proposed method was demonstrated through not only simulation studies but also field experiments using multiple moving obstacles in hostile dynamic environments.
Tuvshinjargal, Doopalam; Lee, Deok Jin
2015-01-01
In this paper, an efficient dynamic reactive motion planning method for an autonomous vehicle in a dynamic environment is proposed. The purpose of the proposed method is to improve the robustness of autonomous robot motion planning capabilities within dynamic, uncertain environments by integrating a virtual plane-based reactive motion planning technique with a sensor fusion-based obstacle detection approach. The dynamic reactive motion planning method assumes a local observer in the virtual plane, which allows the effective transformation of complex dynamic planning problems into simple stationary ones proving the speed and orientation information between the robot and obstacles. In addition, the sensor fusion-based obstacle detection technique allows the pose estimation of moving obstacles using a Kinect sensor and sonar sensors, thus improving the accuracy and robustness of the reactive motion planning approach. The performance of the proposed method was demonstrated through not only simulation studies but also field experiments using multiple moving obstacles in hostile dynamic environments
Ramos, A G; García-Garrido, V J; Mancho, A M; Wiggins, S; Coca, J; Glenn, S; Schofield, O; Kohut, J; Aragon, D; Kerfoot, J; Haskins, T; Miles, T; Haldeman, C; Strandskov, N; Allsup, B; Jones, C; Shapiro, J
2018-03-15
Transoceanic Gliders are Autonomous Underwater Vehicles (AUVs) for which there is a developing and expanding range of applications in open-seas research, technology and underwater clean transport. Mature glider autonomy, operating depth (0-1000 meters) and low energy consumption without a CO 2 footprint enable evolutionary access across ocean basins. Pursuant to the first successful transatlantic glider crossing in December 2009, the Challenger Mission has opened the door to long-term, long-distance routine transoceanic AUV missions. These vehicles, which glide through the water column between 0 and 1000 meters depth, are highly sensitive to the ocean current field. Consequently, it is essential to exploit the complex space-time structure of the ocean current field in order to plan a path that optimizes scientific payoff and navigation efficiency. This letter demonstrates the capability of dynamical system theory for achieving this goal by realizing the real-time navigation strategy for the transoceanic AUV named Silbo, which is a Slocum deep-glider (0-1000 m), that crossed the North Atlantic from April 2016 to March 2017. Path planning in real time based on this approach has facilitated an impressive speed up of the AUV to unprecedented velocities resulting in major battery savings on the mission, offering the potential for routine transoceanic long duration missions.
Optimal path planning for single and multiple aircraft using a reduced order formulation
Twigg, Shannon S.
High-flying unmanned reconnaissance and surveillance systems are now being used extensively in the United States military. Current development programs are producing demonstrations of next-generation unmanned flight systems that are designed to perform combat missions. Their use in first-strike combat operations will dictate operations in densely cluttered environments that include unknown obstacles and threats, and will require the use of terrain for masking. The demand for autonomy of operations in such environments dictates the need for advanced trajectory optimization capabilities. In addition, the ability to coordinate the movements of more than one aircraft in the same area is an emerging challenge. This thesis examines using an analytical reduced order formulation for trajectory generation for minimum time and terrain masking cases. First, pseudo-3D constant velocity equations of motion are used for path planning for a single vehicle. In addition, the inclusion of winds, moving targets and moving threats is considered. Then, this formulation is increased to using 3D equations of motion, both with a constant velocity and with a simplified varying velocity model. Next, the constant velocity equations of motion are expanded to include the simultaneous path planning of an unspecified number of vehicles, for both aircraft avoidance situations and formation flight cases.
Population Problems and Family Planning in Africa.
Uche, Chukwudum
The focal points of this essay are the population problems in Africa and what the African peoples and governments are doing about them. It is stated cagegorically that a problem does exist. Indicators often used to deny this position are population density and pressure, undeveloped resources, the availability of empty lands, and alleged intrigue…
Applying Column Generation to the Discrete Fleet Planning Problem
Bosman, M.G.C.; Bakker, Vincent; Molderink, Albert; Hurink, Johann L.; Smit, Gerardus Johannes Maria
2010-01-01
The paper discusses an Integer Linear Programming (ILP) formulation that describes the problem of planning the use of domestic distributed generators, under individual as well as fleet constraints. The planning problem comprises the assignment of time intervals during which the local generator must
Numerical continuation methods for dynamical systems path following and boundary value problems
Krauskopf, Bernd; Galan-Vioque, Jorge
2007-01-01
Path following in combination with boundary value problem solvers has emerged as a continuing and strong influence in the development of dynamical systems theory and its application. It is widely acknowledged that the software package AUTO - developed by Eusebius J. Doedel about thirty years ago and further expanded and developed ever since - plays a central role in the brief history of numerical continuation. This book has been compiled on the occasion of Sebius Doedel''s 60th birthday. Bringing together for the first time a large amount of material in a single, accessible source, it is hoped that the book will become the natural entry point for researchers in diverse disciplines who wish to learn what numerical continuation techniques can achieve. The book opens with a foreword by Herbert B. Keller and lecture notes by Sebius Doedel himself that introduce the basic concepts of numerical bifurcation analysis. The other chapters by leading experts discuss continuation for various types of systems and objects ...
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.
Wan-Yu Liu
2014-07-01
Full Text Available Torespondto the reduction of greenhouse gas emissions and global warming, this paper investigates the minimal-carbon-footprint time-dependent heterogeneous-fleet vehicle routing problem with alternative paths (MTHVRPP. This finds a route with the smallestcarbon footprint, instead of the shortestroute distance, which is the conventional approach, to serve a number of customers with a heterogeneous fleet of vehicles in cases wherethere may not be only one path between each pair of customers, and the vehicle speed differs at different times of the day. Inheriting from the NP-hardness of the vehicle routing problem, the MTHVRPP is also NP-hard. This paper further proposes a genetic algorithm (GA to solve this problem. The solution representedbyour GA determines the customer serving ordering of each vehicle type. Then, the capacity check is used to classify multiple routes of each vehicle type, and the path selection determines the detailed paths of each route. Additionally, this paper improves the energy consumption model used for calculating the carbon footprint amount more precisely. Compared with the results without alternative paths, our experimental results show that the alternative path in this experimenthas a significant impact on the experimental results in terms of carbon footprint.
Reachability problems in scheduling and planning
Eggermont, C.E.J.
2012-01-01
Reachability problems are fundamental in the context of many mathematical models and abstractions which describe various computational processes. Intuitively, when many objects move within a shared environment, objects may have to wait for others before moving and so slow down, or objects may even
Global and Local Path Planning Study in a ROS-Based Research Platform for Autonomous Vehicles
Pablo Marin-Plaza
2018-01-01
Full Text Available The aim of this work is to integrate and analyze the performance of a path planning method based on Time Elastic Bands (TEB in real research platform based on Ackermann model. Moreover, it will be proved that all modules related to the navigation can coexist and work together to achieve the goal point without any collision. The study is done by analyzing the trajectory generated from global and local planners. The software prototyping tool is Robot Operating System (ROS from Open Source Robotics Foundation and the research platform is the iCab (Intelligent Campus Automobile from University Carlos III. This work has been validated from a test inside the campus where the iCab has performed the navigation between the starting point and the goal point without any collision. During the experiment, we proved the low sensitivity of the TEB method to variations of the vehicle model configuration and constraints.
Optimal path planning for video-guided smart munitions via multitarget tracking
Borkowski, Jeffrey M.; Vasquez, Juan R.
2006-05-01
An advent in the development of smart munitions entails autonomously modifying target selection during flight in order to maximize the value of the target being destroyed. A unique guidance law can be constructed that exploits both attribute and kinematic data obtained from an onboard video sensor. An optimal path planning algorithm has been developed with the goals of obstacle avoidance and maximizing the value of the target impacted by the munition. Target identification and classification provides a basis for target value which is used in conjunction with multi-target tracks to determine an optimal waypoint for the munition. A dynamically feasible trajectory is computed to provide constraints on the waypoint selection. Results demonstrate the ability of the autonomous system to avoid moving obstacles and revise target selection in flight.
MR-based real time path planning for cardiac operations with transapical access.
Yeniaras, Erol; Navkar, Nikhil V; Sonmez, Ahmet E; Shah, Dipan J; Deng, Zhigang; Tsekos, Nikolaos V
2011-01-01
Minimally invasive surgeries (MIS) have been perpetually evolving due to their potential high impact on improving patient management and overall cost effectiveness. Currently, MIS are further strengthened by the incorporation of magnetic resonance imaging (MRI) for amended visualization and high precision. Motivated by the fact that real-time MRI is emerging as a feasible modality especially for guiding interventions and surgeries in the beating heart; in this paper we introduce a real-time path planning algorithm for intracardiac procedures. Our approach creates a volumetric safety zone inside a beating heart and updates it on-the-fly using real-time MRI during the deployment of a robotic device. In order to prove the concept and assess the feasibility of the introduced method, a realistic operational scenario of transapical aortic valve replacement in a beating heart is chosen as the virtual case study.
New Design of Mobile Robot Path Planning with Randomly Moving Obstacles
T. A. Salih
2013-05-01
Full Text Available The navigation of a mobile robot in an unknown environment has always been a very challenging task. In order to achieve safe and autonomous navigation, the mobile robot needs to sense the surrounding environment and plans a collision-free path. This paper focuses on designing and implementing a mobile robot which has the ability of navigating smoothly in an unknown environment, avoiding collisions, without having to stop in front of obstacles, detecting leakage of combustible gases and transmitting a message of detection results to the civil defense unit automatically through the Internet to the E-mail. This design uses the implementation of artificial neural network (ANN on a new technology represented by Field Programmable Analog Array (FPAA for controlling the motion of the robot. The robot with the proposed controller is tested and has completed the required objective successfully.
Vessels Route Planning Problem with Uncertain Data
Tomasz Neumann
2016-09-01
Full Text Available The purpose of this paper is to find a solution for route planning in a transport networks, where the costs of tracks, factor of safety and travel time are ambiguous. This approach is based on the Dempster-Shafer theory and well known Dijkstra's algorithm. In this approach important are the influencing factors of the mentioned coefficients using uncertain possibilities presented by probability intervals. Based on these intervals the quality intervals of each route can be determined. Applied decision rules can be described by the end user.
Path Planning of Mobile Elastic Robotic Arms by Indirect Approach of Optimal Control
Moharam Habibnejad Korayem
2011-03-01
Full Text Available Finding optimal trajectory is critical in several applications of robot manipulators. This paper is applied the open-loop optimal control approach for generating the optimal trajectory of the flexible mobile manipulators in point-to-point motion. This method is based on the Pontryagin-s minimum principle that by providing a two-point boundary value problem is solved the problem. This problem is known to be complex in particular when combined motion of the base and manipulator, non-holonomic constraint of the base and highly non-linear and complicated dynamic equations as a result of flexible nature of links are taken into account. The study emphasizes on modeling of the complete optimal control problem by remaining all nonlinear state and costate variables as well as control constraints. In this method, designer can compromise between different objectives by considering the proper penalty matrices and it yields to choose the proper trajectory among the various paths. The effectiveness and capability of the proposed approach are demonstrated through simulation studies. Finally, to verify the proposed method, the simulation results obtained from the model are compared with the results of those available in the literature.
Mak, C. H.
2009-01-01
A practical method to tackle the sign problem in real-time path integral simulations is proposed based on the multilevel blocking idea. The formulation is made possible by using a cumulant expansion of the action, which in addition to addressing the sign problem, provides an unbiased estimator for the action from a statistically noisy sample of real-time paths. The cumulant formulation also allows the analytical gradients of the action to be computed with little extra computational effort, and it can easily be implemented in a massively parallel environment.
Reaction-diffusion path planning in a hybrid chemical and cellular-automaton processor
Adamatzky, Andrew; Lacy Costello, Benjamin de
2003-01-01
To find the shortest collision-free path in a room containing obstacles we designed a chemical processor and coupled it with a cellular-automaton processor. In the chemical processor obstacles are represented by sites of high concentration of potassium iodide and a planar substrate is saturated with palladium chloride. Potassium iodide diffuses into the substrate and reacts with palladium chloride. A dark coloured precipitate of palladium iodide is formed almost everywhere except sites where two or more diffusion wavefronts collide. The less coloured sites are situated at the furthest distance from obstacles. Thus, the chemical processor develops a repulsive field, generated by obstacles. A snapshot of the chemical processor is inputted to a cellular automaton. The automaton behaves like a discrete excitable media; also, every cell of the automaton is supplied with a pointer that shows an origin of the cell's excitation. The excitation spreads along the cells corresponding to precipitate depleted sites of the chemical processor. When the destination-site is excited, waves travel on the lattice and update the orientations of the pointers. Thus, the automaton constructs a spanning tree, made of pointers, that guides a traveler towards the destination point. Thus, the automaton medium generates an attractive field and combination of this attractive field with the repulsive field, generated by the chemical processor, provides us with a solution of the collision-free path problem
Plans to Observe the 2017 Total Solar Eclipse from near the Path Edges
Waring Dunham, David; Nugent, Richard; Guhl, Konrad; Bode, Hans-Joachim
2015-08-01
The August 21st, 2017 solar eclipse provides a good opportunity, to time the totality contacts, other Baily’s bead phenomena, and observe other dynamic edge phenomena, from locations near the edges of the path of totality. A good network of roads and generally favorable weather prospects means that more observers will likely be able to deploy more equipment than during most previous eclipses. The value of contact and Baily’s bead timings of total solar eclipses, for determining solar diameter and intensity variations, was described in an earlier presentation in Focus Meeting 13. This presentation will concentrate on how observations of different types that have been used during past eclipses can be made by different observers, to obtain better information about the accuracy of the different types of observations for determining the mean solar diameter, and the systematic differences between them. A problem has been that the few observers who have attempted recording Baily’s beads from path edge locations have wanted to use the latest technology, to try to record the observations better, rather than try to make the observations in the same ways that were used for many past eclipses. Several observers trying different techniques at the same location, and doing that at several locations at different places along the path, is needed. Past techniques that we would like to compare include direct visual observation (but keeping eye safety in mind); visual observation of telescopically projected images; direct filtered video telescopic observations; and recording the flash spectrum. There are several towns that straddle the path edges. The International Occultation Timing Association would like to mobilize people in those towns to observe the eclipse from many places, to say whether or not the eclipse happened, and if it did, time it. A suitable cell phone app could be designed to report observations, including the observer’s location, as was attempted for an
Optimal Paths in Gliding Flight
Wolek, Artur
Underwater gliders are robust and long endurance ocean sampling platforms that are increasingly being deployed in coastal regions. This new environment is characterized by shallow waters and significant currents that can challenge the mobility of these efficient (but traditionally slow moving) vehicles. This dissertation aims to improve the performance of shallow water underwater gliders through path planning. The path planning problem is formulated for a dynamic particle (or "kinematic car") model. The objective is to identify the path which satisfies specified boundary conditions and minimizes a particular cost. Several cost functions are considered. The problem is addressed using optimal control theory. The length scales of interest for path planning are within a few turn radii. First, an approach is developed for planning minimum-time paths, for a fixed speed glider, that are sub-optimal but are guaranteed to be feasible in the presence of unknown time-varying currents. Next the minimum-time problem for a glider with speed controls, that may vary between the stall speed and the maximum speed, is solved. Last, optimal paths that minimize change in depth (equivalently, maximize range) are investigated. Recognizing that path planning alone cannot overcome all of the challenges associated with significant currents and shallow waters, the design of a novel underwater glider with improved capabilities is explored. A glider with a pneumatic buoyancy engine (allowing large, rapid buoyancy changes) and a cylindrical moving mass mechanism (generating large pitch and roll moments) is designed, manufactured, and tested to demonstrate potential improvements in speed and maneuverability.
Path planning in GPS-denied environments via collective intelligence of distributed sensor networks
Jha, Devesh K.; Chattopadhyay, Pritthi; Sarkar, Soumik; Ray, Asok
2016-05-01
This paper proposes a framework for reactive goal-directed navigation without global positioning facilities in unknown dynamic environments. A mobile sensor network is used for localising regions of interest for path planning of an autonomous mobile robot. The underlying theory is an extension of a generalised gossip algorithm that has been recently developed in a language-measure-theoretic setting. The algorithm has been used to propagate local decisions of target detection over a mobile sensor network and thus, it generates a belief map for the detected target over the network. In this setting, an autonomous mobile robot may communicate only with a few mobile sensing nodes in its own neighbourhood and localise itself relative to the communicating nodes with bounded uncertainties. The robot makes use of the knowledge based on the belief of the mobile sensors to generate a sequence of way-points, leading to a possible goal. The estimated way-points are used by a sampling-based motion planning algorithm to generate feasible trajectories for the robot. The proposed concept has been validated by numerical simulation on a mobile sensor network test-bed and a Dubin's car-like robot.
Shao, Zhongshi; Pi, Dechang; Shao, Weishi
2018-05-01
This article presents an effective estimation of distribution algorithm, named P-EDA, to solve the blocking flow-shop scheduling problem (BFSP) with the makespan criterion. In the P-EDA, a Nawaz-Enscore-Ham (NEH)-based heuristic and the random method are combined to generate the initial population. Based on several superior individuals provided by a modified linear rank selection, a probabilistic model is constructed to describe the probabilistic distribution of the promising solution space. The path relinking technique is incorporated into EDA to avoid blindness of the search and improve the convergence property. A modified referenced local search is designed to enhance the local exploitation. Moreover, a diversity-maintaining scheme is introduced into EDA to avoid deterioration of the population. Finally, the parameters of the proposed P-EDA are calibrated using a design of experiments approach. Simulation results and comparisons with some well-performing algorithms demonstrate the effectiveness of the P-EDA for solving BFSP.
Matthew Lyndon Armstrong
2015-12-01
Full Text Available This study explored how the Planning Alternatives Tomorrows with Hope (PATH process could enhance and strengthen an individual’s personal journey of recovery. This article utilised the knowledge base of members of a Community of Practice, located in Brisbane Australia. Members had a deep concern and passion to promote and strengthen wellbeing for people who live with the experience of mental ill health. They were invited to form a focus group to explore the use of PATH and its relationship with mental health wellness. After contemplating and reflecting on an example of the PATH process, the focus group explored opportunities for PATH to become one of many wellness resources for people experiencing and overcoming mental ill health. Through the exploration of personal meaning, storytelling and community connection (anchored in the visuals and graphics of the PATH example, the study found that PATH can make a valuable contribution by restoring some of the power inbalances in traditonal service frameworks and enhancing personal self direction. Keywords: mental health distress, practitioners, recovery, facilitation, creativity, planning
Plum, Christian Edinger Munk; Pisinger, David; Salazar-González, Juan-José
2012-01-01
The design of container shipping networks is an important real world problem, with assets and operational costs in billions of dollars. To guide the optimal deployment of the ships, a single vessel roundtrip is considered by minimizing operational costs and flowing the best paying cargo under...... commercial constraints. Inspiration for formulation and solution method is taken from the rich research done within pickup and delivery problems. The problem, the multicommodity one-toone pickup and delivery traveling salesman problem with path duration limits is, to the best of out knowledge, considered...... for the first time. An arc flow and a path flow model are presented. A Branch and Cut and Price solution method is proposed and implemented....
Yong Ma
2013-01-01
Full Text Available We present one algorithm based on particle swarm optimization (PSO with penalty function to determine the conflict-free path for mobile objects in four-dimension (three spatial and one-time dimensions with obstacles. The shortest path of the mobile object is set as goal function, which is constrained by conflict-free criterion, path smoothness, and velocity and acceleration requirements. This problem is formulated as a calculus of variation problem (CVP. With parametrization method, the CVP is converted to a time-varying nonlinear programming problem (TNLPP. Constraints of TNLPP are transformed to general TNLPP without any constraints through penalty functions. Then, by using a little calculations and applying the algorithm PSO, the solution of the CVP is consequently obtained. Approach efficiency is confirmed by numerical examples.
Pricing and Capacity Planning Problems in Energy Transmission Networks
Villumsen, Jonas Christoffer
strategy. In the Nordic electricity system a market with zonal prices is adopted. We consider the problem of designing zones in an optimal way explicitly considering uncertainty. Finally, we formulate the integrated problem of pipeline capacity expansion planning and transmission pricing in natural gas...... necessitates a radical change in the way we plan and operate energy systems. Another paradigm change which began in the 1990’s for electricity systems is that of deregulation. This has led to a variety of different market structures implemented across the world. In this thesis we discuss capacity planning...... and transmission pricing problems in energy transmission networks. Although the modelling framework applies to energy networks in general, most of the applications discussed concern the transmission of electricity. A number of the problems presented involves transmission switching, which allows the operator...
On some mathematical problems in the definition of Feynman path integral
Combe, P.; Rodriguez, R.; Sirugue-Collin, M.
1976-07-01
It is shown how integration on a Hilbert space of paths can be performed to get exact evolution of non relativistic quantum systems for a rather large class of potentials including polynomial interaction
Reliable Path Selection Problem in Uncertain Traffic Network after Natural Disaster
Jing Wang
2013-01-01
Full Text Available After natural disaster, especially for large-scale disasters and affected areas, vast relief materials are often needed. In the meantime, the traffic networks are always of uncertainty because of the disaster. In this paper, we assume that the edges in the network are either connected or blocked, and the connection probability of each edge is known. In order to ensure the arrival of these supplies at the affected areas, it is important to select a reliable path. A reliable path selection model is formulated, and two algorithms for solving this model are presented. Then, adjustable reliable path selection model is proposed when the edge of the selected reliable path is broken. And the corresponding algorithms are shown to be efficient both theoretically and numerically.
Dynamic Modeling and Soil Mechanics for Path Planning of the Mars Exploration Rovers
Trease, Brian; Arvidson, Raymond; Lindemann, Randel; Bennett, Keith; Zhou, Feng; Iagnemma, Karl; Senatore, Carmine; Van Dyke, Lauren
2011-01-01
To help minimize risk of high sinkage and slippage during drives and to better understand soil properties and rover terramechanics from drive data, a multidisciplinary team was formed under the Mars Exploration Rover (MER) project to develop and utilize dynamic computer-based models for rover drives over realistic terrains. The resulting tool, named ARTEMIS (Adams-based Rover Terramechanics and Mobility Interaction Simulator), consists of the dynamic model, a library of terramechanics subroutines, and the high-resolution digital elevation maps of the Mars surface. A 200-element model of the rovers was developed and validated for drop tests before launch, using MSC-Adams dynamic modeling software. Newly modeled terrain-rover interactions include the rut-formation effect of deformable soils, using the classical Bekker-Wong implementation of compaction resistances and bull-dozing effects. The paper presents the details and implementation of the model with two case studies based on actual MER telemetry data. In its final form, ARTEMIS will be used in a predictive manner to assess terrain navigability and will become part of the overall effort in path planning and navigation for both Martian and lunar rovers.
A GRASP algorithm for the container stowage slot planning problem
Parreno, Francisco; Pacino, Dario; Alvarez-Valdes, Ramon
2016-01-01
in clusters along the vessel. For each of those clusters a specific position for each container must be found. Compared to previous studies, we have introduced two new features: the explicit handling of rolled out containers and the inclusion of separations rules for dangerous cargo. We present a novel......This work presents a generalization of the Slot Planning Problem which raises when the liner shipping industry needs to plan the placement of containers within a vessel (stowage planning). State-of-the-art stowage planning relies on a heuristic decomposition where containers are first distributed...... integer programming formulation and a Greedy Randomized Adaptive Search Procedure (GRASP) to solve the problem. The approach is able to find high-quality solution within 1 s. We also provide comparison with the state-of-the-art on an existing and a new set of benchmark instances. (C) 2016 Elsevier Ltd...
An optimal control approach to manpower planning problem
H. W. J. Lee
2001-01-01
Full Text Available A manpower planning problem is studied in this paper. The model includes scheduling different types of workers over different tasks, employing and terminating different types of workers, and assigning different types of workers to various trainning programmes. The aim is to find an optimal way to do all these while keeping the time-varying demand for minimum number of workers working on each different tasks satisfied. The problem is posed as an optimal discrete-valued control problem in discrete time. A novel numerical scheme is proposed to solve the problem, and an illustrative example is provided.
Resolution and optimization methods for tour planning problems
Vasserot, Jean-Pierre
1976-12-01
The aim of this study is to describe computerized methods for the resolution of the computer supported tour planning problem. After a presentation of this problem in operational research, the different existing methods of resolution are reviewed with the different approaches which have led to their elaboration. Different critics and comparisons are made on these methods and some improvements and new procedures are proposed, some of them allowing to solve more general problems. Finally, the structure of such a program, made at the CII to solve this kind of problem under multiple constraints is analysed [fr
Polymorphic Uncertain Linear Programming for Generalized Production Planning Problems
Xinbo Zhang
2014-01-01
Full Text Available A polymorphic uncertain linear programming (PULP model is constructed to formulate a class of generalized production planning problems. In accordance with the practical environment, some factors such as the consumption of raw material, the limitation of resource and the demand of product are incorporated into the model as parameters of interval and fuzzy subsets, respectively. Based on the theory of fuzzy interval program and the modified possibility degree for the order of interval numbers, a deterministic equivalent formulation for this model is derived such that a robust solution for the uncertain optimization problem is obtained. Case study indicates that the constructed model and the proposed solution are useful to search for an optimal production plan for the polymorphic uncertain generalized production planning problems.
Daniel T. L. Shek
2011-01-01
Full Text Available The present study attempts to examine the longitudinal impact of a curriculum-based positive youth development program, entitled the Project P.A.T.H.S. (Positive Adolescent Training through Holistic Social Programmes, on adolescent problem behavior in Hong Kong. Using a longitudinal randomized group design, six waves of data were collected from 19 experimental schools (n = 3,797 at Wave 1 in which students participated in the Project P.A.T.H.S. and 24 control schools (n = 4,049 at Wave 1. At each wave, students responded to questions asking about their current problem behaviors, including delinquency and use of different types of drugs, and their intentions of engaging in such behaviors in the future. Results based on individual growth curve modeling generally showed that the participants displayed lower levels of substance abuse and delinquent behavior than did the control students. Participants who regarded the program to be helpful also showed lower levels of problem behavior than did the control students. The present findings suggest that the Project P.A.T.H.S. is effective in preventing adolescent problem behavior in the junior secondary school years.
Robust Optimization Model for Production Planning Problem under Uncertainty
Pembe GÜÇLÜ
2017-01-01
Full Text Available Conditions of businesses change very quickly. To take into account the uncertainty engendered by changes has become almost a rule while planning. Robust optimization techniques that are methods of handling uncertainty ensure to produce less sensitive results to changing conditions. Production planning, is to decide from which product, when and how much will be produced, with a most basic definition. Modeling and solution of the Production planning problems changes depending on structure of the production processes, parameters and variables. In this paper, it is aimed to generate and apply scenario based robust optimization model for capacitated two-stage multi-product production planning problem under parameter and demand uncertainty. With this purpose, production planning problem of a textile company that operate in İzmir has been modeled and solved, then deterministic scenarios’ and robust method’s results have been compared. Robust method has provided a production plan that has higher cost but, will result close to feasible and optimal for most of the different scenarios in the future.
Path-Constrained Motion Planning for Robotics Based on Kinematic Constraints
Dijk, van N.J.M.; Wouw, van de N.; Pancras, W.C.M.; Nijmeijer, H.
2007-01-01
Common robotic tracking tasks consist of motions along predefined paths. The design of time-optimal path-constrained trajectories for robotic applications is discussed in this paper. To increase industrial applicability, the proposed method accounts for robot kinematics together with actuator
On the complexity of container stowage planning problems
Tierney, Kevin; Pacino, Dario; Jensen, Rune Møller
2014-01-01
The optimization of container ship and depot operations embeds the kk-shift problem, in which containers must be stowed in stacks such that at most kk containers must be removed in order to reach containers below them. We first solve an open problem introduced by Avriel et al. (2000) by showing...... that changing from uncapacitated to capacitated stacks reduces the complexity of this problem from NP-complete to polynomial. We then examine the complexity of the current state-of-the-art abstraction of container ship stowage planning, wherein containers and slots are grouped together. To do this, we define...... the hatch overstow problem, in which a set of containers are placed on top of the hatches of a container ship such that the number of containers that are stowed on hatches that must be accessed is minimized. We show that this problem is NP-complete by a reduction from the set-covering problem, which means...
Trinh, Lan Anh; Ekström, Mikael; Cürüklü, Baran
2018-01-01
Recent industrial developments in autonomous systems, or agents, which assume that humans and the agents share the same space or even work in close proximity, open for new challenges in robotics, especially in motion planning and control. In these settings, the control system should be able to provide these agents a reliable path following control when they are working in a group or in collaboration with one or several humans in complex and dynamic environments. In such scenarios, these agents are not only moving to reach their goals, i.e., locations, they are also aware of the movements of other entities to find a collision-free path. Thus, this paper proposes a dependable, i.e., safe, reliable and effective, path planning algorithm for a group of agents that share their working space with humans. Firstly, the method employs the Theta * algorithm to initialize the paths from a starting point to a goal for a set of agents. As Theta * algorithm is computationally heavy, it only reruns when there is a significant change of the environment. To deal with the movements of the agents, a static flow field along the configured path is defined. This field is used by the agents to navigate and reach their goals even if the planned trajectories are changed. Secondly, a dipole field is calculated to avoid the collision of agents with other agents and human subjects. In this approach, each agent is assumed to be a source of a magnetic dipole field in which the magnetic moment is aligned with the moving direction of the agent. The magnetic dipole-dipole interactions between these agents generate repulsive forces to help them to avoid collision. The effectiveness of the proposed approach has been evaluated with extensive simulations. The results show that the static flow field is able to drive agents to the goals with a small number of requirements to update the path of agents. Meanwhile, the dipole flow field plays an important role to prevent collisions. The combination of
Lan Anh Trinh
2018-06-01
Full Text Available Recent industrial developments in autonomous systems, or agents, which assume that humans and the agents share the same space or even work in close proximity, open for new challenges in robotics, especially in motion planning and control. In these settings, the control system should be able to provide these agents a reliable path following control when they are working in a group or in collaboration with one or several humans in complex and dynamic environments. In such scenarios, these agents are not only moving to reach their goals, i.e., locations, they are also aware of the movements of other entities to find a collision-free path. Thus, this paper proposes a dependable, i.e., safe, reliable and effective, path planning algorithm for a group of agents that share their working space with humans. Firstly, the method employs the Theta* algorithm to initialize the paths from a starting point to a goal for a set of agents. As Theta* algorithm is computationally heavy, it only reruns when there is a significant change of the environment. To deal with the movements of the agents, a static flow field along the configured path is defined. This field is used by the agents to navigate and reach their goals even if the planned trajectories are changed. Secondly, a dipole field is calculated to avoid the collision of agents with other agents and human subjects. In this approach, each agent is assumed to be a source of a magnetic dipole field in which the magnetic moment is aligned with the moving direction of the agent. The magnetic dipole-dipole interactions between these agents generate repulsive forces to help them to avoid collision. The effectiveness of the proposed approach has been evaluated with extensive simulations. The results show that the static flow field is able to drive agents to the goals with a small number of requirements to update the path of agents. Meanwhile, the dipole flow field plays an important role to prevent collisions. The
The Problems And Prospects Of Family Planning Services In The ...
The focus of this research was to study the problems and prospects of family planning services in the University of Calabar Teaching Hospital, Calabar. The Levels of poverty, income and health education of the clients were studied. The main source of data and information was a structured questionnaire. A sample of 200 ...
Kun-Lin Wu
2016-01-01
Full Text Available In this paper, mobile robot navigation on a 3D terrain with a single obstacle is addressed. The terrain is modelled as a smooth, complete manifold with well-defined tangent planes and the hazardous region is modelled as an enclosing circle with a hazard grade tuned radius representing the obstacle projected onto the terrain to allow efficient path-obstacle intersection checking. To resolve the intersections along the initial geodesic, by resorting to the geodesic ideas from differential geometry on surfaces and manifolds, we present a geodesic-based planning and replanning algorithm as a new method for obstacle avoidance on a 3D terrain without using boundary following on the obstacle surface. The replanning algorithm generates two new paths, each a composition of two geodesics, connected via critical points whose locations are found to be heavily relying on the exploration of the terrain via directional scanning on the tangent plane at the first intersection point of the initial geodesic with the circle. An advantage of this geodesic path replanning procedure is that traversability of terrain on which the detour path traverses could be explored based on the local Gauss-Bonnet Theorem of the geodesic triangle at the planning stage. A simulation demonstrates the practicality of the analytical geodesic replanning procedure for navigating a constant speed point robot on a 3D hill-like terrain.
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.
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.
Minimization In Digital Design As A Meta-Planning Problem
Ho, William P. C.; Wu, Jung-Gen
1987-05-01
In our model-based expert system for automatic digital system design, we formalize the design process into three sub-processes - compiling high-level behavioral specifications into primitive behavioral operations, grouping primitive operations into behavioral functions, and grouping functions into modules. Consideration of design minimization explicitly controls decision-making in the last two subprocesses. Design minimization, a key task in the automatic design of digital systems, is complicated by the high degree of interaction among the time sequence and content of design decisions. In this paper, we present an AI approach which directly addresses these interactions and their consequences by modeling the minimization prob-lem as a planning problem, and the management of design decision-making as a meta-planning problem.
Municipal Level of Strategic Planning: Economic and Legal Problems
Evgeniy Moiseevich Bukhvald
2016-12-01
Full Text Available The article focuses on the need of integration of municipal government into a unified hierarchy of strategic planning in the country. The basic positions of the acting version of the Federal law no.131 “On general principles of organization of local self-government” and the Federal law no. 172 “On strategic planning” don’t provide clear legal framework for the solution of this problem. Besides, the practical integration of municipal management into a unified hierarchy of strategic planning meets serious economic obstacles, the main of which consist in the negative situation within the system of local finance, characterized by trends of deficiency, high dependence on subsidies and, as a consequence, volatility and lack of predictability in relation to any plans and programs of long-term nature. The main idea of the article is to prove the need for a systemic approach to solving tasks, related to the integration of municipal management in a unified vertical of strategic planning in the country. The essence of this approach is the combination of a number of legal innovations in the legislation on strategic planning and local government with a set of measures, aimed to strengthen the fiscal basis of Russian local self-government together with institutional ensuring of municipal planning and its interaction with the practice of strategic planning at the level of subjects of the Russian Federation.
Petruseva Silvana
2006-01-01
Full Text Available This paper discusses the comparison of the efficiency of two algorithms, by estimation of their complexity. For solving the problem, the Neural Network Crossbar Adaptive Array (NN-CAA is used as the agent architecture, implementing a model of an emotion. The problem discussed is how to find the shortest path in an environment with n states. The domains concerned are environments with n states, one of which is the starting state, one is the goal state, and some states are undesirable and they should be avoided. It is obtained that finding one path (one solution is efficient, i.e. in polynomial time by both algorithms. One of the algorithms is faster than the other only in the multiplicative constant, and it shows a step forward toward the optimality of the learning process. However, finding the optimal solution (the shortest path by both algorithms is in exponential time which is asserted by two theorems. It might be concluded that the concept of subgoal is one step forward toward the optimality of the process of the agent learning. Yet, it should be explored further on, in order to obtain an efficient, polynomial algorithm.
A. M. Rawani
2002-01-01
Full Text Available This paper presents a path analytic model showing the cause and effect relationships among various Information Systems (IS planning variables for the banking sector in India. In recent years, there has been an increased awareness among banks of the potential of Information Technology (IT and the use of information systems. Strategic information system planning (SISP becomes an important issue in the use of IS strategically. In India, banks have now started realizing the importance of SISP. In this study, 11 IS planning variables for the banking sector in India are examined and the influence of one over the other is investigated using path analysis. Data for the study are collected from 52 banks operating in India. The results of the study indicate that top management involvement in IS planning greatly influences the whole planning exercise. Moreover, top management involvement is higher when they foresee greater future impact of IS. The study also highlights the need and importance of user training in the banking sector. Change in the focus and orientation of user-training will make the users competent to conceive with innovative IS applications.
A model for solving the prescribed burn planning problem.
Rachmawati, Ramya; Ozlen, Melih; Reinke, Karin J; Hearne, John W
2015-01-01
The increasing frequency of destructive wildfires, with a consequent loss of life and property, has led to fire and land management agencies initiating extensive fuel management programs. This involves long-term planning of fuel reduction activities such as prescribed burning or mechanical clearing. In this paper, we propose a mixed integer programming (MIP) model that determines when and where fuel reduction activities should take place. The model takes into account multiple vegetation types in the landscape, their tolerance to frequency of fire events, and keeps track of the age of each vegetation class in each treatment unit. The objective is to minimise fuel load over the planning horizon. The complexity of scheduling fuel reduction activities has led to the introduction of sophisticated mathematical optimisation methods. While these approaches can provide optimum solutions, they can be computationally expensive, particularly for fuel management planning which extends across the landscape and spans long term planning horizons. This raises the question of how much better do exact modelling approaches compare to simpler heuristic approaches in their solutions. To answer this question, the proposed model is run using an exact MIP (using commercial MIP solver) and two heuristic approaches that decompose the problem into multiple single-period sub problems. The Knapsack Problem (KP), which is the first heuristic approach, solves the single period problems, using an exact MIP approach. The second heuristic approach solves the single period sub problem using a greedy heuristic approach. The three methods are compared in term of model tractability, computational time and the objective values. The model was tested using randomised data from 711 treatment units in the Barwon-Otway district of Victoria, Australia. Solutions for the exact MIP could be obtained for up to a 15-year planning only using a standard implementation of CPLEX. Both heuristic approaches can solve
A focussed dynamic path finding algorithm with constraints
Leenen, L
2013-11-01
Full Text Available heuristic to focus the search for an optimal path. Existing approaches to solving path planning problems tend to combine path costs with various other criteria such as obstacle avoidance in the objective function which is being optimised. The authors...
Energy Optimal Path Planning: Integrating Coastal Ocean Modelling with Optimal Control
Subramani, D. N.; Haley, P. J., Jr.; Lermusiaux, P. F. J.
2016-02-01
A stochastic optimization methodology is formulated for computing energy-optimal paths from among time-optimal paths of autonomous vehicles navigating in a dynamic flow field. To set up the energy optimization, the relative vehicle speed and headings are considered to be stochastic, and new stochastic Dynamically Orthogonal (DO) level-set equations that govern their stochastic time-optimal reachability fronts are derived. Their solution provides the distribution of time-optimal reachability fronts and corresponding distribution of time-optimal paths. An optimization is then performed on the vehicle's energy-time joint distribution to select the energy-optimal paths for each arrival time, among all stochastic time-optimal paths for that arrival time. The accuracy and efficiency of the DO level-set equations for solving the governing stochastic level-set reachability fronts are quantitatively assessed, including comparisons with independent semi-analytical solutions. Energy-optimal missions are studied in wind-driven barotropic quasi-geostrophic double-gyre circulations, and in realistic data-assimilative re-analyses of multiscale coastal ocean flows. The latter re-analyses are obtained from multi-resolution 2-way nested primitive-equation simulations of tidal-to-mesoscale dynamics in the Middle Atlantic Bight and Shelbreak Front region. The effects of tidal currents, strong wind events, coastal jets, and shelfbreak fronts on the energy-optimal paths are illustrated and quantified. Results showcase the opportunities for longer-duration missions that intelligently utilize the ocean environment to save energy, rigorously integrating ocean forecasting with optimal control of autonomous vehicles.
Moharam Habibnejad Korayem
2012-10-01
Full Text Available In this work, a computational algorithm is developed for the smooth-jerk optimal path planning of tricycle wheeled mobile manipulators in an obstructed environment. Due to a centred orientable wheel, the tricycle mobile manipulator exhibits more steerability and manoeuvrability over traditional mobile manipulators, especially in the presence of environmental obstacles. This paper presents a general formulation based on the combination of the potential field method and optimal control theory in order to plan the smooth point-to-point path of the tricycle mobile manipulators. The nonholonomic constraints of the tricycle mobile base are taken into account in the dynamic formulation of the system and then the optimality conditions are derived considering jerk restrictions and obstacle avoidance. Furthermore, by means of the potential field method, a new formulation of a repulsive potential function is proposed for collision avoidance between any obstacle and each part of the mobile manipulator. In addition, to ensure the accurate placement of the end effector on the target point an attractive potential function is applied to the optimal control formulation. Next, a mixed analytical-numerical algorithm is proposed to generate the point-to-point optimal path. Finally, the proposed method is verified by a number of simulations on a two-link tricycle manipulator.
RSMDP-based Robust Q-learning for Optimal Path Planning in a Dynamic Environment
Yunfei Zhang
2014-07-01
Full Text Available This paper presents arobust Q-learning method for path planningin a dynamic environment. The method consists of three steps: first, a regime-switching Markov decision process (RSMDP is formed to present the dynamic environment; second a probabilistic roadmap (PRM is constructed, integrated with the RSMDP and stored as a graph whose nodes correspond to a collision-free world state for the robot; and third, an onlineQ-learning method with dynamic stepsize, which facilitates robust convergence of the Q-value iteration, is integrated with the PRM to determine an optimal path for reaching the goal. In this manner, the robot is able to use past experience for improving its performance in avoiding not only static obstacles but also moving obstacles, without knowing the nature of the obstacle motion. The use ofregime switching in the avoidance of obstacles with unknown motion is particularly innovative. The developed approach is applied to a homecare robot in computer simulation. The results show that the online path planner with Q-learning is able torapidly and successfully converge to the correct path.
Critical path method applied to research project planning: Fire Economics Evaluation System (FEES)
Earl B. Anderson; R. Stanton Hales
1986-01-01
The critical path method (CPM) of network analysis (a) depicts precedence among the many activities in a project by a network diagram; (b) identifies critical activities by calculating their starting, finishing, and float times; and (c) displays possible schedules by constructing time charts. CPM was applied to the development of the Forest Service's Fire...
Multi Robot Path Planning for Budgeted Active Perception with Self-Organising Maps
2016-10-04
5], [6], [7], but the formulations have been limited to restricted cases, such as a single object or a constrained action space. Little attention has...solution paths. Object parts are shown in the coloured point clouds. Viewpoint regions are coloured black (low reward), orange (medium) and yellow (high
Spreading paths in partially observed social networks
Onnela, Jukka-Pekka; Christakis, Nicholas A.
2012-03-01
Understanding how and how far information, behaviors, or pathogens spread in social networks is an important problem, having implications for both predicting the size of epidemics, as well as for planning effective interventions. There are, however, two main challenges for inferring spreading paths in real-world networks. One is the practical difficulty of observing a dynamic process on a network, and the other is the typical constraint of only partially observing a network. Using static, structurally realistic social networks as platforms for simulations, we juxtapose three distinct paths: (1) the stochastic path taken by a simulated spreading process from source to target; (2) the topologically shortest path in the fully observed network, and hence the single most likely stochastic path, between the two nodes; and (3) the topologically shortest path in a partially observed network. In a sampled network, how closely does the partially observed shortest path (3) emulate the unobserved spreading path (1)? Although partial observation inflates the length of the shortest path, the stochastic nature of the spreading process also frequently derails the dynamic path from the shortest path. We find that the partially observed shortest path does not necessarily give an inflated estimate of the length of the process path; in fact, partial observation may, counterintuitively, make the path seem shorter than it actually is.
Spreading paths in partially observed social networks.
Onnela, Jukka-Pekka; Christakis, Nicholas A
2012-03-01
Understanding how and how far information, behaviors, or pathogens spread in social networks is an important problem, having implications for both predicting the size of epidemics, as well as for planning effective interventions. There are, however, two main challenges for inferring spreading paths in real-world networks. One is the practical difficulty of observing a dynamic process on a network, and the other is the typical constraint of only partially observing a network. Using static, structurally realistic social networks as platforms for simulations, we juxtapose three distinct paths: (1) the stochastic path taken by a simulated spreading process from source to target; (2) the topologically shortest path in the fully observed network, and hence the single most likely stochastic path, between the two nodes; and (3) the topologically shortest path in a partially observed network. In a sampled network, how closely does the partially observed shortest path (3) emulate the unobserved spreading path (1)? Although partial observation inflates the length of the shortest path, the stochastic nature of the spreading process also frequently derails the dynamic path from the shortest path. We find that the partially observed shortest path does not necessarily give an inflated estimate of the length of the process path; in fact, partial observation may, counterintuitively, make the path seem shorter than it actually is.
Is EIA part of the wind power planning problem?
Smart, Duncan Ewan; Stojanovic, Timothy A., E-mail: tas21@st-andrews.ac.uk; Warren, Charles R.
2014-11-15
This research evaluates the importance and effectiveness of Environmental Impact Assessment (EIA) within wind farm planning debates, drawing on insights from case studies in Scotland. Despite general public support for renewable energy on the grounds that it is needed to tackle climate change and implement sustainable development, many proposed wind farms encounter significant resistance. The importance of planning issues and (EIA) processes has arguably been overlooked within recent wind farm social acceptability discourse. Through semi-structured interviews with key stakeholders and textual analysis of EIA documents, the characteristics of EIA are assessed in terms of its perceived purpose and performance. The data show that whilst respondents perceive EIA to be important, they express concerns about bias and about the inability of EIA to address climate change and wind farm decommissioning issues adequately. Furthermore, the research identifies key issues which impede the effectiveness of EIA, and reveals differences between theoretical and practical framings of EIA. The paper questions the assumption that EIA is a universally applicable tool, and argues that its effectiveness should be analysed in the context of specific development sectors. The article concludes by reviewing whether the recently amended EIA Directive (2014/52/EU) could resolve identified problems within national EIA practice. - Highlights: • Evaluation of EIA for onshore wind farm planning in Scotland. • EIA is important for multiple aspects of onshore wind farm planning. • Multiple substantive deficiencies of relevance to wind farm planning exist in EIA. • Further research into EIA effectiveness for specific development types is required. • Directive 2014/52/EU may improve EIA effectiveness within wind farm planning.
Is EIA part of the wind power planning problem?
Smart, Duncan Ewan; Stojanovic, Timothy A.; Warren, Charles R.
2014-01-01
This research evaluates the importance and effectiveness of Environmental Impact Assessment (EIA) within wind farm planning debates, drawing on insights from case studies in Scotland. Despite general public support for renewable energy on the grounds that it is needed to tackle climate change and implement sustainable development, many proposed wind farms encounter significant resistance. The importance of planning issues and (EIA) processes has arguably been overlooked within recent wind farm social acceptability discourse. Through semi-structured interviews with key stakeholders and textual analysis of EIA documents, the characteristics of EIA are assessed in terms of its perceived purpose and performance. The data show that whilst respondents perceive EIA to be important, they express concerns about bias and about the inability of EIA to address climate change and wind farm decommissioning issues adequately. Furthermore, the research identifies key issues which impede the effectiveness of EIA, and reveals differences between theoretical and practical framings of EIA. The paper questions the assumption that EIA is a universally applicable tool, and argues that its effectiveness should be analysed in the context of specific development sectors. The article concludes by reviewing whether the recently amended EIA Directive (2014/52/EU) could resolve identified problems within national EIA practice. - Highlights: • Evaluation of EIA for onshore wind farm planning in Scotland. • EIA is important for multiple aspects of onshore wind farm planning. • Multiple substantive deficiencies of relevance to wind farm planning exist in EIA. • Further research into EIA effectiveness for specific development types is required. • Directive 2014/52/EU may improve EIA effectiveness within wind farm planning
Critical path method as the criterion for optimization of business planning process
Butsenko Elena V.
2016-01-01
In today's economy the task of improving business planning is considered a necessary component of any enterprise management process and is precisely the solution drawn from that task which determines the financial policy and economic structure. The development of technologies based on the optimization of business planning is a very urgent scientific challenge. In this paper we propose to use the methods of network planning and management as a tool for economic and mathematical modeling to...
Vatutin Eduard
2017-12-01
Full Text Available The article deals with the problem of analysis of effectiveness of the heuristic methods with limited depth-first search techniques of decision obtaining in the test problem of getting the shortest path in graph. The article briefly describes the group of methods based on the limit of branches number of the combinatorial search tree and limit of analyzed subtree depth used to solve the problem. The methodology of comparing experimental data for the estimation of the quality of solutions based on the performing of computational experiments with samples of graphs with pseudo-random structure and selected vertices and arcs number using the BOINC platform is considered. It also shows description of obtained experimental results which allow to identify the areas of the preferable usage of selected subset of heuristic methods depending on the size of the problem and power of constraints. It is shown that the considered pair of methods is ineffective in the selected problem and significantly inferior to the quality of solutions that are provided by ant colony optimization method and its modification with combinatorial returns.
Vatutin, Eduard
2017-12-01
The article deals with the problem of analysis of effectiveness of the heuristic methods with limited depth-first search techniques of decision obtaining in the test problem of getting the shortest path in graph. The article briefly describes the group of methods based on the limit of branches number of the combinatorial search tree and limit of analyzed subtree depth used to solve the problem. The methodology of comparing experimental data for the estimation of the quality of solutions based on the performing of computational experiments with samples of graphs with pseudo-random structure and selected vertices and arcs number using the BOINC platform is considered. It also shows description of obtained experimental results which allow to identify the areas of the preferable usage of selected subset of heuristic methods depending on the size of the problem and power of constraints. It is shown that the considered pair of methods is ineffective in the selected problem and significantly inferior to the quality of solutions that are provided by ant colony optimization method and its modification with combinatorial returns.
INFORMATION FINANCIAL PROBLEMS REFLECTION OF THE PLANNING OF HUMAN RESOURCES
O. S. Protsenko
2015-05-01
Full Text Available Two ways to indentify sources of funding for workforce planning of health care provided limited funds. Emphasized that investment in education is a source of economic growth. Clear boundaries between investment in public education (receiving general education and private investment (vocational training does not exist. A possi ble solution to the problem of harmonization of investment policies can be informatization training system that misses factors industry research, motivation, training difficulties, financial calculations.
Status Problem and Expectations of Competence: A Challenging Path for Teachers
Pescarmona, Isabella
2015-01-01
Complex Instruction (CI) is a cooperative learning approach, which aims at improving the equal status interaction among students working in groups who may be at different academic and social levels. Based on an ethnographic research, the article examines how a group of Italian primary school teachers understand the status problem and how the…
Constraint-based solver for the Military unit path finding problem
Leenen, L
2010-04-01
Full Text Available -based approach because it requires flexibility in modelling. The authors formulate the MUPFP as a constraint satisfaction problem and a constraint-based extension of the search algorithm. The concept demonstrator uses a provided map, for example taken from Google...
A biomimetic, energy-harvesting, obstacle-avoiding, path-planning algorithm for UAVs
Gudmundsson, Snorri
This dissertation presents two new approaches to energy harvesting for Unmanned Aerial Vehicles (UAV). One method is based on the Potential Flow Method (PFM); the other method seeds a wind-field map based on updraft peak analysis and then applies a variant of the Bellman-Ford algorithm to find the minimum-cost path. Both methods are enhanced by taking into account the performance characteristics of the aircraft using advanced performance theory. The combined approach yields five possible trajectories from which the one with the minimum energy cost is selected. The dissertation concludes by using the developed theory and modeling tools to simulate the flight paths of two small Unmanned Aerial Vehicles (sUAV) in the 500 kg and 250 kg class. The results show that, in mountainous regions, substantial energy can be recovered, depending on topography and wind characteristics. For the examples presented, as much as 50% of the energy was recovered for a complex, multi-heading, multi-altitude, 170 km mission in an average wind speed of 9 m/s. The algorithms constitute a Generic Intelligent Control Algorithm (GICA) for autonomous unmanned aerial vehicles that enables an extraction of atmospheric energy while completing a mission trajectory. At the same time, the algorithm. automatically adjusts the flight path in order to avoid obstacles, in a fashion not unlike what one would expect from living organisms, such as birds and insects. This multi-disciplinary approach renders the approach biomimetic, i.e. it constitutes a synthetic system that “mimics the formation and function of biological mechanisms and processes.”.
Risk-Aware Planetary Rover Operation: Autonomous Terrain Classification and Path Planning
Ono, Masahiro; Fuchs, Thoams J.; Steffy, Amanda; Maimone, Mark; Yen, Jeng
2015-01-01
Identifying and avoiding terrain hazards (e.g., soft soil and pointy embedded rocks) are crucial for the safety of planetary rovers. This paper presents a newly developed groundbased Mars rover operation tool that mitigates risks from terrain by automatically identifying hazards on the terrain, evaluating their risks, and suggesting operators safe paths options that avoids potential risks while achieving specified goals. The tool will bring benefits to rover operations by reducing operation cost, by reducing cognitive load of rover operators, by preventing human errors, and most importantly, by significantly reducing the risk of the loss of rovers.
2012-09-13
46, 1989. [75] S. Melkote and M.S. Daskin . An integrated model of facility location and transportation network design. Transportation Research Part A ... a work of the U.S. Government and is not subject to copyright protection in the United States. AFIT/DS/ENS/12-09 THE AVERAGE NETWORK FLOW PROBLEM...focused thinking (VFT) are used sparingly, as is the case across the entirety of the supply chain literature. We provide a VFT tutorial for supply chain
Optimal Control Approaches to the Aggregate Production Planning Problem
Yasser A. Davizón
2015-12-01
Full Text Available In the area of production planning and control, the aggregate production planning (APP problem represents a great challenge for decision makers in production-inventory systems. Tradeoff between inventory-capacity is known as the APP problem. To address it, static and dynamic models have been proposed, which in general have several shortcomings. It is the premise of this paper that the main drawback of these proposals is, that they do not take into account the dynamic nature of the APP. For this reason, we propose the use of an Optimal Control (OC formulation via the approach of energy-based and Hamiltonian-present value. The main contribution of this paper is the mathematical model which integrates a second order dynamical system coupled with a first order system, incorporating production rate, inventory level, and capacity as well with the associated cost by work force in the same formulation. Also, a novel result in relation with the Hamiltonian-present value in the OC formulation is that it reduces the inventory level compared with the pure energy based approach for APP. A set of simulations are provided which verifies the theoretical contribution of this work.
Resing, Wilma C M; Bakker, Merel; Pronk, Christine M E; Elliott, Julian G
2017-01-01
The current study investigated developmental trajectories of analogical reasoning performance of 104 7- and 8-year-old children. We employed a microgenetic research method and multilevel analysis to examine the influence of several background variables and experimental treatment on the children's developmental trajectories. Our participants were divided into two treatment groups: repeated practice alone and repeated practice with training. Each child received an initial working memory assessment and was subsequently asked to solve figural analogies on each of several sessions. We examined children's analogical problem-solving behavior and their subsequent verbal accounts of their employed solving processes. We also investigated the influence of verbal and visual-spatial working memory capacity and initial variability in strategy use on analogical reasoning development. Results indicated that children in both treatment groups improved but that gains were greater for those who had received training. Training also reduced the influence of children's initial variability in the use of analogical strategies with the degree of improvement in reasoning largely unrelated to working memory capacity. Findings from this study demonstrate the value of a microgenetic research method and the use of multilevel analysis to examine inter- and intra-individual change in problem-solving processes. Copyright © 2016 Elsevier Inc. All rights reserved.
Multiple Choice Knapsack Problem: example of planning choice in transportation.
Zhong, Tao; Young, Rhonda
2010-05-01
Transportation programming, a process of selecting projects for funding given budget and other constraints, is becoming more complex as a result of new federal laws, local planning regulations, and increased public involvement. This article describes the use of an integer programming tool, Multiple Choice Knapsack Problem (MCKP), to provide optimal solutions to transportation programming problems in cases where alternative versions of projects are under consideration. In this paper, optimization methods for use in the transportation programming process are compared and then the process of building and solving the optimization problems is discussed. The concepts about the use of MCKP are presented and a real-world transportation programming example at various budget levels is provided. This article illustrates how the use of MCKP addresses the modern complexities and provides timely solutions in transportation programming practice. While the article uses transportation programming as a case study, MCKP can be useful in other fields where a similar decision among a subset of the alternatives is required. Copyright 2009 Elsevier Ltd. All rights reserved.
Multi-scale path planning for reduced environmental impact of aviation
Campbell, Scot Edward
A future air traffic management system capable of rerouting aircraft trajectories in real-time in response to transient and evolving events would result in increased aircraft efficiency, better utilization of the airspace, and decreased environmental impact. Mixed-integer linear programming (MILP) is used within a receding horizon framework to form aircraft trajectories which mitigate persistent contrail formation, avoid areas of convective weather, and seek a minimum fuel solution. Areas conducive to persistent contrail formation and areas of convective weather occur at disparate temporal and spatial scales, and thereby require the receding horizon controller to be adaptable to multi-scale events. In response, a novel adaptable receding horizon controller was developed to account for multi-scale disturbances, as well as generate trajectories using both a penalty function approach for obstacle penetration and hard obstacle avoidance constraints. A realistic aircraft fuel burn model based on aircraft data and engine performance simulations is used to form the cost function in the MILP optimization. The performance of the receding horizon algorithm is tested through simulation. A scalability analysis of the algorithm is conducted to ensure the tractability of the path planner. The adaptable receding horizon algorithm is shown to successfully negotiate multi-scale environments with performance exceeding static receding horizon solutions. The path planner is applied to realistic scenarios involving real atmospheric data. A single flight example for persistent contrail mitigation shows that fuel burn increases 1.48% when approximately 50% of persistent contrails are avoided, but 6.19% when 100% of persistent contrails are avoided. Persistent contrail mitigating trajectories are generated for multiple days of data, and the research shows that 58% of persistent contrails are avoided with a 0.48% increase in fuel consumption when averaged over a year.
From Parent to Child to Parent…: Paths In and Out of Problem Behavior
Bradley, Robert H.; Corwyn, Robert
2014-01-01
This study used data from the NICHD Study of Early Child Care and Youth Development to examine relations between parenting, self-control and externalizing behavior from early childhood to mid-adolescence (N=956; 49.9% male). Results indicated that maternal sensitivity, parental harshness and productive activity are related to externalizing problems but that patterns of relations change from early childhood to middle childhood to adolescence, with evidence suggesting that externalizing behavior influences parenting more than the reverse from middle childhood onward. Self-control measured during early adolescence partially mediated relations between maternal sensitivity and adolescent-reported externalizing behavior. Parental monitoring during adolescence was also related to externalizing behavior at age 15. Monitoring partially mediated the relation between externalizing behavior in early adolescence and externalizing at age 15. PMID:23135289
Divertors for Helical Devices: Concepts, Plans, Results, and Problems
Koenig, R.; Grigull, P.; McCormick, K.
2004-01-01
With Large Helical Device (LHD) and Wendelstein 7-X (W7-X), the development of helical devices is now taking a large step forward on the path to a steady-state fusion reactor. Important issues that need to be settled in these machines are particle flux and heat control and the impact of divertors on plasma performance in future continuously burning fusion plasmas. The divertor concepts that will initially be explored in these large machines were prepared in smaller-scale devices like Heliotron E, Compact Helical System (CHS), and Wendelstein 7-AS (W7-AS). While advanced divertor scenarios relevant for W7-X were already studied in W7-AS, other smaller-scale experiments like Heliotron-J, CHS, and National Compact Stellarator Experiment will be used for the further development of divertor concepts. The two divertor configurations that are being investigated are the helical and the island divertor, as well as the local island divertor, which was successfully demonstrated on CHS and just went into operation on LHD. At present, on its route to a fully closed helical divertor, LHD operates in an open helical divertor configuration. W7-X will be equipped right from the start with an actively cooled discrete island divertor that will allow quasi-continuous operation. The divertor design is very similar to the one explored on W7-AS. For sufficiently large island sizes and not too long field line connection lengths, this divertor gives access to a partially detached quasi-steady-state operating scenario in a newly found high-density H-mode operating regime, which benefits from high energy and low impurity confinement times, with edge radiation levels of up to 90% and sufficient neutral compression in the subdivertor region (>10) for active pumping. The basic physics of the different divertor concepts and associated implementation problems, like asymmetries due to drifts, accessibility of essential operating scenarios, toroidal asymmetries due to symmetry breaking error fields
Divertors for helical devices: Concepts, plans, results and problems
Koenig, R.; Grigull, P.; McCormick, K.
2003-01-01
With LHD and W7-X stellarator development is now taking a large leap forward on the path to a steady-state fusion reactor. Important issues that need to be settled in these machines are particle flux and heat control, and the impact of divertors on plasma performance in future continuously burning fusion plasmas. The divertor concepts that will initially be explored in these large stellarators were carefully prepared in smaller scale devices like Heliotron E, CHS and W7-AS. While advanced divertor scenarios relevant for W7-X were already studied in W7-AS, other smaller scale experiments like Heliotron-J, CHS and NCSX will be used for the further development of divertor concepts. The two divertor configurations that are presently being investigated, are the helical and the island divertor, as well as the local island divertor (LID), which was successfully demonstrated on CHS and just went into operation on LHD. Presently, on its route to a fully closed helical divertor, LHD operates in an open helical divertor configuration. W7-X will be equipped right from the start with an actively cooled discrete island divertor which will allow quasi continuous operation. The divertor design is very similar to the one explored on W7-AS. For sufficiently large island sizes and not too long field line connection lengths, this divertor gives access to a partially detached quasi steady-state operating scenario in a newly found high density H-mode operating regime, which benefits from high energy and extremely low impurity confinement times, with edge radiation levels of up to 90 % and sufficient neutral compression in the subdivertor region (> 10) for active pumping. The basic physics of the different divertor concepts and associated implementation problems, like asymmetries due to drifts, accessibility of essential operating scenarios and toroidal asymmetries due to symmetry breaking error fields, etc. will be discussed. (orig.)
Planning Nurses in Maternity Care: a Stochastic Assignment Problem
Phillipson, Frank
2015-01-01
With 23 percent of all births taking place at home, The Netherlands have the highest rate of home births in the world. Also if the birth did not take place at home, it is not unusual for the mother and child to be out of hospital in a few hours after the baby was born. The explanation for both is the very well organised maternity care system. However, getting the right maternity care nurse available on time introduces a complex planning issue that can be recognized as a Stochastic Assignment Problem. In this paper an expert rule based approach is combined with scenario analysis to support the planner of the maternity care agency in his work. (paper)
Planning Nurses in Maternity Care: a Stochastic Assignment Problem
Phillipson, Frank
2015-05-01
With 23 percent of all births taking place at home, The Netherlands have the highest rate of home births in the world. Also if the birth did not take place at home, it is not unusual for the mother and child to be out of hospital in a few hours after the baby was born. The explanation for both is the very well organised maternity care system. However, getting the right maternity care nurse available on time introduces a complex planning issue that can be recognized as a Stochastic Assignment Problem. In this paper an expert rule based approach is combined with scenario analysis to support the planner of the maternity care agency in his work.
Güler, Fatma; Kasap, Emin
Using the curvature theory for the ruled surfaces a technique for robot trajectory planning is presented. This technique ensures the calculation of robot’s next path. The positional variation of the Tool Center Point (TCP), linear velocity, angular velocity are required in the work area of the robot. In some circumstances, it may not be physically achievable and a re-computation of the robot trajectory might be necessary. This technique is suitable for re-computation of the robot trajectory. We obtain different robot trajectories which change depending on the darboux angle function and define trajectory ruled surface family with a common trajectory curve with the rotation trihedron. Also, the motion of robot end effector is illustrated with examples.
Wood, Nathan J.; Jones, Jeanne M.; Schmidtlein, Mathew; Schelling, John; Frazier, T.
2016-01-01
Successful evacuations are critical to saving lives from future tsunamis. Pedestrian-evacuation modeling related to tsunami hazards primarily has focused on identifying areas and the number of people in these areas where successful evacuations are unlikely. Less attention has been paid to identifying evacuation pathways and population demand at assembly areas for at-risk individuals that may have sufficient time to evacuate. We use the neighboring coastal communities of Hoquiam, Aberdeen, and Cosmopolis (Washington, USA) and the local tsunami threat posed by Cascadia subduction zone earthquakes as a case study to explore the use of geospatial, least-cost-distance evacuation modeling for supporting evacuation outreach, response, and relief planning. We demonstrate an approach that uses geospatial evacuation modeling to (a) map the minimum pedestrian travel speeds to safety, the most efficient paths, and collective evacuation basins, (b) estimate the total number and demographic description of evacuees at predetermined assembly areas, and (c) determine which paths may be compromised due to earthquake-induced ground failure. Results suggest a wide range in the magnitude and type of evacuees at predetermined assembly areas and highlight parts of the communities with no readily accessible assembly area. Earthquake-induced ground failures could obstruct access to some assembly areas, cause evacuees to reroute to get to other assembly areas, and isolate some evacuees from relief personnel. Evacuation-modeling methods and results discussed here have implications and application to tsunami-evacuation outreach, training, response procedures, mitigation, and long-term land use planning to increase community resilience.
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.
Trtanj, J.; Balbus, J. M.; Brown, C.; Shimamoto, M. M.
2017-12-01
The transmission and spread of infectious diseases, especially vector-borne diseases, water-borne diseases and zoonosis, are influenced by short and long-term climate factors, in conjunction with numerous other drivers. Public health interventions, including vaccination, vector control programs, and outreach campaigns could be made more effective if the geographic range and timing of increased disease risk could be more accurately targeted, and high risk areas and populations identified. While some progress has been made in predictive modeling for transmission of these diseases using climate and weather data as inputs, they often still start after the first case appears, the skill of those models remains limited, and their use by public health officials infrequent. And further, predictions with lead times of weeks, months or seasons are even rarer, yet the value of acting early holds the potential to save more lives, reduce cost and enhance both economic and national security. Information on high-risk populations and areas for infectious diseases is also potentially useful for the federal defense and intelligence communities as well. The US Global Change Research Program, through its Interagency Group on Climate Change and Human Health (CCHHG), has put together a science plan that pulls together federal scientists and programs working on predictive modeling of climate-sensitive diseases, and draws on academic and other partners. Through a series of webinars and an in-person workshop, the CCHHG has convened key federal and academic stakeholders to assess the current state of science and develop an integrated science plan to identify data and observation systems needs as well as a targeted research agenda for enhancing predictive modeling. This presentation will summarize the findings from this effort and engage AGU members on plans and next steps to improve predictive modeling for infectious diseases.
On some problems concerning the national emergency planning
Angelov, V.; Bonchev, Ts.; Semova, T.; Georgiev, V.
1995-01-01
The basic principles of national emergency planning and preparedness in case of severe nuclear accident are discussed. Recommendations concerning the participating authorities in Bulgaria and their cooperation are given. The need to synchronize the plan with the NPP Kozloduy emergency plan is pointed out. The introduction of new legislation outlining the necessity of national emergency planning is stressed. 13 refs
On some problems concerning the national emergency planning
Angelov, V [Civil Defence Administration, Sofia (Bulgaria); Bonchev, Ts [Sofia Univ. (Bulgaria). Fizicheski Fakultet; Andonov, S [Civil Defence Administration, Sofia (Bulgaria); Semova, T [Sofia Univ. (Bulgaria). Fizicheski Fakultet; Ganchev, N [Committee on the Use of Atomic Energy for Peaceful Purposes, Sofia (Bulgaria); Georgiev, V [Energoproekt, Sofia (Bulgaria)
1996-12-31
The basic principles of national emergency planning and preparedness in case of severe nuclear accident are discussed. Recommendations concerning the participating authorities in Bulgaria and their cooperation are given. The need to synchronize the plan with the NPP Kozloduy emergency plan is pointed out. The introduction of new legislation outlining the necessity of national emergency planning is stressed. 13 refs.
Optimal Path Planning and Control of Quadrotor Unmanned Aerial Vehicle for Area Coverage
Fan, Jiankun
An Unmanned Aerial Vehicle (UAV) is an aircraft without a human pilot on board. Its flight is controlled either autonomously by computers onboard the vehicle, or remotely by a pilot on the ground, or by another vehicle. In recent years, UAVs have been used more commonly than prior years. The example includes areo-camera where a high speed camera was attached to a UAV which can be used as an airborne camera to obtain aerial video. It also could be used for detecting events on ground for tasks such as surveillance and monitoring which is a common task during wars. Similarly UAVs can be used for relaying communication signal during scenarios when regular communication infrastructure is destroyed. The objective of this thesis is motivated from such civilian operations such as search and rescue or wildfire detection and monitoring. One scenario is that of search and rescue where UAV's objective is to geo-locate a person in a given area. The task is carried out with the help of a camera whose live feed is provided to search and rescue personnel. For this objective, the UAV needs to carry out scanning of the entire area in the shortest time. The aim of this thesis to develop algorithms to enable a UAV to scan an area in optimal time, a problem referred to as "Coverage Control" in literature. The thesis focuses on a special kind of UAVs called "quadrotor" that is propelled with the help of four rotors. The overall objective of this thesis is achieved via solving two problems. The first problem is to develop a dynamic control model of quadrtor. In this thesis, a proportional-integral-derivative controller (PID) based feedback control system is developed and implemented on MATLAB's Simulink. The PID controller helps track any given trajectory. The second problem is to design a trajectory that will fulfill the mission. The planed trajectory should make sure the quadrotor will scan the whole area without missing any part to make sure that the quadrotor will find the lost
Hameed, Ibrahim; la Cour-Harbo, Anders; Osen, O. L.
2016-01-01
Automated path planning is important for the automation and optimization of field operations. It can provide the waypoints required for guidance, navigation and control of agricultural robots and autonomous tractors throughout the execution of these field operations. In agriculture, field...... operations are usually repeated in the same field and from year to year as well, therefore, it should be carried out in a manner that minimizes environmental impact and cost taking into account the topographic land features. Current 3D terrain field coverage path planning algorithms are simply 2D coverage...
Zohreh Mahmoodi
2018-01-01
Full Text Available Background: Despite the large number of studies conducted on breastfeeding, no studies have yet examined the direct and indirect effects of socio-personal factors and mental health on breastfeeding. Aim: This study aimed to analyze of the effects of mental health and socio-personal factors on breastfeeding in infants aged less than six months. Method: This analytical cross-sectional study was conducted on 465 eligible mothers visiting general health centers in a northern city of Iran, in 2015. Data were collected using the researcher-made scale of socio-personal factors of breastfeeding, Spielberger’s State-Trait Anxiety Inventory, Beck’s Depression Inventory, Cohen’s Perceived Stress Scale, the Breastfeeding Difficulties Questionnaire, the Access to Healthcare Questionnaire, and the Poor Health Behaviors Questionnaire. Results: The path analysis of the mental health variables showed that breastfeeding problems are associated through a direct path with depression, through an indirect path with stress, and through both paths with anxiety; a positive correlation was thus observed between these variables and breastfeeding problems. Poor health behaviors also contributed to mothers’ breastfeeding problems through a direct path and indirectly by affecting their level of depression. Income had the highest positive effect (B=0.66, while the number of children had the highest negative effect (B=-3.16 on breastfeeding problems through a direct path. Poor health behaviors had the highest positive effect (B=0.75 and family support had the highest negative effect (B=-0.11 on breastfeeding. Implications for Practice: The early diagnosis of poor postpartum mental health in mothers can help reduce breastfeeding problems.
RISK ASSESSMENT IN PROJECT PLANNING USING FMEA AND CRITICAL PATH METHOD
Sandra Milena CHOLES ARVILLA
2014-10-01
Full Text Available This paper is based upon the research undertaken for the development of the doctoral thesis “Management of software projects based on object-oriented technology”. The study examines the existing risk management practices commonly used for classic software development. The goal is to integrate the elements of the traditional risk management methodologies to create a new agile risk management methodology. The thesis focuses on techniques that can be easily implemented in extreme programming (XP and SCRUM. This study is motivated by the following research questions: What are the elements of existing quality assurance tools that could meet the principles of agile development? And is it possible to use risk estimation for improving quality in agile projects? The thesis presents a synthesis of the most common risk management techniques, as well as an introduction to agile methods XP and SCRUM. The proposal integrates the concepts of Failure Mode and Effect Analysis into the iterative life cycle of an agile software project. The thesis presents a metamodel which integrates the concepts of agile development methodologies: SCRUM and XP with the FMEA concepts for risk quantification. The model was partly implemented into a real development project. Partial results show the improvement in early identification of failures and allowed to reconsider the Sprint plan.
Peter Juhasz
2017-03-01
Full Text Available While risk management gained popularity during the last decades even some of the basic risk types are still far out of focus. One of these is path dependency that refers to the uncertainty of how we reach a certain level of total performance over time. While decision makers are careful in accessing how their position will look like the end of certain periods, little attention is given how they will get there through the period. The uncertainty of how a process will develop across a shorter period of time is often “eliminated” by simply choosing a longer planning time interval, what makes path dependency is one of the most often overlooked business risk types. After reviewing the origin of the problem we propose and compare seven risk measures to access path. Traditional risk measures like standard deviation of sub period cash flows fail to capture this risk type. We conclude that in most cases considering the distribution of the expected cash flow effect caused by the path dependency may offer the best method, but we may need to use several measures at the same time to include all the optimisation limits of the given firm
Klose, Traugott
Major reforms brought about in July 1969 at the Free University of Berlin in its organization, planning, and decision making are reviewed. Specific problems are addressed, such as plans for introducing an information system on technical data and space use, plans for an information system on personnel employed by the university, and plans for an…
Multiagent path-finding in strategic games
Mihevc, Simon
2014-01-01
In this thesis I worked on creating, comparing and improving algorithms for multi-agent path planning on a domain typical for real-time strategy games. I implemented and compared Multiagent pathfinding using clearance and Multiagent pathfinding using independence detection and operator decomposition. I discovered that they had problems maintaining group compactness and took too long to calculate the path. I considerably improved the efficiency of both algorithms.
Problems of the current law concerning official plan approval
Bluemel, W.
1986-01-01
The booklet presents lectures held in October 1985 at the Speyer University for Administration Science, on the subject of the law concerning official plan approval. The lectures have been selected for their common interest in the requirements of nature conservation and landscape protection. These requirements and the current practice of plan approval procedure are the main issue of the lectures which discuss aspects of environmental impact statements, consideration of ecological requirements, and the role of the landscape conservation plan accompanying official project planning documents. (HSCH) [de
Ahmadreza Vajdi
2018-05-01
Full Text Available We study the problem of employing a mobile-sink into a large-scale Event-Driven Wireless Sensor Networks (EWSNs for the purpose of data harvesting from sensor-nodes. Generally, this employment improves the main weakness of WSNs that is about energy-consumption in battery-driven sensor-nodes. The main motivation of our work is to address challenges which are related to a network’s topology by adopting a mobile-sink that moves in a predefined trajectory in the environment. Since, in this fashion, it is not possible to gather data from sensor-nodes individually, we adopt the approach of defining some of the sensor-nodes as Rendezvous Points (RPs in the network. We argue that RP-planning in this case is a tradeoff between minimizing the number of RPs while decreasing the number of hops for a sensor-node that needs data transformation to the related RP which leads to minimizing average energy consumption in the network. We address the problem by formulating the challenges and expectations as a Mixed Integer Linear Programming (MILP. Henceforth, by proving the NP-hardness of the problem, we propose three effective and distributed heuristics for RP-planning, identifying sojourn locations, and constructing routing trees. Finally, experimental results prove the effectiveness of our approach.
Vajdi, Ahmadreza; Zhang, Gongxuan; Zhou, Junlong; Wei, Tongquan; Wang, Yongli; Wang, Tianshu
2018-05-04
We study the problem of employing a mobile-sink into a large-scale Event-Driven Wireless Sensor Networks (EWSNs) for the purpose of data harvesting from sensor-nodes. Generally, this employment improves the main weakness of WSNs that is about energy-consumption in battery-driven sensor-nodes. The main motivation of our work is to address challenges which are related to a network’s topology by adopting a mobile-sink that moves in a predefined trajectory in the environment. Since, in this fashion, it is not possible to gather data from sensor-nodes individually, we adopt the approach of defining some of the sensor-nodes as Rendezvous Points (RPs) in the network. We argue that RP-planning in this case is a tradeoff between minimizing the number of RPs while decreasing the number of hops for a sensor-node that needs data transformation to the related RP which leads to minimizing average energy consumption in the network. We address the problem by formulating the challenges and expectations as a Mixed Integer Linear Programming (MILP). Henceforth, by proving the NP-hardness of the problem, we propose three effective and distributed heuristics for RP-planning, identifying sojourn locations, and constructing routing trees. Finally, experimental results prove the effectiveness of our approach.
Zhang, Gongxuan; Wang, Yongli; Wang, Tianshu
2018-01-01
We study the problem of employing a mobile-sink into a large-scale Event-Driven Wireless Sensor Networks (EWSNs) for the purpose of data harvesting from sensor-nodes. Generally, this employment improves the main weakness of WSNs that is about energy-consumption in battery-driven sensor-nodes. The main motivation of our work is to address challenges which are related to a network’s topology by adopting a mobile-sink that moves in a predefined trajectory in the environment. Since, in this fashion, it is not possible to gather data from sensor-nodes individually, we adopt the approach of defining some of the sensor-nodes as Rendezvous Points (RPs) in the network. We argue that RP-planning in this case is a tradeoff between minimizing the number of RPs while decreasing the number of hops for a sensor-node that needs data transformation to the related RP which leads to minimizing average energy consumption in the network. We address the problem by formulating the challenges and expectations as a Mixed Integer Linear Programming (MILP). Henceforth, by proving the NP-hardness of the problem, we propose three effective and distributed heuristics for RP-planning, identifying sojourn locations, and constructing routing trees. Finally, experimental results prove the effectiveness of our approach. PMID:29734718
Optimization-based decision support systems for planning problems in processing industries
Claassen, G.D.H.
2014-01-01
Summary
Optimization-based decision support systems for planning problems in processing industries
Nowadays, efficient planning of material flows within and between supply chains is of vital importance and has become one of the most challenging problems for decision support in
Enhancement of a model for Large-scale Airline Network Planning Problems
Kölker, K.; Lopes dos Santos, Bruno F.; Lütjens, K.
2016-01-01
The main focus of this study is to solve the network planning problem based on passenger decision criteria including the preferred departure time and travel time for a real-sized airline network. For this purpose, a model of the integrated network planning problem is formulated including scheduling
R Goudarzi
2018-03-01
Full Text Available Introduction The demand of pre-determined optimal coverage paths in agricultural environments have been increased due to the growing application of field robots and autonomous field machines. Also coverage path planning problem (CPP has been extensively studied in robotics and many algorithms have been provided in many topics, but differences and limitations in agriculture lead to several different heuristic and modified adaptive methods from robotics. In this paper, a modified and enhanced version of currently used decomposition algorithm in robotics (boustrophedon cellular decomposition has been presented as a main part of path planning systems of agricultural vehicles. Developed algorithm is based on the parallelization of the edges of the polygon representing the environment to satisfy the requirements of the problem as far as possible. This idea is based on "minimum facing to the cost making condition" in turn, it is derived from encounter concept as a basis of cost making factors. Materials and Methods Generally, a line termed as a slice in boustrophedon cellular decomposition (BCD, sweeps an area in a pre-determined direction and decomposes the area only at critical points (where two segments can be extended to top and bottom of the point. Furthermore, sweep line direction does not change until the decomposition finish. To implement the BCD for parallelization method, two modifications were applied in order to provide a modified version of the boustrophedon cellular decomposition (M-BCD. In the first modification, the longest edge (base edge is targeted, and sweep line direction is set in line with the base edge direction (sweep direction is set perpendicular to the sweep line direction. Then Sweep line moves through the environment and stops at the first (nearest critical point. Next sweep direction will be the same as previous, If the length of those polygon's newly added edges, during the decomposition, are less than or equal to the
Compiling Planning into Quantum Optimization Problems: A Comparative Study
2015-06-07
to SAT, and then reduces higher order terms to quadratic terms through a series of gadgets . Our mappings allow both positive and negative preconditions...to its being specific to this type of problem) and likely benefits from an homogeneous parameter setting (Venturelli et al. 2014), as it generates a...Guzik, A. 2013. Resource efficient gadgets for compiling adiabatic quan- tum optimization problems. Annalen der Physik 525(10- 11):877–888. Blum, A
MIP-based approaches for complex planning problems
Broek, van den J.J.J.
2009-01-01
Plans and timetables can be found everywhere during our daily lives. Examples are the Dutch railway timetable, the schedule for the Dutch soccer league and the roster of nurses in hospitals or home care. Together with the increase in computing power, solution techniques for solving such real-world
Behaviour planning and problem solving deficiencies in children ...
Objective: To compare planning behaviour (frontal lobe functioning) in children with and without symptoms of attention deficit hyperactivity disorder (ADHD). Method: A total of 90 children (45 with symptoms of ADHD and 45 matched controls without ADHD symptoms) of both genders, who were medication naïve, from the ...
Prokhorov, L.V.
1982-01-01
The properties of path integrals associated with the allowance for nonstandard terms reflecting the operator nature of the canonical variables are considered. Rules for treating such terms (''equivalence rules'') are formulated. Problems with a boundary, the behavior of path integrals under canonical transformations, and the problem of quantization of dynamical systems with constraints are considered in the framework of the method
Tunjo Perić; Željko Mandić
2017-01-01
This paper presents the production plan optimization in the metal industry considered as a multi-criteria programming problem. We first provided the definition of the multi-criteria programming problem and classification of the multicriteria programming methods. Then we applied two multi-criteria programming methods (the STEM method and the PROMETHEE method) in solving a problem of multi-criteria optimization production plan in a company from the metal industry. The obtained resul...
Problems of Transition from a Planned to a Market Economy
Krelle, Wilhelm
2000-01-01
The paper shows that a transition from a planned to a market economy implies an important change of the structure of production, i. e. a reallocation of resources which takes time and induces sufferings for some people. These sufferings may be reduced by subsidization of some sectors, with some negative effects on GDP and growth if subsidization exceeds a certain size. The time tillthe economy in transition reaches an ``old" market economy (asymptotically or totally) is estimated by different...
Optimising the Slab Yard Planning and Crane Scheduling Problem using a two-stage heuristic
Hansen, Anders Dohn; Clausen, Jens
2010-01-01
In this paper, we present the Slab Yard Planning and Crane Scheduling Problem. The problem has its origin in steel production facilities with a large throughput. A slab yard is used as a buffer for slabs that are needed in the upcoming production. Slabs are transported by cranes and the problem...
A Generalized Orienteering Problem for Optimal Search and Interdiction Planning
2013-09-01
proposed for the TOP. Boussier et al. (2007) presents a branch-and- price algorithm that relies on a pricing step within the column generation phase...dominates in all metric categories and B&B appears to be the least favorable. We use performance proles ( Dolan and Moré 2002) as a method for comparing...exceeded, with greater computing power it may be possible to obtain the optimal solution in a period of time that can support a 24-hour planning
Population in urban development and the practical problems of urban planning policy in Africa
Joseph Uyanga
2013-07-01
Full Text Available The paper analyses the pattern of recent growth in African towns, examines the population component in this growth process and discusses the attendant urban planning problems. The contention in the study is that there are problems of definition. policy enunciation, and organisational co-ordination in the conceptualization. planning. orchestration and implementation of urban development and service systems. The magnitude of African urban developmental problems, and its multi-faceted nature demands that the latest in scientific knowledge and technological innovations should be integrated and incorporated into the urban planning and implementation processes.
Problem Based Internship in Surveying and Planning Curricula
Sørensen, Esben Munk; Enemark, Stig
2006-01-01
Programme has been divided into a 3 year Bachelor-Programme and after this a 2 year Master-Programme. It has been done as a part of a governmental policy to adapt and fulfil the Bologna-charter in all University Curricula in Denmark. A new element in the Master Programme is a problem-based internship...... economy and – leadership”. This course is organized as an e-Learning course and the student has to develop and document their skills to follow distance e-learning courses. It will prepare them to follow and organize self paced learning in virtual environment which will develop their capacity for life...... by the society to serve the community with still more new knowledge and technology transfer from the international research community. The internship and still more real world influenced problem based learning by writing thesis will be and important bridge builder in the following years....
Problems of future energy market planning and optimization
Lelek, V.; Jaluvka, D.
2007-01-01
Probable development of energy market is described in the article and special attention is devoted to the nuclear energy, which not only consume, but also produce raw material and how to proceed to avoid crises in supply. Problems of future energy supply of heat, liquid fuel, electricity are described. Expected effect will be jump in prices or regulated supply to equalize supply and use. It can completely change our standard consideration of profit
Problems of future energy market planning and optimization
Vladimir Lelek; David Jaluvka
2007-01-01
Problems of future energy supply in the form, which is demanded - heat, liquid fuel, electricity - are described. There are several factors, which probably could be studied separately: technology and its sustain ability with respect to the raw materials resources, long time for capacity construction, for some form of energy even absence of sufficiently deep technology knowledge and model of prices. Prices are specially peculiar problem - they could be very different from the standard approach (investment, operation and maintenance, fuel, profit), if there are market instabilities and you are not able to supply market by the demanded amount form of energy with the consequences on production. Expected effect will be jump in prices or regulated supply to equalize supply and use. Such situation will be until the new capacities are put into operation or new technologies of production are established - it could be time about ten or more years and this can completely change our standard consideration of profit. The main profit will be to avoid losses and unemployment. Also concept of local or domestic raw material resources could be changed - in the free market your resources will be sold to those paying more. Probable development of energy market is described in the article and special attention is devoted to the nuclear energy, which not only consume, but also produce raw material and how to proceed to avoid crises in supply. Contemporary understanding of the problem does not enable to formulate it strictly as mathematical optimization task (Authors)
Addressing global health, economic, and environmental problems through family planning.
Speidel, J Joseph; Grossman, Richard A
2011-06-01
Although obstetrician-gynecologists recognize the importance of managing fertility for the reproductive health of individuals, many are not aware of the vital effect they can have on some of the world's most pressing issues. Unintended pregnancy is a key contributor to the rapid population growth that in turn impairs social welfare, hinders economic progress, and exacerbates environmental degradation. An estimated 215 million women in developing countries wish to limit their fertility but do not have access to effective contraception. In the United States, half of all pregnancies are unplanned. Voluntary prevention of unplanned pregnancies is a cost-effective, humane way to limit population growth, slow environmental degradation, and yield other health and welfare benefits. Family planning should be a top priority for our specialty.
Tunjo Perić
2017-09-01
Full Text Available This paper presents the production plan optimization in the metal industry considered as a multi-criteria programming problem. We first provided the definition of the multi-criteria programming problem and classification of the multicriteria programming methods. Then we applied two multi-criteria programming methods (the STEM method and the PROMETHEE method in solving a problem of multi-criteria optimization production plan in a company from the metal industry. The obtained results indicate a high efficiency of the applied methods in solving the problem.
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.
M. A. Karakuts
2015-01-01
Full Text Available The basic problems of route network and aircraft fleet optimization and its role in airline strategic planning are considered. Measures to improve the methods of its implementation are proposed.
The motion planning problem and exponential stabilization of a heavy chain. Part II
Piotr Grabowski
2008-01-01
This is the second part of paper [P. Grabowski, The motion planning problem and exponential stabilization of a heavy chain. Part I, to appear in International Journal of Control], where a model of a heavy chain system with a punctual load (tip mass) in the form of a system of partial differential equations was interpreted as an abstract semigroup system and then analysed on a Hilbert state space. In particular, in [P. Grabowski, The motion planning problem and exponential stabilization of a h...
Optimization-based decision support systems for planning problems in processing industries
Claassen, G.D.H.
2014-01-01
Summary Optimization-based decision support systems for planning problems in processing industries Nowadays, efficient planning of material flows within and between supply chains is of vital importance and has become one of the most challenging problems for decision support in practice. The tremendous progress in hard- and software of the past decades was an important gateway for developing computerized systems that are able to support decision making on different levels within enterprises. T...
Kiosses, Dimitris N; Ravdin, Lisa D; Stern, Amy; Bolier, Ruth; Kenien, Cara; Reid, M Carrington
2017-01-01
Chronic pain is highly prevalent in older adults, contributes to activity restriction and social isolation, disrupts family and interpersonal relationships, and poses a significant economic burden to society. Negative emotions such as sadness, anxiety, helplessness, and hopelessness are associated with chronic pain and contribute to poor quality of life, impaired interpersonal and social functioning, and increased disability. Psychosocial interventions for older adults with chronic pain have been historically developed for, and are almost exclusively delivered to, cognitively intact patients. Therefore, many older adults with chronic pain and comorbid cognitive deficits have limited treatment options. Our multidisciplinary team developed Problem Adaptation Therapy for Pain in Primary Care (PATH-Pain), a psychosocial intervention for older adults with chronic pain, negative emotions, and a wide range of cognitive functioning, including mild-to-moderate cognitive impairment. In the current article, we describe the principles underlying PATH-Pain, review the steps taken to adapt the original PATH protocol, outline the treatment process, and present a case illustrating its potential value.
Mayasari, Ruth; Mawengkang, Herman; Gomar Purba, Ronal
2018-02-01
Land revitalization refers to comprehensive renovation of farmland, waterways, roads, forest or villages to improve the quality of plantation, raise the productivity of the plantation area and improve agricultural production conditions and the environment. The objective of sustainable land revitalization planning is to facilitate environmentally, socially, and economically viable land use. Therefore it is reasonable to use participatory approach to fullfil the plan. This paper addresses a multicriteria decision aid to model such planning problem, then we develop an interactive approach for solving the problem.
Marco A. Contreras; Woodam Chung; Greg Jones
2008-01-01
Forest transportation planning problems (FTPP) have evolved from considering only the financial aspects of timber management to more holistic problems that also consider the environmental impacts of roads. These additional requirements have introduced side constraints, making FTPP larger and more complex. Mixed-integer programming (MIP) has been used to solve FTPP, but...
Jammet, H.P.
1977-01-01
Problems associated with the organization and planning of medical treatment for radiation accident casualties are considered for different types of radiation accident: whole-body or partial irradiation, external or internal contamination and small or large numbers of cases. The problems posed are ones of competence, urgency and capacity; on the diagnostic side there is the problem of evaluating the exposure or contamination and assessing the resultant damage, while on the treatment side the questions of first aid, conventional treatment and specialized treatment have to be considered. The solutions envisaged involve organization at the local and national levels and planning of medical treatment by skilled, multidisciplinary medical teams. (author)
Act first, think later: the presence and absence of inferential planning in problem solving.
Ormerod, Thomas C; Macgregor, James N; Chronicle, Edward P; Dewald, Andrew D; Chu, Yun
2013-10-01
Planning is fundamental to successful problem solving, yet individuals sometimes fail to plan even one step ahead when it lies within their competence to do so. In this article, we report two experiments in which we explored variants of a ball-weighing puzzle, a problem that has only two steps, yet nonetheless yields performance consistent with a failure to plan. The results fit a computational model in which a solver's attempts are determined by two heuristics: maximization of the apparent progress made toward the problem goal and minimization of the problem space in which attempts are sought. The effectiveness of these heuristics was determined by lookahead, defined operationally as the number of steps evaluated in a planned move. Where move outcomes cannot be visualized but must be inferred, planning is constrained to the point where some individuals apply zero lookahead, which with n-ball problems yields seemingly irrational unequal weighs. Applying general-purpose heuristics with or without lookahead accounts for a range of rational and irrational phenomena found with insight and noninsight problems.
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...... Routing Problem based on partial paths is presented. Finally, a practical application of finding shortest paths in the telecommunication industry is shown....
Barnow, Sven; Schuckit, Marc A; Lucht, Michael; John, Ulrich; Freyberger, Harald J
2002-05-01
The purpose of this study was to test a hypothetical model of alcohol problems in German adolescents. Among 180 offspring, family history of alcoholism, parenting styles, behavioral and emotional problems, peer-group characteristics, feelings of self-esteem, behavioral problems and psychiatric comorbidity of the parents were examined. Data were generated from the Study of Health in Pomerania (SHIP), in which families were randomly selected if 12-18 year old biological offspring were members of the household; a smaller group of subjects was selected from local outpatient treatment centers. Members of 133 families, including 180 (50.6% male) offspring who were appropriate for the current analyses, received personal semistructured diagnostic interviews and several self-rating questionnaires. Analyses compared offspring with alcohol problems (AP; n = 40) and with no alcohol problems (NAP; n = 140), and used structural equation modeling to test a hypothetical model. The comparisons revealed that the AP group had significantly more behavioral problems (e.g., aggression/delinquency), more perceived parental rejection and less emotional warmth, a higher amount of alcohol consumption, were more likely to associate with substance-using peers and more often received a diagnosis of conduct disorder or antisocial personality disorder. Whereas the family history of alcoholism did not differ significantly between groups, parents of offspring with an alcohol use disorder had significantly more additional diagnoses on DSM-IV Axis I. The evaluation of the model supported the importance of aggression/delinquency and association with substance-using peers for alcohol problems in people. An additional diagnosis in the parents was directly and indirectly (through aggression/delinquency) related to alcohol problems of the adolescents. The data indicate that alcohol problems in the offspring are associated with several domains of influence in their environment. Prospective studies
A capacity expansion planning model for integrated water desalination and power supply chain problem
Saif, Y.; Almansoori, A.
2016-01-01
Highlights: • Water and power supply chain is considered by a discrete optimization model. • The model examines the capacity expansion and operation of the supply chain problem. • Renewable/alternative power technologies and carbon mitigation are considered. • A case study of Abu Dhabi in UAE is examined as an application of the model. - Abstract: Cogeneration of water and power in integrated cogeneration production plants is a common practice in the Middle East and North Africa (MENA) countries. There are several combinations of water desalination and power technologies which give significant adverse environmental impact. Renewable and alternative energy technologies have been recently proposed as alternative power production paths in the water and power sector. In this study, we examine the optimal capacity expansion of water and power infrastructure over an extended planning horizon. A generic mixed integer linear programming model is developed to assist in the decision making process on: (1) optimal installation of cogeneration expansion capacities; (2) optimal installation of renewable and alternative power plants; (3) optimal operation of the integrated water and power supply chain over large geographical areas. Furthermore, the model considers the installation of carbon capture methods in fossil-based power plants. A case study will be presented to illustrate the mathematical programming application for the Emirate of Abu Dhabi (AD) in the United Arab Emirates (UAE). The case study is solved reflecting different scenarios: base case scenario, integration of renewable and alternative technologies scenario, and CO_2 reduction targets scenario. The results show that increased carbon tax values up to 150 $/ton-CO_2 gives a maximum 3% cost increase for the supply chain net present value. The installation of carbon capture methods is not an economical solution due to its high operation energy requirements in the order of 370 kW h per ton of captured CO_2
Optimal Path Planner for Mobile Robot in 2D Environment
Valeri Kroumov
2004-06-01
Full Text Available The problem of path planning for the case of a mobile robot moving in an environment filled with obstacles with known shapes and positions is studied. A path planner based on the genetic algorithm approach, which generates optimal in length path is proposed. The population member paths are generated by another algorithm, which uses for description of the obstacles an artificial annealing neural network and is based on potential field approach. The resulting path is piecewise linear with changing directions at the corners of the obstacles. Because of this feature, the inverse kinematics problems in controlling differential drive robots are simply solved: to drive the robot to some goal pose (x, y, theta, the robot can be spun in place until it is aimed at (x, y, then driven forward until it is at (x, y, and then spun in place until the required goal orientation
Knudsen, Thomas Phillip; Madsen, Ole Brun
2004-01-01
are proposed. These problems appear on the background of a dawning understanding of IT infrastructure as a crucial part of the modern society comparable to the recognised infrastructures, such as roads and electricity. The IT-infrastructure and the problems are placed in the context of the growing importance......This paper gives an overview of the more prominent problems in IT infrastructure evolution and in particular the neccessary planning process in Denmark. A discussion of consequences and possible solutions is presented. Through the DDN-project Nordjysk Netforum, NJNF, and its partners and attendant...... research at Aalborg University, AAU, it has become apparent that several problems pose significant hindrances to an efficient IT-infrastructrure planning and implementation. These problems range form awareness of IT-infrastructure issues, over education and research to main cause and possible solutions...
Madsen, Ole Brun; Knudsen, Thomas Phillip
are proposed. These problems appear on the background of a dawning understanding of IT infrastructure as a crucial part of the modern society comparable to the recognised infrastructures, such as roads and electricity. The IT-infrastructure and the problems are placed in the context of the growing importance......This paper gives an overview of the more prominent problems in IT infrastructure evolution and in particular the neccessary planning process in Denmark. A discussion of consequences and possible solutions is presented. Through the DDN-project Nordjysk Netforum, NJNF, and its partners and attendant...... research at Aalborg University, AAU, it has become apparent that several problems pose significant hindrances to an efficient IT-infrastructrure planning and implementation. These problems range form awareness of IT-infrastructure issues, over education and research to main cause and possible solutions...
Muhammad Farhan Ausaf
2015-12-01
Full Text Available Process planning and scheduling are two important components of a manufacturing setup. It is important to integrate them to achieve better global optimality and improved system performance. To find optimal solutions for integrated process planning and scheduling (IPPS problem, numerous algorithm-based approaches exist. Most of these approaches try to use existing meta-heuristic algorithms for solving the IPPS problem. Although these approaches have been shown to be effective in optimizing the IPPS problem, there is still room for improvement in terms of quality of solution and algorithm efficiency, especially for more complicated problems. Dispatching rules have been successfully utilized for solving complicated scheduling problems, but haven’t been considered extensively for the IPPS problem. This approach incorporates dispatching rules with the concept of prioritizing jobs, in an algorithm called priority-based heuristic algorithm (PBHA. PBHA tries to establish job and machine priority for selecting operations. Priority assignment and a set of dispatching rules are simultaneously used to generate both the process plans and schedules for all jobs and machines. The algorithm was tested for a series of benchmark problems. The proposed algorithm was able to achieve superior results for most complex problems presented in recent literature while utilizing lesser computational resources.
Kosaka, Shinya; Saji, Etsuro
2000-01-01
A characteristics transport theory code, CHAPLET, has been developed for the purpose of making it practical to perform a whole LWR core calculation with the same level of calculational model and accuracy as that of an ordinary single assembly calculation. The characteristics routine employs the CACTUS algorithm for drawing ray tracing lines, which assists the two key features of the flux solution in the CHAPLET code. One is the direct neutron path linking (DNPL) technique which strictly connects angular fluxes at each assembly interface in the flux solution separated between assemblies. Another is to reduce the required memory storage by sharing the data related to ray tracing among assemblies with the same configuration. For faster computation, the coarse mesh rebalance (CMR) method and the Aitken method were incorporated in the code and the combined use of both methods showed the most promising acceleration performance among the trials. In addition, the parallelization of the flux solution was attempted, resulting in a significant reduction in the wall-clock time of the calculation. By all these efforts, coupled with the results of many verification studies, a whole LWR core heterogeneous transport theory calculation finally became practical. CHAPLET is thought to be a useful tool which can produce the reference solutions for analyses of an LWR (author)
None, None
2003-03-05
This report presents a plan for the deployment of a fusion demonstration power plant within 35 years, leading to commercial application of fusion energy by mid-century. The plan is derived from the necessary features of a demonstration fusion power plant and from the time scale defined by President Bush. It identifies critical milestones, key decision points, needed major facilities and required budgets.
Whitfield, Clifford A.
2009-12-01
A multi-objective technique for Unmanned Air Vehicle (UAV) path and trajectory autonomy generation, through task allocation and sensor fusion has been developed. The Dual-Optimal Path-Planning (D-O.P-P.) Technique generates on-line adaptive flight paths for UAVs based on available flight windows and environmental influenced objectives. The environmental influenced optimal condition, known as the driver' determines the condition, within a downstream virtual window of possible vehicle destinations and orientation built from the UAV kinematics. The intermittent results are pursued by a dynamic optimization technique to determine the flight path. This sequential optimization technique is a multi-objective optimization procedure consisting of two goals, without requiring additional information to combine the conflicting objectives into a single-objective. An example case-study and additional applications are developed and the results are discussed; including the application to the field of Solar Regenerative (SR) High Altitude Long Endurance (HALE) UAV flight. Harnessing solar energy has recently been adapted for use on high altitude UAV platforms. An aircraft that uses solar panels and powered by the sun during the day and through the night by SR systems, in principle could sustain flight for weeks or months. The requirements and limitations of solar powered flight were determined. The SR-HALE UAV platform geometry and flight characteristics were selected from an existing aircraft that has demonstrated the capability for sustained flight through flight tests. The goals were to maintain continual Situational Awareness (SA) over a case-study selected Area of Interest (AOI) and existing UAV power and surveillance systems. This was done for still wind and constant wind conditions at altitude along with variations in latitude. The characteristics of solar flux and the dependence on the surface location and orientation were established along with fixed flight maneuvers for
DeWitt-Morette, C.
1983-01-01
Much is expected of path integration as a quantization procedure. Much more is possible if one recognizes that path integration is at the crossroad of stochastic and differential calculus and uses the full power of both stochastic and differential calculus in setting up and computing path integrals. In contrast to differential calculus, stochastic calculus has only comparatively recently become an instrument of thought. It has nevertheless already been used in a variety of challenging problems, for instance in the quantization problem. The author presents some applications of the stochastic scheme. (Auth.)
Wilson, Helen W.; Widom, Cathy Spatz
2010-01-01
Behaviors beginning in childhood or adolescence may mediate the relationship between childhood maltreatment and involvement in prostitution. This paper examines 5 potential mediators: early sexual initiation, running away, juvenile crime, school problems, and early drug use. Using a prospective cohort design, abused and neglected children (ages…
Rehmat, Abeera Parvaiz
As we progress into the 21st century, higher-order thinking skills and achievement in science and math are essential to meet the educational requirement of STEM careers. Educators need to think of innovative ways to engage and prepare students for current and future challenges while cultivating an interest among students in STEM disciplines. An instructional pedagogy that can capture students' attention, support interdisciplinary STEM practices, and foster higher-order thinking skills is problem-based learning. Problem-based learning embedded in the social constructivist view of teaching and learning (Savery & Duffy, 1995) promotes self-regulated learning that is enhanced through exploration, cooperative social activity, and discourse (Fosnot, 1996). This quasi-experimental mixed methods study was conducted with 98 fourth grade students. The study utilized STEM content assessments, a standardized critical thinking test, STEM attitude survey, PBL questionnaire, and field notes from classroom observations to investigate the impact of problem-based learning on students' content knowledge, critical thinking, and their attitude towards STEM. Subsequently, it explored students' experiences of STEM integration in a PBL environment. The quantitative results revealed a significant difference between groups in regards to their content knowledge, critical thinking skills, and STEM attitude. From the qualitative results, three themes emerged: learning approaches, increased interaction, and design and engineering implementation. From the overall data set, students described the PBL environment to be highly interactive that prompted them to employ multiple approaches, including design and engineering to solve the problem.
Walwyn, Amy L.; Navarro, Daniel J.
2010-01-01
An experiment is reported comparing human performance on two kinds of visually presented traveling salesperson problems (TSPs), those reliant on Euclidean geometry and those reliant on city block geometry. Across multiple array sizes, human performance was near-optimal in both geometries, but was slightly better in the Euclidean format. Even so,…
A fuzzy approach to the generation expansion planning problem in a multi-objective environment
Abass, S. A.; Massoud, E. M. A.; Abass, S. A.)
2007-01-01
In many power system problems, the use of optimization techniques has proved inductive to reducing the costs and losses of the system. A fuzzy multi-objective decision is used for solving power system problems. One of the most important issues in the field of power system engineering is the generation expansion planning problem. In this paper, we use the concepts of membership functions to define a fuzzy decision model for generating an optimal solution for this problem. Solutions obtained by the fuzzy decision theory are always efficient and constitute the best compromise. (author)
Xu, Y; Li, N
2014-09-01
Biological species have produced many simple but efficient rules in their complex and critical survival activities such as hunting and mating. A common feature observed in several biological motion strategies is that the predator only moves along paths in a carefully selected or iteratively refined subspace (or manifold), which might be able to explain why these motion strategies are effective. In this paper, a unified linear algebraic formulation representing such a predator-prey relationship is developed to simplify the construction and refinement process of the subspace (or manifold). Specifically, the following three motion strategies are studied and modified: motion camouflage, constant absolute target direction and local pursuit. The framework constructed based on this varying subspace concept could significantly reduce the computational cost in solving a class of nonlinear constrained optimal trajectory planning problems, particularly for the case with severe constraints. Two non-trivial examples, a ground robot and a hypersonic aircraft trajectory optimization problem, are used to show the capabilities of the algorithms in this new computational framework.
Xu, Y; Li, N
2014-01-01
Biological species have produced many simple but efficient rules in their complex and critical survival activities such as hunting and mating. A common feature observed in several biological motion strategies is that the predator only moves along paths in a carefully selected or iteratively refined subspace (or manifold), which might be able to explain why these motion strategies are effective. In this paper, a unified linear algebraic formulation representing such a predator–prey relationship is developed to simplify the construction and refinement process of the subspace (or manifold). Specifically, the following three motion strategies are studied and modified: motion camouflage, constant absolute target direction and local pursuit. The framework constructed based on this varying subspace concept could significantly reduce the computational cost in solving a class of nonlinear constrained optimal trajectory planning problems, particularly for the case with severe constraints. Two non-trivial examples, a ground robot and a hypersonic aircraft trajectory optimization problem, are used to show the capabilities of the algorithms in this new computational framework. (paper)
Parametric linear programming for a materials requirement planning problem solution with uncertainty
Martin Darío Arango Serna; Conrado Augusto Serna; Giovanni Pérez Ortega
2010-01-01
Using fuzzy set theory as a methodology for modelling and analysing decision systems is particularly interesting for researchers in industrial engineering because it allows qualitative and quantitative analysis of problems involving uncertainty and imprecision. Thus, in an effort to gain a better understanding of the use of fuzzy logic in industrial engineering, more specifically in the field of production planning, this article was aimed at providing a materials requirement planning (MRP) pr...
The IAEA and Y2K. The Agency's action plan on the year 2000 problem
Cherif, H.S.; Winkels, J.
1999-01-01
The article describes the aims of it IAEA action plan concerned with Year 2000 (Y2K) problem and the results achieved during four years of work, including the technical documents dealing with the Y2K computer problem, published by IAEA. This include IAEA systems and operations, contingency plans, coordination in the United Nations system. Through the IAEA Internet site, a series of Web pages were developed by the Division of Public Information to co-ordinate the global exchange of information on the IAEA Y2K activities and related topics. The site is open to Member States and international organisations within and outside United Nations system
Application of particle swarm optimization algorithm in the heating system planning problem.
Ma, Rong-Jiang; Yu, Nan-Yang; Hu, Jun-Yi
2013-01-01
Based on the life cycle cost (LCC) approach, this paper presents an integral mathematical model and particle swarm optimization (PSO) algorithm for the heating system planning (HSP) problem. The proposed mathematical model minimizes the cost of heating system as the objective for a given life cycle time. For the particularity of HSP problem, the general particle swarm optimization algorithm was improved. An actual case study was calculated to check its feasibility in practical use. The results show that the improved particle swarm optimization (IPSO) algorithm can more preferably solve the HSP problem than PSO algorithm. Moreover, the results also present the potential to provide useful information when making decisions in the practical planning process. Therefore, it is believed that if this approach is applied correctly and in combination with other elements, it can become a powerful and effective optimization tool for HSP problem.
A hybrid heuristic algorithm for the open-pit-mining operational planning problem.
Souza, Marcone Jamilson Freitas; Coelho, Igor Machado; Ribas, Sabir; Santos, Haroldo Gambini; Merschmann, Luiz Henrique de Campos
2010-01-01
This paper deals with the Open-Pit-Mining Operational Planning problem with dynamic truck allocation. The objective is to optimize mineral extraction in the mines by minimizing the number of mining trucks used to meet production goals and quality requirements. According to the literature, this problem is NPhard, so a heuristic strategy is justified. We present a hybrid algorithm that combines characteristics of two metaheuristics: Greedy Randomized Adaptive Search Procedures and General Varia...
Tekiner, Hatice [Industrial Engineering, College of Engineering and Natural Sciences, Istanbul Sehir University, 2 Ahmet Bayman Rd, Istanbul (Turkey); Coit, David W. [Department of Industrial and Systems Engineering, Rutgers University, 96 Frelinghuysen Rd., Piscataway, NJ (United States); Felder, Frank A. [Edward J. Bloustein School of Planning and Public Policy, Rutgers University, Piscataway, NJ (United States)
2010-12-15
A new approach to the electricity generation expansion problem is proposed to minimize simultaneously multiple objectives, such as cost and air emissions, including CO{sub 2} and NO{sub x}, over a long term planning horizon. In this problem, system expansion decisions are made to select the type of power generation, such as coal, nuclear, wind, etc., where the new generation asset should be located, and at which time period expansion should take place. We are able to find a Pareto front for the multi-objective generation expansion planning problem that explicitly considers availability of the system components over the planning horizon and operational dispatching decisions. Monte-Carlo simulation is used to generate numerous scenarios based on the component availabilities and anticipated demand for energy. The problem is then formulated as a mixed integer linear program, and optimal solutions are found based on the simulated scenarios with a combined objective function considering the multiple problem objectives. The different objectives are combined using dimensionless weights and a Pareto front can be determined by varying these weights. The mathematical model is demonstrated on an example problem with interesting results indicating how expansion decisions vary depending on whether minimizing cost or minimizing greenhouse gas emissions or pollutants is given higher priority. (author)
1975-06-01
Traditionally, synchronization of concurrent processes is coded in line by operations on semaphores or similar objects. Path expressions move the...discussion about a variety of synchronization primitives . An analysis of their relative power is found in [3]. Path expressions do not introduce yet...another synchronization primitive . A path expression relates to such primitives as a for- or while-statement of an ALGOL-like language relates to a JUMP
Spreading paths in partially observed social networks
Onnela, Jukka-Pekka; Christakis, Nicholas A.
2012-01-01
Understanding how and how far information, behaviors, or pathogens spread in social networks is an important problem, having implications for both predicting the size of epidemics, as well as for planning effective interventions. There are, however, two main challenges for inferring spreading paths in real-world networks. One is the practical difficulty of observing a dynamic process on a network, and the other is the typical constraint of only partially observing a network. Using a static, s...
The Teacher's Encyclopedia of Behavior Management: 100 Problems/500 Plans for Grades K-9.
Sprick, Randall S.; Howard, Lisa M.
This reference is intended to provide teachers with a wide variety of intervention plans for responding to behavior, discipline, and motivation problems. While most interventions are based on behavioral research, others are derived from counseling, Adlerian psychology, social learning theory, and cognitive/behavior modification approaches. An…
Single string planning problem arising in liner shipping industries: A heuristic approach
Gelareh, Shahin; Neamatian Monemi, Rahimeh; Mahey, Philippe
2013-01-01
We propose an efficient heuristic approach for solving instances of the Single String Planning Problem (SSPP) arising in the liner shipping industry. In the SSPP a Liner Service Provider (LSP) only revises one of its many operational strings, and it is assumed that the other strings are unchangea...
Problems of Implementation of Strategic Plans for Secondary Schools' Improvement in Anambra State
Chukwumah, Fides Okwukweka; Ezeugbor, Carol Obiageli
2015-01-01
This study investigated the extent of problems of strategic plans implementation for secondary schools' improvement in Anambra State, Nigeria for quality education provision. The study used a descriptive survey design paradigm. Respondents comprised 217 principals. There was no sampling. All the principals were used. Data were collected using…
The waste tyre problem in South Africa: An analysis of the REDISA plan
Nkosi, N
2013-04-01
Full Text Available problem only but has the potential to contribute to job creation, capacity building, establishment of small businesses as well as research and development of new and innovative waste tyre utilization techniques. The Plan is seen as the only viable approach...
Modeling an integrated hospital management planning problem using integer optimization approach
Sitepu, Suryati; Mawengkang, Herman; Irvan
2017-09-01
Hospital is a very important institution to provide health care for people. It is not surprising that nowadays the people’s demands for hospital is increasing. However, due to the rising cost of healthcare services, hospitals need to consider efficiencies in order to overcome these two problems. This paper deals with an integrated strategy of staff capacity management and bed allocation planning to tackle these problems. Mathematically, the strategy can be modeled as an integer linear programming problem. We solve the model using a direct neighborhood search approach, based on the notion of superbasic variables.
Vu, Duy-Duc; Monies, Frédéric; Rubio, Walter
2018-05-01
A large number of studies, based on 3-axis end milling of free-form surfaces, seek to optimize tool path planning. Approaches try to optimize the machining time by reducing the total tool path length while respecting the criterion of the maximum scallop height. Theoretically, the tool path trajectories that remove the most material follow the directions in which the machined width is the largest. The free-form surface is often considered as a single machining area. Therefore, the optimization on the entire surface is limited. Indeed, it is difficult to define tool trajectories with optimal feed directions which generate largest machined widths. Another limiting point of previous approaches for effectively reduce machining time is the inadequate choice of the tool. Researchers use generally a spherical tool on the entire surface. However, the gains proposed by these different methods developed with these tools lead to relatively small time savings. Therefore, this study proposes a new method, using toroidal milling tools, for generating toolpaths in different regions on the machining surface. The surface is divided into several regions based on machining intervals. These intervals ensure that the effective radius of the tool, at each cutter-contact points on the surface, is always greater than the radius of the tool in an optimized feed direction. A parallel plane strategy is then used on the sub-surfaces with an optimal specific feed direction for each sub-surface. This method allows one to mill the entire surface with efficiency greater than with the use of a spherical tool. The proposed method is calculated and modeled using Maple software to find optimal regions and feed directions in each region. This new method is tested on a free-form surface. A comparison is made with a spherical cutter to show the significant gains obtained with a toroidal milling cutter. Comparisons with CAM software and experimental validations are also done. The results show the
Hagger, Martin S; Chan, Derwin K C; Protogerou, Cleo; Chatzisarantis, Nikos L D
2016-08-01
Synthesizing research on social cognitive theories applied to health behavior is an important step in the development of an evidence base of psychological factors as targets for effective behavioral interventions. However, few meta-analyses of research on social cognitive theories in health contexts have conducted simultaneous tests of theoretically-stipulated pattern effects using path analysis. We argue that conducting path analyses of meta-analytic effects among constructs from social cognitive theories is important to test nomological validity, account for mediation effects, and evaluate unique effects of theory constructs independent of past behavior. We illustrate our points by conducting new analyses of two meta-analyses of a popular theory applied to health behaviors, the theory of planned behavior. We conducted meta-analytic path analyses of the theory in two behavioral contexts (alcohol and dietary behaviors) using data from the primary studies included in the original meta-analyses augmented to include intercorrelations among constructs and relations with past behavior missing from the original analysis. Findings supported the nomological validity of the theory and its hypotheses for both behaviors, confirmed important model processes through mediation analysis, demonstrated the attenuating effect of past behavior on theory relations, and provided estimates of the unique effects of theory constructs independent of past behavior. Our analysis illustrates the importance of conducting a simultaneous test of theory-stipulated effects in meta-analyses of social cognitive theories applied to health behavior. We recommend researchers adopt this analytic procedure when synthesizing evidence across primary tests of social cognitive theories in health. Copyright © 2016 Elsevier Inc. All rights reserved.
K. Karthikeyan
2012-10-01
Full Text Available This paper describes the application of an evolutionary algorithm, Restart Covariance Matrix Adaptation Evolution Strategy (RCMA-ES to the Generation Expansion Planning (GEP problem. RCMA-ES is a class of continuous Evolutionary Algorithm (EA derived from the concept of self-adaptation in evolution strategies, which adapts the covariance matrix of a multivariate normal search distribution. The original GEP problem is modified by incorporating Virtual Mapping Procedure (VMP. The GEP problem of a synthetic test systems for 6-year, 14-year and 24-year planning horizons having five types of candidate units is considered. Two different constraint-handling methods are incorporated and impact of each method has been compared. In addition, comparison and validation has also made with dynamic programming method.
NSGA-II algorithm for multi-objective generation expansion planning problem
Murugan, P.; Kannan, S. [Electronics and Communication Engineering Department, Arulmigu Kalasalingam College of Engineering, Krishnankoil 626190, Tamilnadu (India); Baskar, S. [Electrical Engineering Department, Thiagarajar College of Engineering, Madurai 625015, Tamilnadu (India)
2009-04-15
This paper presents an application of Elitist Non-dominated Sorting Genetic Algorithm version II (NSGA-II), to multi-objective generation expansion planning (GEP) problem. The GEP problem is considered as a two-objective problem. The first objective is the minimization of investment cost and the second objective is the minimization of outage cost (or maximization of reliability). To improve the performance of NSGA-II, two modifications are proposed. One modification is incorporation of Virtual Mapping Procedure (VMP), and the other is introduction of controlled elitism in NSGA-II. A synthetic test system having 5 types of candidate units is considered here for GEP for a 6-year planning horizon. The effectiveness of the proposed modifications is illustrated in detail. (author)
Marc Reimann
2014-05-01
Full Text Available Keen competition and increasingly demanding customers have forced companies to use their resources more efficiently and to integrate production and transportation planning. In the last few years more and more researchers have also focused on this challenging problem by trying to determine the complexity of the individual problems and then developing fast and robust algorithms to solve them. This paper reviews existing literature on integrated production and distribution decisions at the tactical and operational level, where the distribution part is modelled as some variation of the well-known Vehicle Routing Problem (VRP. The focus is thereby on problems that explicitly consider deliveries to multiple clients in a less-than-truckload fashion. In terms of the production decisions we distinguish in our review between tactical and operational production problems by considering lot-sizing/capacity allocation and scheduling models, respectively.
Vrooijink, Gustaaf J.; Abayazid, Momen; Patil, Sachin; Alterovitz, Ron; Misra, Sarthak
2015-01-01
Needle insertion is commonly performed in minimally invasive medical procedures such as biopsy and radiation cancer treatment. During such procedures, accurate needle tip placement is critical for correct diagnosis or successful treatment. Accurate placement of the needle tip inside tissue is challenging, especially when the target moves and anatomical obstacles must be avoided. We develop a needle steering system capable of autonomously and accurately guiding a steerable needle using two-dimensional (2D) ultrasound images. The needle is steered to a moving target while avoiding moving obstacles in a three-dimensional (3D) non-static environment. Using a 2D ultrasound imaging device, our system accurately tracks the needle tip motion in 3D space in order to estimate the tip pose. The needle tip pose is used by a rapidly exploring random tree-based motion planner to compute a feasible needle path to the target. The motion planner is sufficiently fast such that replanning can be performed repeatedly in a closed-loop manner. This enables the system to correct for perturbations in needle motion, and movement in obstacle and target locations. Our needle steering experiments in a soft-tissue phantom achieves maximum targeting errors of 0.86 ± 0.35 mm (without obstacles) and 2.16 ± 0.88 mm (with a moving obstacle). PMID:26279600
Digital Problems and Strategies of Partial Revision in Overall Plan of Land Use
2010-01-01
The technical route of partial revision in overall plan of land use is briefly described.It is pointed out that problems of area measuring in the technical route are mainly due to the digital process.The digital problems of partial revision in overall plan of land use are presented as follows:the maps are not proofread before digitalization;the coordinate matching and projection transformation are not conducted on the maps;the information is asymmetrical pre and post the digitalization;the location lacks precision;the result maps are substandard.The causes of these problems are analyzed,which cover the following aspects.The lack of united management regulations;uneven working abilities of the staff in the compilation units;unawareness of the importance of map digilalization;poor basic conclitions of the original plan maps.At last,the relevant suggestions are put forward,for instance,releasing the national united management methods and technical criteria,establishing industrial admittance system and qualification system of complication units,setting up the mechanism of supervising digitalized results and controlling the quality,conducting coordinate matching and projection transformation and unifying the specification and mode of the results of maps so as to provide technical support for the overall plan of land use,play the micro-regulating role of land use and take a leading role in the sustainable development of social economy.
Pereira, Hernane Borges de Barros; Pérez Vidal, Lluís; Lozada, Eleazar G. Madrid
2003-01-01
Behavioral impedance domain consists of a theory on route planning for pedestrians, within which constraint management is considered. The goal of this paper is to present the k-shortest path model using the behavioral impedance approach. After the mathematical model building, optimization problem and resolution problem by a behavioral impedance algorithm, it is discussed how behavioral impedance cost function is embedded in the k-shortest path model. From the pedestrian's route planning persp...
Morris, J. F.; Merrill, O. S.; Reddy, H. K.
1981-01-01
Thermionic energy conversion (TEC) is discussed. In recent TEC-topping analyses, overall plant efficiency (OPE) and cost of electricity (COE) improved slightly with current capabilities and substantially with fully matured technologies. Enhanced credibility derives from proven hot-corrosion protection for TEC by silicon-carbide clads in fossil fuel combustion products. Combustion augmentation with TEC (CATEC) affords minimal cost and plant perturbation, but with smaller OPE and COE improvements than more conventional topping applications. Risk minimization as well as comparative simplicity and convenience, favor CATEC for early market penetration. A program-management plan is proposed. Inputs, characteristics, outputs and capabilities are discussed.
Morris, J. F.; Merrill, O. S.; Reddy, H. K.
Thermionic energy conversion (TEC) is discussed. In recent TEC-topping analyses, overall plant efficiency (OPE) and cost of electricity (COE) improved slightly with current capabilities and substantially with fully matured technologies. Enhanced credibility derives from proven hot-corrosion protection for TEC by silicon-carbide clads in fossil fuel combustion products. Combustion augmentation with TEC (CATEC) affords minimal cost and plant perturbation, but with smaller OPE and COE improvements than more conventional topping applications. Risk minimization as well as comparative simplicity and convenience, favor CATEC for early market penetration. A program-management plan is proposed. Inputs, characteristics, outputs and capabilities are discussed.
Tahvili, Sahar; Österberg, Jonas; Silvestrov, Sergei; Biteus, Jonas
2014-01-01
One of the most important factors in the operations of many cooperations today is to maximize profit and one important tool to that effect is the optimization of maintenance activities. Maintenance activities is at the largest level divided into two major areas, corrective maintenance (CM) and preventive maintenance (PM). When optimizing maintenance activities, by a maintenance plan or policy, we seek to find the best activities to perform at each point in time, be it PM or CM. We explore the use of stochastic simulation, genetic algorithms and other tools for solving complex maintenance planning optimization problems in terms of a suggested framework model based on discrete event simulation
Application of the Monte Carlo method to the problem of expensive experiment planning
Aleksandrov, V.M.; Sanina, S.B.
1989-01-01
Numerical method for determination of the optimal experiment plan by the criterion of maximizing the information worth is suggested. The method is based on statistical mathematical simulation of possible outcomes of the experiment and on the analysis of efficiency of subsequent solutions. It is shown that results of conducted statistical simulation contain the data, enabling to determine the direction of plan correction, which provides the increase of its efficiency. A major advantages of the method are that it enables to interpret evidently all its stages and can be used in many-dimensional problems
Tahvili, Sahar [Mälardalen University (Sweden); Österberg, Jonas; Silvestrov, Sergei [Division of Applied Mathematics, Mälardalen University (Sweden); Biteus, Jonas [Scania CV (Sweden)
2014-12-10
One of the most important factors in the operations of many cooperations today is to maximize profit and one important tool to that effect is the optimization of maintenance activities. Maintenance activities is at the largest level divided into two major areas, corrective maintenance (CM) and preventive maintenance (PM). When optimizing maintenance activities, by a maintenance plan or policy, we seek to find the best activities to perform at each point in time, be it PM or CM. We explore the use of stochastic simulation, genetic algorithms and other tools for solving complex maintenance planning optimization problems in terms of a suggested framework model based on discrete event simulation.
Approximation Algorithm for a Heterogeneous Vehicle Routing Problem
Jungyun Bae
2015-08-01
Full Text Available This article addresses a fundamental path planning problem which aims to route a collection of heterogeneous vehicles such that each target location is visited by some vehicle and the sum of the travel costs of the vehicles is minimal. Vehicles are heterogeneous as the cost of traveling between any two locations depends on the type of the vehicle. Algorithms are developed for this path planning problem with bounds on the quality of the solutions produced by the algorithms. Computational results show that high quality solutions can be obtained for the path planning problem involving four vehicles and 40 targets using the proposed approach.
Optimizing a Biobjective Production-Distribution Planning Problem Using a GRASP
Martha-Selene Casas-Ramírez
2018-01-01
Full Text Available This paper addresses a biobjective production-distribution planning problem. The problem is formulated as a mixed integer programming problem with two objectives. The objectives are to minimize the total costs and to balance the total workload of the supply chain, which consist of plants and depots, considering that it represents a company vertically integrated. In order to solve the model, we propose an adapted biobjective GRASP to obtain an approximation of the Pareto front. To evaluate the performance of the proposed algorithm, numerical experimentations are conducted over a set of instances used for similar problems. Results indicate that the proposed GRASP obtains a relatively small number of nondominated solutions for each tested instance in very short computational time. The approximated Pareto fronts are discontinuous and nonconvex. Moreover, the solutions clearly show the compromise between both objective functions.
Development of reference problems for neutron capture therapy treatment planning systems
Albritton, J.R.; Kiger, W.S. III
2006-01-01
Currently, 5 different treatment planning systems (TPSs) are or have been used in clinical trials of Neutron Capture Therapy (NCT): MacNCTPlan, NCTPlan, BNCT Rtpe, SERA, and JCDS. This paper describes work performed to comprehensively test and compare 4 of these NCT treatment planning systems in order to facilitate the pooling of patient data from the different clinical sites for analysis of the clinical results as well as to provide an important quality assurance tool for existing and future TPSs. Two different phantoms were used to evaluate the planning systems: the modified Snyder head phantom and a large water-filled box, similar to that used in the International Dosimetry Exchange for NCT. The comparison of the resulting dose profile, isodose contours, and dose volume histograms to reference calculations performed with the Monte Carlo radiation transport code MCNP5 yielded many interesting differences. Each of the planning systems deviated from the reference calculations, with the newer systems (i.e., SERA and NCTPlan) most often yielding better agreement than their predecessors (i.e., BNCT Rtpe and MacNCTPlan). The combination of simple phantoms and sources with more complicated and realistic planning conditions has produced a well-rounded and useful suite of test problems for NCT treatment planning system analysis. (author)
Yuan Chen
2011-09-01
Full Text Available This paper proposes a piecewise acceleration-optimal and smooth-jerk trajectory planning method of robot manipulator. The optimal objective function is given by the weighted sum of two terms having opposite effects: the maximal acceleration and the minimal jerk. Some computing techniques are proposed to determine the optimal solution. These techniques take both the time intervals between two interpolation points and the control points of B-spline function as optimal variables, redefine the kinematic constraints as the constraints of optimal variables, and reformulate the objective function in matrix form. The feasibility of the optimal method is illustrated by simulation and experimental results with pan mechanism for cooking robot.
Communication on climate, energy, natural gas and forests as a problem for energy planning
Czeskleba-Dupont, Rolf
Danish energy planning has since its inception in the end of the 1970s been politically controversial, which led to language problems of communicating on alternatives (natural gas, nuclear energy). But previously alternative scenarios were in the 1990s successfully transformed into law...... that it can happen on the ground of wrong premises (on CO2 neutrality e.g.) that a shift say from natural gas to wood combustion can be interpreted as a solution to climate problems, whereas this in reality aggravates them. Not the least because forests because of continuously high emissions of CO2...
Hendler, James A
2014-01-01
A recent area of interest in the Artificial Intelligence community has been the application of massively parallel algorithms to enhance the choice mechanism in traditional AI problems. This volume provides a detailed description of how marker-passing -- a parallel, non-deductive, spreading activation algorithm -- is a powerful approach to refining the choice mechanisms in an AI problem-solving system. The author scrutinizes the design of both the algorithm and the system, and then reviews the current literature and research in planning and marker passing. Also included: a comparison of this
Path-based Queries on Trajectory Data
Krogh, Benjamin Bjerre; Pelekis, Nikos; Theodoridis, Yannis
2014-01-01
In traffic research, management, and planning a number of path-based analyses are heavily used, e.g., for computing turn-times, evaluating green waves, or studying traffic flow. These analyses require retrieving the trajectories that follow the full path being analyzed. Existing path queries cannot...... sufficiently support such path-based analyses because they retrieve all trajectories that touch any edge in the path. In this paper, we define and formalize the strict path query. This is a novel query type tailored to support path-based analysis, where trajectories must follow all edges in the path...... a specific path by only retrieving data from the first and last edge in the path. To correctly answer strict path queries existing network-constrained trajectory indexes must retrieve data from all edges in the path. An extensive performance study of NETTRA using a very large real-world trajectory data set...
Leader-Follower Approach to Gas-Electricity Expansion Planning Problem
Khaligh, Vahid; Oloomi Buygi, Majid; Anvari-Moghaddam, Amjad
2018-01-01
investment in capacity addition to the generation and transmission levels while considers the limitations on fuel consumption. On the other hand gas operator decides about investment in gas pipelines expansions considering the demanded gas by the electricity network. In this planning model for a joint gas......The main purpose of this paper is to develop a method for sequential gas and electricity networks expansion planning problem. A leader-follower approach performs the expansion planning of the joint gas and electricity networks. Electric system operator under adequacy incentive decides about......-electricity network, supply and demand are matched together while adequacy of fuel for gas consuming units is also guaranteed. To illustrate the effectiveness of the proposed method Khorasan province of Iran is considered as a case study which has a high penetration level of gas-fired power plants (GFPP). Also...
Porter, S H; Yocus, T E
1994-05-01
In today's world, it is a challenge just to stay in business, let alone remain competitive in a specific industry. We will show you how to pinpoint MRP II problems and attack them through self-assessment audits. You will discover the secrets of breaking down barriers between Master Schedulers, Material Planners, Production Control Planners, and the Manufacturing Line. Self-assessment audits are one way to take care of your planning functions before outside auditors take care of them for you.
HMOs and physician recruiting: a survey of problems and methods among group practice plans.
Fink, R
1981-01-01
A mail survey was conducted among 69 group practice health maintenance organizations (HMOs) to collect information on the recruiting of primary care physicians and specialists. In reporting on difficulties in recruiting physicians for primary care, the medical directors of HMOs indicated that the greatest problem was locating obstetrician-gynecologists. Among specialists, recruiting for orthopedists was reported as being most difficult, although plans that employ neurologists and anesthesiolo...
Jianfei Ye
2015-01-01
Full Text Available In order to solve the joint optimization of production scheduling and maintenance planning problem in the flexible job-shop, a multiobjective joint optimization model considering the maximum completion time and maintenance costs per unit time is established based on the concept of flexible job-shop and preventive maintenance. A weighted sum method is adopted to eliminate the index dimension. In addition, a double-coded genetic algorithm is designed according to the problem characteristics. The best result under the circumstances of joint decision-making is obtained through multiple simulation experiments, which proves the validity of the algorithm. We can prove the superiority of joint optimization model by comparing the result of joint decision-making project with the result of independent decision-making project under fixed preventive maintenance period. This study will enrich and expand the theoretical framework and analytical methods of this problem; it provides a scientific decision analysis method for enterprise to make production plan and maintenance plan.
On-Line Path Generation and Tracking for High-Speed Wheeled Autonomous Vehicles
2006-02-17
On-Line Path Generation and Tracking for High-Speed Wheeled Autonomous Vehicles Report Title ABSTRACT In this work we proposed two semi-analytic...298-102 Enclosure 1 On-Line Path Generation and Tracking for High-Speed Wheeled Autonomous Vehicles by...Specifically, the following problems will be addressed during this project: 2.1 Challenges The problem of trajectory planning for high-speed autonomous vehicles is
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.
Thompson, M.P.; Sessions, J.; Hamann, J.D.
2009-01-01
Genetic algorithms (GAs) have demonstrated success in solving spatial forest planning problems. We present an adaptive GA that incorporates population-level statistics to dynamically update penalty functions, a process analogous to strategic oscillation from the tabu search literature. We also explore performance of various selection strategies. The GA identified feasible solutions within 96%, 98%, and 93% of a non spatial relaxed upper bound calculated for landscapes of 100, 500, and 1000 units, respectively. The problem solved includes forest structure constraints limiting harvest opening sizes and requiring minimally sized patches of mature forest. Results suggest that the dynamic penalty strategy is superior to the more standard static penalty implementation. Results also suggest that tournament selection can be superior to the more standard implementation of proportional selection for smaller problems, but becomes susceptible to premature convergence as problem size increases. It is therefore important to balance selection pressure with appropriate disruption. We conclude that integrating intelligent search strategies into the context of genetic algorithms can yield improvements and should be investigated for future use in spatial planning with ecological goals.
Inverse planning for x-ray rotation therapy: a general solution of the inverse problem
Oelfke, U.; Bortfeld, T.
1999-01-01
Rotation therapy with photons is currently under investigation for the delivery of intensity modulated radiotherapy (IMRT). An analytical approach for inverse treatment planning of this radiotherapy technique is described. The inverse problem for the delivery of arbitrary 2D dose profiles is first formulated and then solved analytically. In contrast to previously applied strategies for solving the inverse problem, it is shown that the most general solution for the fluence profiles consists of two independent solutions of different parity. A first analytical expression for both fluence profiles is derived. The mathematical derivation includes two different strategies, an elementary expansion of fluence and dose into polynomials and a more practical approach in terms of Fourier transforms. The obtained results are discussed in the context of previous work on this problem. (author)
Metropolis Parking Problems and Management Planning Solutions for Traffic Operation Effectiveness
Yuejun Liu
2012-01-01
Full Text Available Advances in mobility are clearly illustrated by the rapid development of urbanization and motorization in developing countries. Following the dramatic incensement of traffic demand, the parking problem has been becoming much more seriously important in many metropolises. With the aim of seeking solutions as to how the parking system could operate more efficiently by using new technologies and new methodologies, this paper discusses the application of geographic information system into the parking planning and management for traffic operation effectiveness in metropolis. The concentration of this paper includes the characteristics of parking demand and the causations of parking problems, especially the basic parking principle and strategies for solving parking problems from the perspective of geographic information system are discussed in enough detail in this paper.
Prokhorov, L.V.
1982-01-01
Problems related to consideration of operator nonpermutability in Hamiltonian path integral (HPI) are considered in the review. Integrals are investigated using trajectories in configuration space (nonrelativistic quantum mechanics). Problems related to trajectory integrals in HPI phase space are discussed: the problem of operator nonpermutability consideration (extra terms problem) and corresponding equivalence rules; ambiguity of HPI usual recording; transition to curvilinear coordinates. Problem of quantization of dynamical systems with couplings has been studied. As in the case of canonical transformations, quantization of the systems with couplings of the first kind requires the consideration of extra terms
Problems of spatial planning and urban development: social-philosophical aspect
Mezentsev Sergey Dmitrievich
2014-07-01
Full Text Available The article examines social and philosophical problems of spatial planning and urban development from the 1920's until the present. From the historical point of view there are three phases: the 1920s, 1930-1980s, 1990-2010s. In the 1920s two approaches were used in the development of the country: technical and economic and personalistics. The first meant not only the development of power engineering but also of the economy in the whole country. The second lies in stimulation of active creative work, disclosure of worker’s personal potential. On the one hand, it was turned to economic and technical modernization on the basis of the State Plan of the Electrification of Russia; on the other, it was relied on "diligent farmer". In the 1930-1980s the technical and economic approach was dominating. In the 1990-2010s the market approach was widely extended. According to the latter, the development of the national economy should be executed depending on the law of demand and supply. In Russia the realization of the market economy based on demand and supply was reduced to development of exclusively highly profitable business. In the article the author uses the methods of historical knowledge, analysis and comparison and provides suggestions on solving problems of spatial planning and urban development. Special emphasis is placed on the Soviet experience of the 1920s, when the market relations have not been completely destroyed.
Ramana, M.V.; Ahmad, Ali
2016-01-01
Jordan plans to import two conventional gigawatt scale nuclear reactors from Russia that are expensive and too large for Jordan's current electricity grid. Jordan efforts to establish nuclear power might become easier in some ways if the country were to construct Small Modular Reactors, which might be better suited to Jordan's financial capabilities and its smaller electrical grid capacity. But, the SMR option raises new problems, including locating sites for multiple reactors, finding water to cool these reactors, and the higher cost of electricity generation. Jordan's decision has important implications for its energy planning as well as for the market for SMRs. - Highlights: •Jordan is planning to purchase two large reactors from Russia. •Large reactors would be inappropriate to Jordan's small electricity grid. •Small modular reactors would be more appropriate to Jordan's grid, but have problems. •The market for small modular reactors will be smaller than often projected. •Jordan should consider the financial impact of building a large nuclear reactor.
Modeling and solving a large-scale generation expansion planning problem under uncertainty
Jin, Shan; Ryan, Sarah M. [Iowa State University, Department of Industrial and Manufacturing Systems Engineering, Ames (United States); Watson, Jean-Paul [Sandia National Laboratories, Discrete Math and Complex Systems Department, Albuquerque (United States); Woodruff, David L. [University of California Davis, Graduate School of Management, Davis (United States)
2011-11-15
We formulate a generation expansion planning problem to determine the type and quantity of power plants to be constructed over each year of an extended planning horizon, considering uncertainty regarding future demand and fuel prices. Our model is expressed as a two-stage stochastic mixed-integer program, which we use to compute solutions independently minimizing the expected cost and the Conditional Value-at-Risk; i.e., the risk of significantly larger-than-expected operational costs. We introduce stochastic process models to capture demand and fuel price uncertainty, which are in turn used to generate trees that accurately represent the uncertainty space. Using a realistic problem instance based on the Midwest US, we explore two fundamental, unexplored issues that arise when solving any stochastic generation expansion model. First, we introduce and discuss the use of an algorithm for computing confidence intervals on obtained solution costs, to account for the fact that a finite sample of scenarios was used to obtain a particular solution. Second, we analyze the nature of solutions obtained under different parameterizations of this method, to assess whether the recommended solutions themselves are invariant to changes in costs. The issues are critical for decision makers who seek truly robust recommendations for generation expansion planning. (orig.)
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...
Hansen, Anders Dohn; Clausen, Jens
2008-01-01
In this paper, we present The Slab Yard Planning and Crane Scheduling Problem. The problem has its origin in steel production facilities with a large throughput. A slab yard is used as a buffer for slabs that are needed in the upcoming production. Slabs are transported by cranes and the problem...... considered here, is concerned with the generation of schedules for these. The problem is decomposed and modeled in two parts, namely a planning problem and a scheduling problem. In the planning problem a set of crane operations is created to take the yard from its current state to a desired goal state...... schedule for the cranes is generated, where each operation is assigned to a crane and is given a specific time of initiation. For both models, a thorough description of the modeling details is given along with a specification of objective criteria. Variants of the models are presented as well. Preliminary...
Anticipating students' reasoning and planning prompts in structured problem-solving lessons
Vale, Colleen; Widjaja, Wanty; Doig, Brian; Groves, Susie
2018-02-01
Structured problem-solving lessons are used to explore mathematical concepts such as pattern and relationships in early algebra, and regularly used in Japanese Lesson Study research lessons. However, enactment of structured problem-solving lessons which involves detailed planning, anticipation of student solutions and orchestration of whole-class discussion of solutions is an ongoing challenge for many teachers. Moreover, primary teachers have limited experience in teaching early algebra or mathematical reasoning actions such as generalising. In this study, the critical factors of enacting the structured problem-solving lessons used in Japanese Lesson Study to elicit and develop primary students' capacity to generalise are explored. Teachers from three primary schools participated in two Japanese Lesson Study teams for this study. The lesson plans and video recordings of teaching and post-lesson discussion of the two research lessons along with students' responses and learning are compared to identify critical factors. The anticipation of students' reasoning together with preparation of supporting and challenging prompts was critical for scaffolding students' capacity to grasp and communicate generality.
Solving the Students’ Problems in Writing Argumentative Essay Through the Provision of Planning
Lestari Setyowati
2017-10-01
Full Text Available Most Indonesian students who are learning English often consider writing as not only the most difficult skill to master, but also a demanding activity. To help them cope these problems, the application of planning in the writing process seems to be a solution. This study attempts to find out howdifferent planning formats can improve EFL students’ writing performance in argumentative essays. The subjects of the studywere the fourth semester students taking essay writing class. The research was conducted from May to June 2015, consisting of three cycles in Classroom Action Research design by using different planning types, namely rough drafting and outlining strategy in which each cycle consisted of two meetings.The students’ compositions were measured by using primary trait scoring rubric for argumentative essay. The result of the study shows that the provision of planning is effective to improve the students’ performance in writing argumentative essay. The effectiveness of different types planningdepends on the students’ preference of which to use.
Two efficient heuristics to solve the integrated load distribution and production planning problem
Gajpal, Yuvraj; Nourelfath, Mustapha
2015-01-01
This paper considers a multi-period production system where a set of machines are arranged in parallel. The machines are unreliable and the failure rate of machine depends on the load assigned to the machine. The expected production rate of the system is considered to be a non-monotonic function of its load. Because of the machine failure rate, the total production output depends on the combination of loads assigned to different machines. We consider the integration of load distribution decisions with production planning decision. The product demands are considered to be known in advance. The objective is to minimize the sum of holding costs, backorder costs, production costs, setup costs, capacity change costs and unused capacity costs while satisfying the demand over specified time horizon. The constraint is not to exceed available repair resources required to repair the machine breakdown. The paper develops two heuristics to solve the integrated load distribution and production planning problem. The first heuristic consists of a three-phase approach, while the second one is based on tabu search metaheuristic. The efficiency of the proposed heuristics is tested through the randomly generated problem instances. - Highlights: • The expected performance of the system is a non-monotonic function of its load. • We consider the integration of load distribution and production planning decisions. • The paper proposes three phase and tabu search based heuristics to solve the problem. • Lower bound has been developed for checking the effectiveness of the heuristics. • The efficiency of the heuristic is tested through randomly generated instances.
Yan Sun
2015-09-01
Full Text Available Purpose: The purpose of study is to solve the multi-modal transportation routing planning problem that aims to select an optimal route to move a consignment of goods from its origin to its destination through the multi-modal transportation network. And the optimization is from two viewpoints including cost and time. Design/methodology/approach: In this study, a bi-objective mixed integer linear programming model is proposed to optimize the multi-modal transportation routing planning problem. Minimizing the total transportation cost and the total transportation time are set as the optimization objectives of the model. In order to balance the benefit between the two objectives, Pareto optimality is utilized to solve the model by gaining its Pareto frontier. The Pareto frontier of the model can provide the multi-modal transportation operator (MTO and customers with better decision support and it is gained by the normalized normal constraint method. Then, an experimental case study is designed to verify the feasibility of the model and Pareto optimality by using the mathematical programming software Lingo. Finally, the sensitivity analysis of the demand and supply in the multi-modal transportation organization is performed based on the designed case. Findings: The calculation results indicate that the proposed model and Pareto optimality have good performance in dealing with the bi-objective optimization. The sensitivity analysis also shows the influence of the variation of the demand and supply on the multi-modal transportation organization clearly. Therefore, this method can be further promoted to the practice. Originality/value: A bi-objective mixed integer linear programming model is proposed to optimize the multi-modal transportation routing planning problem. The Pareto frontier based sensitivity analysis of the demand and supply in the multi-modal transportation organization is performed based on the designed case.
Chang, Pyung Hun; Park, Ki Cheol; Park, Suk Ho [Korea Advanced Institute of Science and Technology, Taejon (Korea)
1999-04-01
This project focuses on the development of the control system for a teleoperated redundant manipulator, which performs many tasks dexterously, while avoiding obstacles, instead of human workers in the extreme situations like nuclear power plants. To this end, four consecutive research works have been performed. First, two new methods for global path-planning have been developed to inspect the global behavior of the redundant manipulator. Second, characteristics of optimal solutions(COS) under inequality constraints have been analyzed and, using the COS, how to greatly enhance the conventional redundancy resolution methods in terms of performance and repeatability has also been proposed. Third, an effective control method for a redundant manipulator has been developed, which incorporates all kinds of physical limits into practical inequality constraints and is computationally efficient for real-time purposes. Finally, using this control method as the controller of the slave redundant manipulator and developing a master manipulator, the inertial torque and gravitation torque of which are negligible, a force-reflected teleoperation control system has been developed. Through the teleoperation control system, human operator can accurately control the position and the force of the end-effector of the slave manipulator while feeling the interaction force between the slave and the workpiece. In addition, the slave redundant manipulator autonomously can control the impedance and can optimize a given performance measure while avoiding physical limits such as joint angle limits and obstacles. 49 refs., 43 figs., 10 tabs. (Author)
A NEPA compliance strategy plan for providing programmatic coverage to agency problems
Eccleston, C.H.
1994-04-01
The National Environmental Policy Act (NEPA) of 1969, requires that all federal actions be reviewed before making a final decision to pursue a proposed action or one of its reasonable alternatives. The NEPA process is expected to begin early in the planning process. This paper discusses an approach for providing efficient and comprehensive NEPA coverage to large-scale programs. Particular emphasis has been given to determining bottlenecks and developing workarounds to such problems. Specifically, the strategy is designed to meet four specific goals: (1) provide comprehensive coverage, (2) reduce compliance cost/time, (3) prevent project delays, and (4) reduce document obsolescence
Hines, Walter G.
1973-01-01
The San Francisco Bay region has suffered adverse environmental effects related to the discharge of municipal-, industrial-, and agricultural- wastewater and storm-water runoff. Specific pollutional properties of theses discharges are not well understood in all cases although the toxic materials and aquatic-plant nutrients (biostimulants) found in municipal and industrial waterwater are considered to be a major cause of regional water-quality problems. Other water-quality problems in the region are commonly attributed to pesticides found in agricultural wastewater and potentially pathogenic bacteria in municipal-wastewater discharges and in storm-water runoff. The geographical distribution and magnitude of wastewater discharges in the bay region, particularly those from municipalities and industries, is largely a function of population, economic growth, and urban development. As might be expected, the total volume of wastewater has increased in a trend paralleling this growth and development. More significant, perhaps, is the fact that the total volume parameters such as BOD (biochemical oxygen demand), biostimulant concentrations, and toxicity, has increased despite large expenditures on new and improved municipal- and industrial-wastewater-treatment plants. Also, pollutant loadings from other major source, such as agriculture and storm-water runoff, have increased. At the time of writing (1972), many Federal, State, regional, and local agencies are engaged in a comprehensive wastewater-management-planning effort for the entire bay region. Initial objectives of this planning effort are: (1) the consolidation and coordination of loosely integrated wastewater-management facilities and (2) the elimination of wastewater discharges to ecologically sensitive areas, such as fresh-water streams and shallow extremities of San Francisco Bay. There has been some investigation of potential long-range wastewater-management alternatives based upon disposal in deep water in the
Fuzzy bicriteria multi-index transportation problems for coal allocation planning of Taipower
Tzeng, G.-H.; Teodorvic, D.; Hwang, M.-J.
1996-01-01
Taipower, the official electricity authority of Taiwan, encounters several difficulties in planning annual coal purchase and allocation schedule, e.g. with multiple sources, multiple destinations, multiple coal types, different shipping vessels, and even an uncertain demand and supply. In this study, these concerns are formulated as a fuzzy bicriteria multi-index transportation problem. Furthermore, an effective and interactive algorithm is proposed which combines reducing index method and interactive fuzzy multi-objective linear programming technique to cope with a complicated problem which may be prevalent in other industries. Results obtained in this study clearly demonstrate that this model can not only satisfy more of the actual requirements of the integral system but also offer more information to the decision makers (DMs) for reference in favor of exalting decision making quality. 34 refs., 4 figs., 4 tabs
Tabrizi, Babak H.; Ghaderi, Seyed Farid
2016-09-01
Simultaneous planning of project scheduling and material procurement can improve the project execution costs. Hence, the issue has been addressed here by a mixed-integer programming model. The proposed model facilitates the procurement decisions by accounting for a number of suppliers offering a distinctive discount formula from which to purchase the required materials. It is aimed at developing schedules with the best net present value regarding the obtained benefit and costs of the project execution. A genetic algorithm is applied to deal with the problem, in addition to a modified version equipped with a variable neighbourhood search. The underlying factors of the solution methods are calibrated by the Taguchi method to obtain robust solutions. The performance of the aforementioned methods is compared for different problem sizes, in which the utilized local search proved efficient. Finally, a sensitivity analysis is carried out to check the effect of inflation on the objective function value.
A PostgreSQL/PostGIS Implementation for the Sightseeing Tour Planning Problem
Ardiansyah .
2013-04-01
Full Text Available This article discusses a procedure for finding the best multi stops route for sightseeing tour through a road network. The procedure involves building a database containing nodes and road network in PostgreSQL, calculating the shortest distance between a pair of nodes using pgDijkstra module, and solving the tour problem using a function written in PL/pgSQL. The function was developed based on the Nearest Insertion Algorithm for solving the Travelling Salesman Problem. The algorithm inserts a sightseeing attraction (node at the best position in the existing route, which is between a pair of nodes that yields the minimum difference between the total tour time before and after the new node was inserted. The test result shows that the function can solve the problem within acceptable runtime for web application for total destination nodes of 22. It is concluded that the whole procedure was suitable for developing Web GIS application that solve the sightseeing tour planning problem.
Yu Zhou
2017-01-01
Full Text Available The train-set circulation plan problem (TCPP belongs to the rolling stock scheduling (RSS problem and is similar to the aircraft routing problem (ARP in airline operations and the vehicle routing problem (VRP in the logistics field. However, TCPP involves additional complexity due to the maintenance constraint of train-sets: train-sets must conduct maintenance tasks after running for a certain time and distance. The TCPP is nondeterministic polynomial hard (NP-hard. There is no available algorithm that can obtain the optimal global solution, and many factors such as the utilization mode and the maintenance mode impact the solution of the TCPP. This paper proposes a train-set circulation optimization model to minimize the total connection time and maintenance costs and describes the design of an efficient multiple-population genetic algorithm (MPGA to solve this model. A realistic high-speed railway (HSR case is selected to verify our model and algorithm, and, then, a comparison of different algorithms is carried out. Furthermore, a new maintenance mode is proposed, and related implementation requirements are discussed.
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...
Problems of heat sources modeling on stage of isolated power systems expansion planning
Malenkov, A.V.; Reshetnikova, L.N.; Sergeev, Yu.A.
1998-01-01
It is necessary to use computer codes for evaluation of possible applications and role of nuclear district heating plants in the local self-balancing power and heating systems, which are to be located in the remote isolated and hardly accessible regions in the Far North of Russia. Key factors in determining system configurations and its performances are: (1) interdependency of electricity, heat and fuel supply; (2) long distance between energy consumer centres (from several tens up to some hundred kilometers); and (3) difficulty in export and import of the electricity, especially the fuel in and from neighbouring and remote regions. The problem to challenge is to work out an optimum expansion plan of the local electricity and heat supply system. The ENPEP (ENergy and Power Evaluation Program) software package, which was developed by IAEA together with the USA Argonne National Laboratory, was chosen for this purpose. The Chaun-Bilibino power system (CBPS), an isolated power system in far North-East region of Russia, was selected as the first case of the ENPEP study. ENPEP allows a complex approach in the system expansion optimization planning in the time frame of planning period of up to 30 years. The key ENPEP module, ELECTRIC, considers electricity as the only product. The cogeneration part (heat production) must be considered outside the ELECTRIC model and then the results to be transfer ed to ELECTRIC. The ENPEP study on the Chaun-Bilibino isolated power system has shown that the modelling of the heat supply sources in ENPEP is not a trivial problem. It is very important and difficult to correctly represent specific features of cogeneration process at the same time. (author)
Abrams, Gene; Siles Molina, Mercedes
2017-01-01
This book offers a comprehensive introduction by three of the leading experts in the field, collecting fundamental results and open problems in a single volume. Since Leavitt path algebras were first defined in 2005, interest in these algebras has grown substantially, with ring theorists as well as researchers working in graph C*-algebras, group theory and symbolic dynamics attracted to the topic. Providing a historical perspective on the subject, the authors review existing arguments, establish new results, and outline the major themes and ring-theoretic concepts, such as the ideal structure, Z-grading and the close link between Leavitt path algebras and graph C*-algebras. The book also presents key lines of current research, including the Algebraic Kirchberg Phillips Question, various additional classification questions, and connections to noncommutative algebraic geometry. Leavitt Path Algebras will appeal to graduate students and researchers working in the field and related areas, such as C*-algebras and...
Past the hype. Climate change as a structural spatial planning problem
2007-01-01
Adaptation to climate change is not only a physical or spatial issue, but also a social and political-administrative issue. This advice especially focuses on the following aspects: How is the problem tackled from an administrative viewpoint. Which issues receive sufficient focus and which parts of the problem remain underexposed? How is the tuning among and within managing bodies? Who feels responsible? How is society involved in the issue? The central question is how the Dutch government can best anticipate the spatial consequences of climate change. Chapter 2 provides a short overview of certainties and uncertainties of the climate system and the spatial consequences of climate change for the Netherlands. The societal perception of the climate change problem is described in Chapter 3. Chapter 4 addresses administrative aspects. The recommendations of the VROM council (the Netherlands Council of Housing, Spatial Planning and the Environment) are provided in Chapter 5, in which the elements of a spatial strategy are discussed. The VROM council started this advice trajectory with an extensive literature analysis of the climate system and current knowledge of climate change. Next the implementation of this knowledge in policy is examined. In that process, the authors were confronted with a number of fallacies (thinking errors) that could hamper a sensible approach to climate change. (mk) [nl
St-Pierre, Renée A; Temcheff, Caroline E; Derevensky, Jeffrey L; Gupta, Rina
2015-12-01
Given its serious implications for psychological and socio-emotional health, the prevention of problem gambling among adolescents is increasingly acknowledged as an area requiring attention. The theory of planned behavior (TPB) is a well-established model of behavior change that has been studied in the development and evaluation of primary preventive interventions aimed at modifying cognitions and behavior. However, the utility of the TPB has yet to be explored as a framework for the development of adolescent problem gambling prevention initiatives. This paper first examines the existing empirical literature addressing the effectiveness of school-based primary prevention programs for adolescent gambling. Given the limitations of existing programs, we then present a conceptual framework for the integration of the TPB in the development of effective problem gambling preventive interventions. The paper describes the TPB, demonstrates how the framework has been applied to gambling behavior, and reviews the strengths and limitations of the model for the design of primary prevention initiatives targeting adolescent risk and addictive behaviors, including adolescent gambling.
Welding Robot Collision-Free Path Optimization
Xuewu Wang
2017-02-01
Full Text Available Reasonable welding path has a significant impact on welding efficiency, and a collision-free path should be considered first in the process of welding robot path planning. The shortest path length is considered as an optimization objective, and obstacle avoidance is considered as the constraint condition in this paper. First, a grid method is used as a modeling method after the optimization objective is analyzed. For local collision-free path planning, an ant colony algorithm is selected as the search strategy. Then, to overcome the shortcomings of the ant colony algorithm, a secondary optimization is presented to improve the optimization performance. Finally, the particle swarm optimization algorithm is used to realize global path planning. Simulation results show that the desired welding path can be obtained based on the optimization strategy.
Review. Supporting problem structuring with computer-based tools in participatory forest planning
Hujala, T.; Khadka, C.; Wolfslehner, B.; Vacik, H.
2013-09-01
Aim of study: This review presents the state-of-art of using computerized techniques for problem structuring (PS) in participatory forest planning. Frequency and modes of using different computerized tool types and their contribution for planning processes as well as critical observations are described, followed by recommendations on how to better integrate PS with the use of forest decision support systems. Area of study: The reviewed research cases are from Asia, Europe, North-America, Africa and Australia. Material and methods: Via Scopus search and screening of abstracts, 32 research articles from years 2002-2011 were selected for review. Explicit and implicit evidence of using computerized tools for PS was recorded and assessed with content-driven qualitative analysis. Main results: GIS and forest-specific simulation tools were the most prevalent software types whereas cognitive modelling software and spreadsheet and calculation tools were less frequently used, followed by multi-criteria and interactive tools. The typical use type was to provide outputs of simulation–optimization or spatial analysis to negotiation situations or to compile summaries or illustrations afterwards; using software during group negotiation to foster interaction was observed only in a few cases. Research highlights: Expertise in both decision support systems and group learning is needed to better integrate PS and computerized decision analysis. From the knowledge management perspective, it is recommended to consider how the results of PS —e.g. conceptual models— could be stored into a problem perception database, and how PS and decision making could be streamlined by retrievals from such systems. (Author)
Review. Supporting problem structuring with computer-based tools in participatory forest planning
T. Hujala
2013-07-01
Full Text Available Aim of study: This review presents the state-of-art of using computerized techniques for problem structuring (PS in participatory forest planning. Frequency and modes of using different computerized tool types and their contribution for planning processes as well as critical observations are described, followed by recommendations on how to better integrate PS with the use of forest decision support systems.Area of study: The reviewed research cases are from Asia, Europe, North-America, Africa and Australia.Materials and methods: Via Scopus search and screening of abstracts, 32 research articles from years 2002–2011 were selected for review. Explicit and implicit evidence of using computerized tools for PS was recorded and assessed with content-driven qualitative analysis.Main results: GIS and forest-specific simulation tools were the most prevalent software types whereas cognitive modelling software and spreadsheet and calculation tools were less frequently used, followed by multi-criteria and interactive tools. The typical use type was to provide outputs of simulation–optimization or spatial analysis to negotiation situations or to compile summaries or illustrations afterwards; using software during group negotiation to foster interaction was observed only in a few cases.Research highlights: Expertise in both decision support systems and group learning is needed to better integrate PS and computerized decision analysis. From the knowledge management perspective, it is recommended to consider how the results of PS – e.g. conceptual models – could be stored into a problem perception database, and how PS and decision making could be streamlined by retrievals from such systems.Keywords: facilitated modeling; group negotiation; knowledge management; natural resource management; PSM; soft OR; stakeholders.
Extension of portfolio theory application to energy planning problem – The Italian case
Arnesano, M.; Carlucci, A.P.; Laforgia, D.
2012-01-01
Energy procurement is a necessity which needs a deep study of both the demand and the generation sources, referred to consumers territorial localization. The study presented in this paper extends and consolidate the Shimon Awerbuch’s study on portfolio theory applied to the energy planning, in order to define a broad generating mix which optimizes one or more objective functions defined for a determined contest. For this purpose the computation model was specialized in energy generation problem and extended with the addition of new cost-risk settings, like renewable energy availability, and Black–Litterman model, which extends Markowitz theory. Energy planning was then contextualized to the territory: the introduction of geographic and climatic features allows to plan energy infrastructures on both global and local (regional, provincial, municipal) scale. The result is an efficient decision making tool to drive the investment on typical energy policy assets. In general the tool allows to analyze several scenarios in support of renewable energy sources, environmental sustainability, costs and risks reduction. In this paper the model was applied to the energy generation in Italy, and the analysis was done: on the actual energy mix; assuming the use of nuclear technology; assuming the verisimilar improvement of several technologies in the future. -- Highlights: ► Extension and consolidation of Shimon Awerbuch’s studies. ► Introduction of aspects connected to realization and utilization of power plants. ► Application of the model on a national, provincial, municipal scale. ► Modification of Energy Portfolio based on subjective previsions (Black–Litterman).
María-Teresa Sebastiá-Frasquet
2014-03-01
Full Text Available The policies that define the use and management of wetlands in Spain have undergone tremendous changes in recent decades. During the period of 1950–1980, Land Reform Plans promoted filling and draining of these areas for agricultural use. In 1986, with the incorporation of Spain to the European Union (EU, there was a sudden change of direction in these policies, which, thereafter, pursued restoring and protecting these ecosystems. This change, combined with increasing urban development and infrastructure pressures (e.g., roads, golf courses, etc., creates a conflict of uses which complicates the management of these ecosystems by local governments. This study analyzes the effectiveness of policies and management tools of important coastal wetlands at the local scale in the Valencian Community (Western Mediterranean Sea using a strengths-weaknesses-opportunities-threats (SWOT methodology. A supra-municipal model of environmental planning is proposed to enable consistent management at a regional scale. This model enhances local government’s effectiveness and it can be applied in other areas with similar problems.
The problem involving OPMEs and the health plans contracts: outline and analysis of the issue
MARTINS, Paulo Roberto do Nascimento
2016-06-01
Full Text Available This paper has as its scope to introduce and analyze some of most polemic issues involving the indications of OPMEs within the health plans contracts. During the text, are exhibited normative elements related to this context, as well as some judicial decisions concerning this matter, aiming to defend, with reasonable grounds, that the indication of the patient’s doctor, when choosing prostheses and orthoses, cannot be taken as the unique nor necessarily the best opinion, given the existence of other interests, beyond the patient’s health, that are often in stake as well. At the end, it is explained that, in light of the currently existing regulation in Brazil, in the context of the supplementary health system, to the patient’s doctor is given the authority only to indicate the characteristics of the materials needed, leaving it to the health plans Operators the choice of the brand and the manufacturer. As long as the courts deny these rules, this serious problem will not be solved.
Regional action plan handling of social welfare problem in nganjuk regency
Zain, IM; Utami, WS; Setyawan, KG
2018-01-01
Local action plans are expected to ensure a social protection for vulnerable and disadvantaged groups or PMKS. The method used in this research is by primary survey and secondary survey. The condition of the people who still belong to PMKS requires the state to come to the community to solve the problems faced. Stakeholders should be involved to handle PMKS. The activities presented should also receive periodic monitoring and evaluation so that there is progress reporting at any time. Implementable poverty reduction strategies and policies are social protection strategies, opportunity expansion strategies, resource capacity building strategies, community empowerment strategies and partnership strategies. The flow of PMKS is the validation and updating of data, the fulfillment of the basic needs of the PMKS family, the development of PMKS human resources, the improvement of the quality of life for poor families, the institutions of poverty alleviation stakeholders and the unemployed at the base level. The Regional Action Plan (RAP) is prepared as a reference in the context of carrying out PMKS mitigation which is expected to serve as a guide for managers and program implementers with relevant agencies that are conducted jointly and continuously for the period of time specified.
The dose-volume constraint satisfaction problem for inverse treatment planning with field segments
Michalski, Darek; Xiao, Ying; Censor, Yair; Galvin, James M
2004-01-01
The prescribed goals of radiation treatment planning are often expressed in terms of dose-volume constraints. We present a novel formulation of a dose-volume constraint satisfaction search for the discretized radiation therapy model. This approach does not rely on any explicit cost function. Inverse treatment planning uses the aperture-based approach with predefined, according to geometric rules, segmental fields. The solver utilizes the simultaneous version of the cyclic subgradient projection algorithm. This is a deterministic iterative method designed for solving the convex feasibility problems. A prescription is expressed with the set of inequalities imposed on the dose at the voxel resolution. Additional constraint functions control the compliance with selected points of the expected cumulative dose-volume histograms. The performance of this method is tested on prostate and head-and-neck cases. The relationships with other models and algorithms of similar conceptual origin are discussed. The demonstrated advantages of the method are: the equivalence of the algorithmic and prescription parameters, the intuitive setup of free parameters, and the improved speed of the method as compared to similar iterative as well as other techniques. The technique reported here will deliver approximate solutions for inconsistent prescriptions
Pegler, Klaus
1977-01-01
Gives a detailed ESL (English as a second language) class-hour plan for using a BBC radio news program on vandalism as a social problem. Teaching goals, teaching materials and methodology are discussed. The working texts are appended; the news tests are available free from the author. (Text is in German.) (IFS/WGA)
Hagger, Martin; Chan, Dervin K. C.; Protogerou, Cleo; Chatzisarantis, Nikos L. D.
2016-01-01
Objective Synthesizing research on social cognitive theories applied to health behavior is an important step in the development of an evidence base of psychological factors as targets for effective behavioral interventions. However, few meta-analyses of research on social cognitive theories in health contexts have conducted simultaneous tests of theoretically-stipulated pattern effects using path analysis. We argue that conducting path analyses of meta-analytic effects among constructs fr...
The Defined Benefit Pension Plan System: Financial Problems and Policy Responses
Lang, Joel
2004-01-01
.... This thesis examines the challenges facing the DB pension plan system, beginning with an overview of the DB plan system, a review of the different plan types, the benefits received, and funding rules...
Funabiki, T. (Ministry of Construction, Tokyo (Japan))
1992-08-06
The present city plans are questioned on the formation of a good city environment, improvement of mansion/building supply, due to the new city problems on the Tokyo concentration and re-increase of the land value recently. Based on the discussion of the central city planning council, various improvement of the system were made by government. As a structure plan of the city, the green area plan that the balance between the urban land use and the national land use is distributed, must be included. As the problem of the green area plan on the system of city plan, this paper explained the distinguish between city area and city adjustment area, the green master plan about the green area preservation in long time, the green area system corresponded to the policy for realizing the plan of preserving the green area mainly, and the park work and green area policy corresponded to the policy for realizing the plan of creating the green area.
Ausaf, Muhammad Farhan; Gao, Liang; Li, Xinyu
2015-12-01
For increasing the overall performance of modern manufacturing systems, effective integration of process planning and scheduling functions has been an important area of consideration among researchers. Owing to the complexity of handling process planning and scheduling simultaneously, most of the research work has been limited to solving the integrated process planning and scheduling (IPPS) problem for a single objective function. As there are many conflicting objectives when dealing with process planning and scheduling, real world problems cannot be fully captured considering only a single objective for optimization. Therefore considering multi-objective IPPS (MOIPPS) problem is inevitable. Unfortunately, only a handful of research papers are available on solving MOIPPS problem. In this paper, an optimization algorithm for solving MOIPPS problem is presented. The proposed algorithm uses a set of dispatching rules coupled with priority assignment to optimize the IPPS problem for various objectives like makespan, total machine load, total tardiness, etc. A fixed sized external archive coupled with a crowding distance mechanism is used to store and maintain the non-dominated solutions. To compare the results with other algorithms, a C-matric based method has been used. Instances from four recent papers have been solved to demonstrate the effectiveness of the proposed algorithm. The experimental results show that the proposed method is an efficient approach for solving the MOIPPS problem.
Partial Path Column Generation for the ESPPRC
Jepsen, Mads Kehlet; Petersen, Bjørn
This talk introduces a decomposition of the Elementary Shortest Path Problem with Resource Constraints(ESPPRC), where the path is combined by smaller sub paths. We show computational result by comparing different approaches for the decomposition and compare the best of these with existing algorit...
Todorov, A K; Arnaudov, B K; Brankova, B A; Gyuleva, B I; Zakhariyev, G K
1977-01-01
The system for planning for the development of coal mines is a complex of interrelated plan optimization, plan calculation and supporting (accounting-analytical and standards) tasks. An important point in this complex is held by the plan optimization tasks. The questions about the synthesis and the structural peculiarities of the system, the essence and machine realization of the tasks are examined.
Bijelić Branislav
2017-01-01
Full Text Available The implementation of spatial plans in the Republic of Srpska is certainly the weakest phase of the process of spatial planning in this entity. It is particularly evident in the case of the Spatial Plan of the Republic of Srpska until 2015 which is the highest strategic spatial planning document in the Republic of Srpska. More precisely, the implementation of spatial plans has been defined as the carrying out of spatial planning documents, i.e. planning propositions as defined in the spatial plans. For the purpose of this paper, a quantitative analysis of the implementation of the planning propositions envisioned by this document has been carried out. The difference between what was planned and what was implemented at the end of the planning period (ex-post evaluation of planning decisions is presented in this paper. The weighting factor is defined for each thematic field and planning proposition, where the main criterion for determining the weighting factor is the share of the planning proposition and thematic field in the estimated total costs of the plan (financial criterion. The paper has also tackled the issue of the implementation of the Spatial Plan of Bosnia and Herzegovina for the period 1981 - 2000, as well as of the Spatial Plan of the Republic of Srpska 1996 - 2001 - Phased Plan for the period 1996 - 2001, as the previous strategic spatial planning documents of the highest rank covering the area of the Republic of Srpska. The research results have proven primary hypothesis of the paper that the level of the implementation of Spatial Plan of the Republic of Srpska until 2015 is less than 10%.
Zhou Kaiyi; Sheate, William R.
2011-01-01
Since the Law of the People's Republic of China on Environmental Impact Assessment was enacted in 2003 and Huanfa 2004 No. 98 was released in 2004, Strategic Environmental Assessment (SEA) has been officially being implemented in the expressway infrastructure planning field in China. Through scrutinizing two SEA application cases of China's provincial level expressway infrastructure (PLEI) network plans, it is found that current SEA practice in expressway infrastructure planning field has a number of problems including: SEA practitioners do not fully understand the objective of SEA; its potential contributions to strategic planning and decision-making is extremely limited; the employed application procedure and prediction and assessment techniques are too simple to bring objective, unbiased and scientific results; and no alternative options are considered. All these problems directly lead to poor quality SEA and consequently weaken SEA's effectiveness.
Jin Huang
2017-09-01
Full Text Available Process planning is an important function in a manufacturing system; it specifies the manufacturing requirements and details for the shop floor to convert a part from raw material to the finished form. However, considering only economical criterion with technological constraints is not enough in sustainable manufacturing practice; formerly, criteria about low carbon emission awareness have seldom been taken into account in process planning optimization. In this paper, a mathematical model that considers both machining costs reduction as well as carbon emission reduction is established for the process planning problem. However, due to various flexibilities together with complex precedence constraints between operations, the process planning problem is a non-deterministic polynomial-time (NP hard problem. Aiming at the distinctive feature of the multi-objectives process planning optimization, we then developed a hybrid non-dominated sorting genetic algorithm (NSGA-II to tackle this problem. A local search method that considers both the total cost criterion and the carbon emission criterion are introduced into the proposed algorithm to avoid being trapped into local optima. Moreover, the technique for order preference by similarity to an ideal solution (TOPSIS method is also adopted to determine the best solution from the Pareto front. Experiments have been conducted using Kim’s benchmark. Computational results show that process plan schemes with low carbon emission can be captured, and, more importantly, the proposed hybrid NSGA-II algorithm can obtain more promising optimal Pareto front than the plain NSGA-II algorithm. Meanwhile, according to the computational results of Kim’s benchmark, we find that both of the total machining cost and carbon emission are roughly proportional to the number of operations, and a process plan with less operation may be more satisfactory. This study will draw references for the further research on green
Trindade, B. C.; Reed, P. M.
2017-12-01
The growing access and reduced cost for computing power in recent years has promoted rapid development and application of multi-objective water supply portfolio planning. As this trend continues there is a pressing need for flexible risk-based simulation frameworks and improved algorithm benchmarking for emerging classes of water supply planning and management problems. This work contributes the Water Utilities Management and Planning (WUMP) model: a generalizable and open source simulation framework designed to capture how water utilities can minimize operational and financial risks by regionally coordinating planning and management choices, i.e. making more efficient and coordinated use of restrictions, water transfers and financial hedging combined with possible construction of new infrastructure. We introduce the WUMP simulation framework as part of a new multi-objective benchmark problem for planning and management of regionally integrated water utility companies. In this problem, a group of fictitious water utilities seek to balance the use of the mentioned reliability driven actions (e.g., restrictions, water transfers and infrastructure pathways) and their inherent financial risks. Several traits of this problem make it ideal for a benchmark problem, namely the presence of (1) strong non-linearities and discontinuities in the Pareto front caused by the step-wise nature of the decision making formulation and by the abrupt addition of storage through infrastructure construction, (2) noise due to the stochastic nature of the streamflows and water demands, and (3) non-separability resulting from the cooperative formulation of the problem, in which decisions made by stakeholder may substantially impact others. Both the open source WUMP simulation framework and its demonstration in a challenging benchmarking example hold value for promoting broader advances in urban water supply portfolio planning for regions confronting change.
Software for Project-Based Learning of Robot Motion Planning
Moll, Mark; Bordeaux, Janice; Kavraki, Lydia E.
2013-01-01
Motion planning is a core problem in robotics concerned with finding feasible paths for a given robot. Motion planning algorithms perform a search in the high-dimensional continuous space of robot configurations and exemplify many of the core algorithmic concepts of search algorithms and associated data structures. Motion planning algorithms can…
Arling V.
2015-09-01
Full Text Available Interdisciplinary skills gain increasing importance in university and professional contexts. To support these interdisciplinary skills, problem-based learning (PBL is regularly used in a course for biomedical education. In this study, we investigated whether enhancing consciousness for planning processes can support the effectiveness of PBL concepts in an intervention-control group design. Results indicated clear evidence for this: planning skills were associated with better PBL performance. Concluding, self-reflection of planning skills is useful to increase outcome performance of students in PBL courses.
Local Management as a Proposal for the Solution of Urban Planning Common Problems in Latin America
Verónica Sánchez García
2015-09-01
Full Text Available The scene of the majority of Latin American cities is hopeless due the crisis faced by this part of the world. The decisive factor was globalization because it forced an economical restructuring and the implementation of new ways of production. Cities had to reorganize to deal with and adapt to this system through “global cities.” This way, it was possible to strengthen certain groups or population areas while ignoring others. This generated and emphasized poverty, which, at the same time, created social and environmental segregation, insecurity, mobility, lack of housing and utilities, overspend, waste of materials and human resources, as well as other institutional difficulties. These were a constant and limited the equitable access to social opportunities.For this reason, every urban planning and prediction system should take into account realistic circumstances that foster solidarity, participation, consensus, and sustainability as the central concept of the strategy to implement. This is known as “local management.” To manage a city implies working together with public, private, and social sectors in order to solve everyday problems efficiently and wisely. This way, it is possible to prevent and solve the difficulties faced by the community while searching for a common good and the recovery of its citizenship.
In April 2018, EPA released the draft IRIS Assessment Plan for Ammonia and Ammonium Salts Noncancer Oral. An IRIS Assessment Plan (IAP) communicates to the public the plan for assessing each individual chemical and includes summary information on the IRIS Program’s sco...
Ehsan Zakeri
Full Text Available Abstract In this research, generation of a short and smooth path in three-dimensional space with obstacles for guiding an Unmanned Underwater Vehicle (UUV without collision is investigated. This is done by utilizing spline technique, in which the spline control points positions are determined by Imperialist Competitive Algorithm (ICA in three-dimensional space such that the shortest possible path from the starting point to the target point without colliding with obstacles is achieved. Furthermore, for guiding the UUV in the generated path, an Interval Type-2 Fuzzy Logic Controller (IT2FLC, the coefficients of which are optimized by considering an objective function that includes quadratic terms of the input forces and state error of the system, is used. Selecting such objective function reduces the control error and also the force applied to the UUV, which consequently leads to reduction of energy consumption. Therefore, by using a special method, desired signals of UUV state are obtained from generated three-dimensional optimal path such that tracking these signals by the controller leads to the tracking of this path by UUV. In this paper, the dynamical model of the UUV, entitled as "mUUV-WJ-1" , is derived and its hydrodynamic coefficients are calculated by CFD in order to be used in the simulations. For simulation by the method presented in this study, three environments with different obstacles are intended in order to check the performance of the IT2FLC controller in generating optimal paths for guiding the UUV. In this article, in addition to ICA, Particle Swarm Optimization (PSO and Artificial Bee Colony (ABC are also used for generation of the paths and the results are compared with each other. The results show the appropriate performance of ICA rather than ABC and PSO. Moreover, to evaluate the performance of the IT2FLC, optimal Type-1 Fuzzy Logic Controller (T1FLC and Proportional Integrator Differentiator (PID controller are designed
comparative analysis and implementation of dijkstra's shortest path
user
path problem requires finding a single shortest-path between given vertices s and t; ... Bridge in 1735, [5 – 10]. This problem led to the .... their advancements from new design paradigms, data structures ..... .
The evolutionary origin of the vertebrate body plan: the problem of head segmentation.
Onai, Takayuki; Irie, Naoki; Kuratani, Shigeru
2014-01-01
The basic body plan of vertebrates, as typified by the complex head structure, evolved from the last common ancestor approximately 530 Mya. In this review, we present a brief overview of historical discussions to disentangle the various concepts and arguments regarding the evolutionary development of the vertebrate body plan. We then explain the historical transition of the arguments about the vertebrate body plan from merely epistemological comparative morphology to comparative embryology as a scientific treatment on this topic. Finally, we review the current progress of molecular evidence regarding the basic vertebrate body plan, focusing on the link between the basic vertebrate body plan and the evolutionarily conserved developmental stages (phylotypic stages).
Kilic, Çigdem; Sancar-Tokmak, Hatice
2017-01-01
This case study investigates how preservice primary school teachers describe their experiences with digital story-based problem solving applications and their plans for the future integration of this technology into their teaching. Totally 113 preservice primary school teachers participated in the study. Data collection tools included a…
Hansen, Anders Dohn; Clausen, Jens
This paper presents the Steel Plate Storage Yard Crane Scheduling Problem. The task is to generate a schedule for two gantry cranes sharing tracks. The schedule must comply with a number of constraints and at the same time be cost efficient. We propose some ideas for a two stage planning...
Schlagheck, R. A.
1977-01-01
New planning techniques and supporting computer tools are needed for the optimization of resources and costs for space transportation and payload systems. Heavy emphasis on cost effective utilization of resources has caused NASA program planners to look at the impact of various independent variables that affect procurement buying. A description is presented of a category of resource planning which deals with Spacelab inventory procurement analysis. Spacelab is a joint payload project between NASA and the European Space Agency and will be flown aboard the Space Shuttle starting in 1980. In order to respond rapidly to the various procurement planning exercises, a system was built that could perform resource analysis in a quick and efficient manner. This system is known as the Interactive Resource Utilization Program (IRUP). Attention is given to aspects of problem definition, an IRUP system description, questions of data base entry, the approach used for project scheduling, and problems of resource allocation.
Path Minima Queries in Dynamic Weighted Trees
Davoodi, Pooya; Brodal, Gerth Stølting; Satti, Srinivasa Rao
2011-01-01
In the path minima problem on a tree, each edge is assigned a weight and a query asks for the edge with minimum weight on a path between two nodes. For the dynamic version of the problem, where the edge weights can be updated, we give data structures that achieve optimal query time\\todo{what about...
Time optimal paths for high speed maneuvering
Reister, D.B.; Lenhart, S.M.
1993-01-01
Recent theoretical results have completely solved the problem of determining the minimum length path for a vehicle with a minimum turning radius moving from an initial configuration to a final configuration. Time optimal paths for a constant speed vehicle are a subset of the minimum length paths. This paper uses the Pontryagin maximum principle to find time optimal paths for a constant speed vehicle. The time optimal paths consist of sequences of axes of circles and straight lines. The maximum principle introduces concepts (dual variables, bang-bang solutions, singular solutions, and transversality conditions) that provide important insight into the nature of the time optimal paths. We explore the properties of the optimal paths and present some experimental results for a mobile robot following an optimal path.
Education - path towards solution regarding disposal of spent nuclear fuel
Klein, D.E.
1991-01-01
Education, not emotional reaction, is the path to take in the safe disposal of spent nuclear fuel. Education is needed at all levels: Elementary schools, secondary schools, two-year colleges, four-year colleges, graduate schools, and adult education. The Office of Civilian Radioactive Waste Management (OCRWM) should not be expected to tackle this problem alone. Assistance is needed from local communities, schools, and state and federal governments. However, OCRWM can lay the foundation for a comprehensive educational plan directed specifically at educating the public on the spent nuclear fuel issue and OCRWM can begin the implementation of this plan
N. Kapinos
2017-05-01
Full Text Available Summary Fundamental changes of land relations that have been established for the period of land reform in the independent Ukraine and the new socio-economic and environmental problems identified new character and content of the land. During the land reform in Ukraine to land management encountered new challenges that focus on the implementation of land policy and land relations fundamental change. Accordingly, to land management faces new challenges. Today for events to decentralize power facilities, new land - the territory united local communities should determine for whom the prospect of organizing the use and protection of land and other natural resources. However, the current land law the answer to this problem does not. Instead, normalization is an attempt to issues related to improving the quality of drafting documentation spatial planning (urban planning documents establish procedures for integrated development plans of local communities, the introduction of rules regulating local area to establish procedures for planning, construction and other use areas and about objects, improving public hearings to address public interests and relieve tension in the planning and construction of the territories. However, planning documentation does not solve the problems of perspective development of the organization use and protection of land and other natural resources. There is a need to distinguish between objects of regional urban planning and land management. This is because the urban planning regulations covering mainly two categories of land (settlements, industry, transport, communications and other purposes, not including agricultural land, which houses objects of capital construction. However, they make up for Ukraine just 4.2% of the total area. For the remaining seven categories of land (agricultural land, forest and water resources, conservation, recreation, recreational purposes land use planning and their protection should be based on
PATHS groundwater hydrologic model
Nelson, R.W.; Schur, J.A.
1980-04-01
A preliminary evaluation capability for two-dimensional groundwater pollution problems was developed as part of the Transport Modeling Task for the Waste Isolation Safety Assessment Program (WISAP). Our approach was to use the data limitations as a guide in setting the level of modeling detail. PATHS Groundwater Hydrologic Model is the first level (simplest) idealized hybrid analytical/numerical model for two-dimensional, saturated groundwater flow and single component transport; homogeneous geology. This document consists of the description of the PATHS groundwater hydrologic model. The preliminary evaluation capability prepared for WISAP, including the enhancements that were made because of the authors' experience using the earlier capability is described. Appendixes A through D supplement the report as follows: complete derivations of the background equations are provided in Appendix A. Appendix B is a comprehensive set of instructions for users of PATHS. It is written for users who have little or no experience with computers. Appendix C is for the programmer. It contains information on how input parameters are passed between programs in the system. It also contains program listings and test case listing. Appendix D is a definition of terms.
Tool path in torus tool CNC machining
XU Ying
2016-10-01
Full Text Available This paper is about tool path in torus tool CNC machining.The mathematical model of torus tool is established.The tool path planning algorithm is determined through calculation of the cutter location,boundary discretization,calculation of adjacent tool path and so on,according to the conversion formula,the cutter contact point will be converted to the cutter location point and then these points fit a toolpath.Lastly,the path planning algorithm is implemented by using Matlab programming.The cutter location points for torus tool are calculated by Matlab,and then fit these points to a toolpath.While using UG software,another tool path of free surface is simulated of the same data.It is drew compared the two tool paths that using torus tool is more efficient.
In April 2018, EPA released the draft IRIS Assessment Plan for Ammonia and Ammonium Salts Noncancer Oral. The IAP communicates to the public the plan for assessing each individual chemical and includes summary information on the IRIS Program’s scoping and initial proble...
Some special problems during the planning and construction of the Paks nuclear power station
Szilagyi, Gyula; Szalai, Geza; Ferenczy, Gabor; Sarkoezy, Endre; Daniel, Gabor
1984-01-01
The construction of the power plant building using cradle case technology is outlined. The planning and construction of the auxiliary building for waste storage, for water-treatment equipment and others are described. The planning and specifications of a part of the electrical and control systems are presented briefly. Finally, the use of computer-aided design techniques is mentioned. (R.P.)
Some special problems during the planning and construction of the Paks nuclear power station
Szilagyi, G.; Szalai, G.; Ferenczy, G.; Sarkoezy, E.; Daniel, G. (Eroemue es Halozattervezoe Vallalat, Eroeterv, Budapest (Hungary))
1984-01-01
The construction of the power plant building using cradle case technology is outlined. The planning and construction of the auxiliary building for waste storage, for water-treatment equipment and others are described. The planning and specifications of a part of the electrical and control systems are presented briefly. Finally, the use of computer-aided design techniques is mentioned.
Oostermeijer, M.; Boonen, A.J.H.; Jolles, J.
2014-01-01
The scientific literature shows that constructive play activities are positively related to children's spatial ability. Likewise, a close positive relation is found between spatial ability and mathematical word problem-solving performances. The relation between children's constructive play and their
Path Creation, Path Dependence and Breaking Away from the Path
Wang, Jens; Hedman, Jonas; Tuunainen, Virpi Kristiina
2016-01-01
The explanation of how and why firms succeed or fail is a recurrent research challenge. This is particularly important in the context of technological innovations. We focus on the role of historical events and decisions in explaining such success and failure. Using a case study of Nokia, we develop and extend a multi-layer path dependence framework. We identify four layers of path dependence: technical, strategic and leadership, organizational, and external collaboration. We show how path dep...
Quickly Planning TF/TA2 Trajectory by Artificial Immune Algorithm
LIU Lifeng
2015-04-01
Full Text Available Flight path planning by artificial immune algorithm approach met the requirements of aircraft's flyability and operation is proposed for the problem of single and double TF/TA2 flight path planning. Punishment function (affinity function with comprehensive 3D threat information is designed. A comprehensive threat model is formed including dynamic and static threats and no-fly-zone. Accordingly, single and dual flight paths are planned by AIA, which have been compared with the paths by GA. The results show that, GA's planned a quick and longer path compared under simple threat environment; in complex environments, GA has high failure rate (greater than 95% for single aircraft, but it is failed for double aircrafts. For the single and double aircrafts, AIA can provides one optimal and more candidate optimal flight paths.
Nataliya Gennadievna Yushkova
2015-01-01
Full Text Available The emerging imperatives of innovation economic development in Russia determine the content of conceptual and institutional constraints to the development of regional economic systems (RES. They consider the regional planning system as a leading priority in its inseparable unity with modern public administration tasks. However, the practice of development of long-term plans in the RF subjects proves that the innovation challenges of economic policy are not reflected properly in them or they are significantly distorted. The following reasons reduce the effectiveness of modernization processes in the RF subjects and hamper the appropriate reaction of RES on their impact: the lack of coordination between socio-economic and spatial regional plans, the imbalance of interaction between state authorities engaged in long-term planning, the lack of real prerequisites for the implementation of innovation initiatives in the regions. Systematization and analysis of long-term plans make it possible to substantiate the consistency of the spatial approach to regional planning expressed in the dominance of the transformational function that synchronizes the configuration and parameters of RES, and to establish ways to integrate spatial components in the system of regional planning through optimization of its tool support. The change in the content of the instrumentation support is based on the synthesis of the predominant basic characteristics of the existing tools used in isolated subsystems of regional planning of socio-economic and territorial development. The study has established a system of tool support for regional planning that adapts to the changes in both internal and external factors in the development of RES. Three main groups of tools: organizing, regulating, and coordinating are defined by their typing in accordance with the groups of management functions. The article proposes the modeling of combinations of tools that are subordinated to the
Scowen, Paul A.; Tripp, Todd; Beasley, Matt; Ardila, David; Andersson, B-G; Apellániz, Jesús Maíz; Barstow, Martin; Bianchi, Luciana; Calzetti, Daniela; Clampin, Mark; Evans, Christopher J.; France, Kevin; García, Miriam García; de Castro, Ana Gomez; Harris, Walt
2016-01-01
We present the science cases and technological discussions that came from the workshop titled ¿Finding the ultraviolet (UV)-Visible Path Forward¿ held at NASA GSFC 2015 June 25-26. The material presented outlines the compelling science that can be enabled by a next generation space-based observatory dedicated for UV¿visible science, the technologies that are available to include in that observatory design, and the range of possible alternative launch approaches that could also enable some of ...
New problem with sales, inventories, and operations planning in a supply chain environment
Thomas, Andre; Lamouri, Samir
2000-10-01
The highest level of planning and control system is necessary, because production and logistics systems are not so flexible to follow, from day to day, sales evolutions. The companies are therefore held to standardize the good practices concerning the elaboration of their Sales, Inventories and Operations Planning (SIOP). The SIOP makes it possible to implement the strategic objectives defined by Top Management at the time of the Business Plan. It is the link between sales and manufacturing planning. The objectives of each of those depend on the specificity of their trade: the Sales Department will go for a maximum sales whereas Production will endeavor to keep industrial cost prices as low as possible while the Finance Department will try to optimize the use of available funds. There are several tools for this optimization: Graphical method and linear programming. Today, the economic context requires robust optimization.
Webb, T.
1979-01-01
Energy policy is discussed, with particular reference to Scotland. The plans for nuclear power are analyzed in comparison with developments in coal mining, use of oil and gas and other possible energy sources such as wind and wave power. Arguments against the development of nuclear power are raised on grounds of economics, employment potential, and problems of waste disposal. (U.K.)
Breazu, F [Institute of Power Studies and Design, Bucharest (Romania)
1997-09-01
Romanian experience with the use of IAEA planning methodologies was effectively initiated in 1989 with the launching of a Technical Cooperation project of the IAEA for the study of the energy demand and optimal expansion plans for the electricity generation system. The experience gathered during this project was crucial for the Romanian experts who conducted the studies. As a results, now Romania has a team of well trained experts in the use of the IAEA planning models. This paper describes the principal problems faced by Romanian planners in the use of these models with emphasis on the WASP package. Suggestions for future enhancements of the package are also part of this report. (author). 5 figs.
[Thinking about several problems of the research of our family planning strategy].
Shi, H
1989-03-01
On the basis of 1982 census data, it is estimated that from 1987-1997 13 million women will enter the age of marriage and child-bearing each year. The tasks of keeping the population size around 1.2 billion by the year 2000 is arduous. Great efforts have to be made to continue encouraging one child/couple, and to pursue the current plans and policies and maintain strict control over fertility. Keeping population growth in pace with economic growth, environment, ecological balance, availability of per capita resources, education programs, employment capability, health services, maternal and child care, social welfare and social security should be a component of the long term development strategy of the country. Family planning is a comprehensive program which involves long cycles and complicated factors, viewpoints of expediency in guiding policy and program formulation for short term benefits are inappropriate. The emphasis of family planning program strategy should be placed on the rural areas where the majority of population reside. Specifically, the major aspects of strategic thrusts should be the linkage between policy implementation and reception, between family planning publicity and changes of ideation on fertility; the integrated urban and rural program management relating to migration and differentiation of policy towards minority population and areas in different economic development stages. In order to achieve the above strategies, several measures are proposed. (1) strengthening family planning program and organization structure; (2) providing information on population and contraception; (3) establishing family planning program network for infiltration effects; (4) using government financing, taxation, loan, social welfare and penalty to regulate fertility motivations; (5) improving the system of target allocation and data reporting to facilitate program implementation; (6) strengthening population projection and policy research; (7) and strengthening
S. M. J. Mirzapour Al-e-Hashem
2011-01-01
Full Text Available A multi-objective two stage stochastic programming model is proposed to deal with a multi-period multi-product multi-site production-distribution planning problem for a midterm planning horizon. The presented model involves majority of supply chain cost parameters such as transportation cost, inventory holding cost, shortage cost, production cost. Moreover some respects as lead time, outsourcing, employment, dismissal, workers productivity and training are considered. Due to the uncertain nature of the supply chain, it is assumed that cost parameters and demand fluctuations are random variables and follow from a pre-defined probability distribution. To develop a robust stochastic model, an additional objective functions is added to the traditional production-distribution-planning problem. So, our multi-objective model includes (i the minimization of the expected total cost of supply chain, (ii the minimization of the variance of the total cost of supply chain and (iii the maximization of the workers productivity through training courses that could be held during the planning horizon. Then, the proposed model is solved applying a hybrid algorithm that is a combination of Monte Carlo sampling method, modified -constraint method and L-shaped method. Finally, a numerical example is solved to demonstrate the validity of the model as well as the efficiency of the hybrid algorithm.
Feynman's path integrals and Bohm's particle paths
Tumulka, Roderich
2005-01-01
Both Bohmian mechanics, a version of quantum mechanics with trajectories, and Feynman's path integral formalism have something to do with particle paths in space and time. The question thus arises how the two ideas relate to each other. In short, the answer is, path integrals provide a re-formulation of Schroedinger's equation, which is half of the defining equations of Bohmian mechanics. I try to give a clear and concise description of the various aspects of the situation. (letters and comments)
Path coupling and aggregate path coupling
Kovchegov, Yevgeniy
2018-01-01
This book describes and characterizes an extension to the classical path coupling method applied to statistical mechanical models, referred to as aggregate path coupling. In conjunction with large deviations estimates, the aggregate path coupling method is used to prove rapid mixing of Glauber dynamics for a large class of statistical mechanical models, including models that exhibit discontinuous phase transitions which have traditionally been more difficult to analyze rigorously. The book shows how the parameter regions for rapid mixing for several classes of statistical mechanical models are derived using the aggregate path coupling method.
Nourifar, Raheleh; Mahdavi, Iraj; Mahdavi-Amiri, Nezam; Paydar, Mohammad Mahdi
2017-09-01
Decentralized supply chain management is found to be significantly relevant in today's competitive markets. Production and distribution planning is posed as an important optimization problem in supply chain networks. Here, we propose a multi-period decentralized supply chain network model with uncertainty. The imprecision related to uncertain parameters like demand and price of the final product is appropriated with stochastic and fuzzy numbers. We provide mathematical formulation of the problem as a bi-level mixed integer linear programming model. Due to problem's convolution, a structure to solve is developed that incorporates a novel heuristic algorithm based on Kth-best algorithm, fuzzy approach and chance constraint approach. Ultimately, a numerical example is constructed and worked through to demonstrate applicability of the optimization model. A sensitivity analysis is also made.
Problems related to public perceptions of radiological emergency planning and response
Reilly, Margaret A.
1989-01-01
Beyond the scientific, the administrative and procedural issues of radiological emergency planning and response there is the issue of public perception. This paper emphasises that, radiation crises being a rare occurrence there is no enough database for generating scholarly quantitative reports. It suggests the need for disseminating timely and accurate information through a single spokesman from a responsible public agency
IRIS Assessment Plan for Nitrate and Nitrite (Scoping and Problem Formulation Materials)
In September 2017, EPA released the draft IRIS Assessment Plan (IAP) for Nitrate and Nitrite for public review and comment. This document was discussed at an EPA Science Advisory Board (SAB) Chemical Assessment Advisory Committee (CAAC) meeting on September 27-28, 2017....
Pre-Planning Civic Action: An Analysis of Civic Leaders' Problem Solving Strategies
Fitzgerald, Jason
2016-01-01
This study explores the civic thinking heuristics that civic leaders use when pre-planning action. Across eight think-aloud protocols, findings suggest that three heuristics are employed. "Frame alignment" refers to the process of harmonizing personal beliefs and interests with the particulars of a civic action issue to find personal…
Planning lessons with learning platforms - problem and prospects for mathematics education
Tamborg, Andreas Lindenskov
2018-01-01
is a key intention behind the implementation of the platform. It is also concluded that when the teachers succeed in using learning objectives actively in their planning, the objectives support the teachers in designing lessons that correspond with their intentions. The paper concludes with a discussion...
Chin, Siu A.
2014-03-01
The sign-problem in PIMC simulations of non-relativistic fermions increases in serverity with the number of fermions and the number of beads (or time-slices) of the simulation. A large of number of beads is usually needed, because the conventional primitive propagator is only second-order and the usual thermodynamic energy-estimator converges very slowly from below with the total imaginary time. The Hamiltonian energy-estimator, while more complicated to evaluate, is a variational upper-bound and converges much faster with the total imaginary time, thereby requiring fewer beads. This work shows that when the Hamiltonian estimator is used in conjunction with fourth-order propagators with optimizable parameters, the ground state energies of 2D parabolic quantum-dots with approximately 10 completely polarized electrons can be obtain with ONLY 3-5 beads, before the onset of severe sign problems. This work was made possible by NPRP GRANT #5-674-1-114 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the author.
Connolly, T.J.; Hansen, U.; Jaek, W.; Beckurts, K.H.
1979-01-01
In examing the world nuclear energy paths, the following assumptions were adopted: the world economy will grow somewhat more slowly than in the past, leading to reductions in electricity demand growth rates; national and international political impediments to the deployment of nuclear power will gradually disappear over the next few years; further development of nuclear power will proceed steadily, without serious interruption but with realistic lead times for the introduction of advanced technologies. Given these assumptions, this paper attempts a study of possible world nuclear energy developments, disaggregated on a regional and national basis. The scenario technique was used and a few alternative fuel-cycle scenarios were developed. Each is an internally consistent model of technically and economically feasible paths to the further development of nuclear power in an aggregate of individual countries and regions of the world. The main purpose of this modeling exercise was to gain some insight into the probable international locations of reactors and other nuclear facilities, the future requirements for uranium and for fuel-cycle services, and the problems of spent-fuel storage and waste management. The study also presents an assessment of the role that nuclear power might actually play in meeting future world energy demand
Bogusława Baran-Zgłobicka
2015-11-01
Full Text Available Local planning in Poland encompasses spatial development conditions and directions study for a district (“study” and a local spatial development plan (“local plan”. The study is the only planning document that is required for the entire area of a district. It outlines directions of spatial policy and spatial development. Detailed investigations encompassed nine functionally diverse rural districts in SE Poland. The objective was to assess the description of environmental determinants and the problems of natural resources protection presented in the studies. The adequacy of the adopted approach to the subject matter and its correlation with spatial development directions were analysed. The analysed studies usually provide an exhaustive description of (a natural resources and the nature conservation system along with restrictions in environment use, and (b the problem of raw materials. Not all studies, however, highlight the local, very often unique characteristics of the natural environment. Natural hazards are marginalized in some studies. There is also a lack of concrete solutions for the protection of space and improvement of spatial order.
Gang Du
2015-11-01
Full Text Available It is of theoretical and practical significance to understand what factors influence the sustainable development of home healthcare services in China. Based on a face-to-face survey, we find that the location planning, which is decisive for the improvement of patient satisfaction, can effectively reduce the risks, as well as the costs of redundant construction and re-construction of service centers for home healthcare and, thus, helps ensure the sustainability of health and the environment. The purposes of this paper are to investigate the existing problem of home healthcare in Shanghai and to find the optimum location planning scheme under several realistic constraints. By considering differentiated services provided by the medical staff at different levels and the degrees of patient satisfaction, a mixed integer programming model is built to minimize the total medical cost. The IBM ILOGCPLEX is used to solve the above model. Finally, a case study of Putuo district in Shanghai is conducted to validate the proposed model and methodology. Results indicate that the model used in this paper can effectively reduce the total medical cost and enhance the medical sustainability, and therefore, the results of the model can be used as a reference for decision makers on the location planning problem of home healthcare services in China.
Comparison of Behavior-based and Planning Techniques on the Small Robot Maze Exploration Problem
Slušný, Stanislav; Neruda, Roman; Vidnerová, Petra
2010-01-01
Roč. 23, č. 4 (2010), s. 560-567 ISSN 0893-6080. [ICANN 2008. International Conference on Artificial Neural Networks /18./. Prague, 03.09.2008-06.09.2008] R&D Projects: GA ČR GA201/08/1744 Institutional research plan: CEZ:AV0Z10300504 Keywords : evolutionary robotic s * neural networks * reinforcement learning * localization Subject RIV: IN - Informatics, Computer Science Impact factor: 1.955, year: 2010
Emiel, G.
2008-01-01
This manuscript deals with large-scale non-smooth optimization that may typically arise when performing Lagrangian relaxation of difficult problems. This technique is commonly used to tackle mixed-integer linear programming - or large-scale convex problems. For example, a classical approach when dealing with power generation planning problems in a stochastic environment is to perform a Lagrangian relaxation of the coupling constraints of demand. In this approach, a master problem coordinates local subproblems, specific to each generation unit. The master problem deals with a separable non-smooth dual function which can be maximized with, for example, bundle algorithms. In chapter 2, we introduce basic tools of non-smooth analysis and some recent results regarding incremental or inexact instances of non-smooth algorithms. However, in some situations, the dual problem may still be very hard to solve. For instance, when the number of dualized constraints is very large (exponential in the dimension of the primal problem), explicit dualization may no longer be possible or the update of dual variables may fail. In order to reduce the dual dimension, different heuristics were proposed. They involve a separation procedure to dynamically select a restricted set of constraints to be dualized along the iterations. This relax-and-cut type approach has shown its numerical efficiency in many combinatorial problems. In chapter 3, we show Primal-dual convergence of such strategy when using an adapted sub-gradient method for the dual step and under minimal assumptions on the separation procedure. Another limit of Lagrangian relaxation may appear when the dual function is separable in highly numerous or complex sub-functions. In such situation, the computational burden of solving all local subproblems may be preponderant in the whole iterative process. A natural strategy would be here to take full advantage of the dual separable structure, performing a dual iteration after having
Conway, Kevin P; Green, Victoria R; Kasza, Karin A; Silveira, Marushka L; Borek, Nicolette; Kimmel, Heather L; Sargent, James D; Stanton, Cassandra; Lambert, Elizabeth; Hilmi, Nahla; Reissig, Chad J; Jackson, Kia J; Tanski, Susanne E; Maklan, David; Hyland, Andrew J; Compton, Wilson M
2017-08-01
Although non-cigarette tobacco product use is increasing among U.S. adults, their associations with substance use and mental health problems are unclear. This study examined co-occurrence of tobacco use, substance use, and mental health problems, and its moderation by gender, among 32,202U.S. adults from Wave 1 (2013-2014) of the nationally representative longitudinal Population Assessment of Tobacco and Health (PATH) Study. Participants self-reported current cigarette, e-cigarette, traditional cigar, cigarillo, filtered cigar, hookah, smokeless tobacco and other tobacco product use; past year alcohol, marijuana, and other drug use; and past year substance use, internalizing and externalizing problems. Compared to non-current tobacco users, current users were more likely to report alcohol or drug use (adjusted odds ratio (AOR)=2.6; 95% confidence interval (CI): 2.3, 2.9), with the strongest associations observed for cigarillo and hookah users. Across all tobacco product groups, users were more likely to report internalizing (AOR=1.9; 95% CI: 1.7, 2.1), externalizing (AOR=1.6; 95% CI: 1.5, 1.8), and substance use (AOR=3.4; 95% CI: 2.9, 4.1) problems than non-users. Gender moderated many of these associations and, of these, all non-cigarette tobacco product associations were stronger among females. This nationally representative study of U.S. adults is the first to comprehensively document tobacco use, substance use, and mental health comorbidities across the range of currently available tobacco products, while also demonstrating that female tobacco users are at increased risk for substance use and mental health problems. These findings may point to gender differences in vulnerability and suggest that interventions incorporate gender-specific approaches. Copyright © 2017 Elsevier B.V. All rights reserved.
The Historical Path of Evaluation as Reflected in the Content of Evaluation and Program Planning
Ayob, Abu H.; Morell, Jonathan A.
2016-01-01
This paper examines the intellectual structure of evaluation by means of citation analysis. By using various article attributes and citation counts in Google Scholar and (Social) Science Citation Index Web of Science, we analyze all articles published in Evaluation and Program Planning from 2000...... until 2012. We identify and discuss the characteristics and development of the field as reflected in the history of those citations....
Vervet monkeys use paths consistent with context-specific spatial movement heuristics.
Teichroeb, Julie A
2015-10-01
Animal foraging routes are analogous to the computationally demanding "traveling salesman problem" (TSP), where individuals must find the shortest path among several locations before returning to the start. Humans approximate solutions to TSPs using simple heuristics or "rules of thumb," but our knowledge of how other animals solve multidestination routing problems is incomplete. Most nonhuman primate species have shown limited ability to route plan. However, captive vervets were shown to solve a TSP for six sites. These results were consistent with either planning three steps ahead or a risk-avoidance strategy. I investigated how wild vervet monkeys (Chlorocebus pygerythrus) solved a path problem with six, equally rewarding food sites; where site arrangement allowed assessment of whether vervets found the shortest route and/or used paths consistent with one of three simple heuristics to navigate. Single vervets took the shortest possible path in fewer than half of the trials, usually in ways consistent with the most efficient heuristic (the convex hull). When in competition, vervets' paths were consistent with different, more efficient heuristics dependent on their dominance rank (a cluster strategy for dominants and the nearest neighbor rule for subordinates). These results suggest that, like humans, vervets may solve multidestination routing problems by applying simple, adaptive, context-specific "rules of thumb." The heuristics that were consistent with vervet paths in this study are the same as some of those asserted to be used by humans. These spatial movement strategies may have common evolutionary roots and be part of a universal mental navigational toolkit. Alternatively, they may have emerged through convergent evolution as the optimal way to solve multidestination routing problems.
Effects of Online Problem-Based Learning on Teachers' Technology Perceptions and Planning
Nelson, Erik T.
2007-01-01
The purpose of this qualitative study was to examine the ways in which the experience of learning through an online problem-based learning (PBL) model affect teachers' perceptions of integrating technology. Participant reflections were collected and analyzed to identify the pros, cons, and challenges of learning technology integration through this…
Honhon, D.B.L.P.; Seshardi, S.
2013-01-01
We consider the problem of determining the optimal assortment of products to offer in a given product category when each customer is characterized by a type, which is a list of products he is willing to buy in decreasing order of preference. We assume consumer-driven, dynamic, stockout-based
Armando González-Cabán
2009-01-01
These proceedings summarize the results of a symposium designed to address current issues of agencies with wildland fire protection responsibility at the federal and state levels in the United States as well as agencies in the international community. The topics discussed at the symposium included regional, national, and global vision of forest fires: common problems...
Architectural and town-planning reconstruction problems of the city of Voronezh
Mikhaylova, TTatyana; Parshin, Dmitriy; Shoshinov, Vitaly; Trebukhin, Anatoliy
2018-03-01
The analysis of the state of the historically developed urban district of the city of Voronezh is made. The ways of solving the identified architectural and urban problems of reconstruction of historically developed buildings are proposed. The concept of reconstruction of a territory with historical buildings along Vaytsekhovsky Street is presented.
Attalla, E.M.; Lotayef, M.M.; Khalil, E.M.; El-Hosiny, H.A.
2007-01-01
The purpose of this study was to quantify dose distribution errors by comparing actual dose measurements with the calculated values done by the software. To evaluate the outcome of radiation overexposure related to Panama's accident and in response to ensure that the treatment planning systems (T.P.S.) are being operated in accordance with the appropriate quality assurance programme, we studied the central axis and pripheral depth dose data using complex field shaped with blocks to quantify dose distribution errors. Material and Methods: Multi data T.P.S. software versions 2.35 and 2.40 and Helax T.P.S. software version 5.1 B were assesed. The calculated data of the software treatment planning systems were verified by comparing these data with the actual dose measurements for open and blocked high energy photon fields (Co-60, 6MV and 18MV photons). Results: Close calculated and measured results were obtained for the 2-D (Multi data) and 3-D treatment planning (TMS Helax). These results were correct within 1 to 2% for open fields and 0.5 to 2.5% for peripheral blocked fields. Discrepancies between calculated and measured data ranged between 13. to 36% along the central axis of complex blocked fields when normalisation point was selected at the Dmax, when the normalisation point was selected near or under the blocks, the variation between the calculated and the measured data was up to 500% difference. Conclusions: The present results emphasize the importance of the proper selection of the normalization point in the radiation field, as this facilitates detection of aberrant dose distribution (over exposure or under exposure)
Attalla, Ehab M; Lotayef, Mohamed M; Khalil, Ehab M; El-Hosiny, Hesham A; Nazmy, Mohamed S
2007-06-01
The purpose of this study was to quantify dose distribution errors by comparing actual dose measurements with the calculated values done by the software. To evaluate the outcome of radiation overexposure related to Panama's accident and in response to ensure that the treatment planning systems (T.P.S.) are being operated in accordance with the appropriate quality assurance programme, we studied the central axis and pripheral depth dose data using complex field shaped with blocks to quantify dose distribution errors. Multidata T.P.S. software versions 2.35 and 2.40 and Helax T.P.S. software version 5.1 B were assesed. The calculated data of the software treatment planning systems were verified by comparing these data with the actual dose measurements for open and blocked high energy photon fields (Co-60, 6MV & 18MV photons). Close calculated and measured results were obtained for the 2-D (Multidata) and 3-D treatment planning (TMS Helax). These results were correct within 1 to 2% for open fields and 0.5 to 2.5% for peripheral blocked fields. Discrepancies between calculated and measured data ranged between 13. to 36% along the central axis of complex blocked fields when normalisation point was selected at the Dmax, when the normalisation point was selected near or under the blocks, the variation between the calculated and the measured data was up to 500% difference. The present results emphasize the importance of the proper selection of the normalization point in the radiation field, as this facilitates detection of aberrant dose distribution (over exposure or under exposure).
Molten Salt Demonstration Transmuter (comparison of new technical problems with old US MSR plans)
Lelek, V.
2001-01-01
A Molten Salt Demonstration Transmuter (MSDT) is required to show the operation and design performance for closing the nuclear spent fuel (NSF) cycle for PWR or WWER reactors operated in the once-through cycle (OTC) mode. The remnant waste (fission products only) would be either permanently stored or held for secondary use. The purpose of this proposal is to establish the design basis for the MSDT and compare contemporary knowledge and demands with that from US plans for MS reactors from 1974, because both technologies are very near (Authors)
Generating Approximative Minimum Length Paths in 3D for UAVs
Schøler, Flemming; la Cour-Harbo, Anders; Bisgaard, Morten
2012-01-01
We consider the challenge of planning a minimum length path from an initial position to a desired position for a rotorcraft. The path is found in a 3-dimensional Euclidean space containing a geometric obstacle. We base our approach on visibility graphs which have been used extensively for path pl...
Moesby, Egon
2005-01-01
In this article, the author is giving examples on an approach to include the personal competences in the initial phase of the planning process for a change towards project organized and problem-based learning ? POPBL. A model is presented on how to have trainees recognize the necessity to include...... professional competences as well as personal competences in a new POPBL based curriculum. The article continues by giving an example of a possible method to be used in the developing of a curriculum where the personal skills and abilities are an active and equally valued as the development of the students...
Abdul Aziz, Safiyyah; Fletcher, Janet; Bayliss, Donna M
2017-05-01
Past research with children with specific language impairment (SLI) has shown them to have poorer planning and problem-solving ability, and delayed self-regulatory speech (SRS) relative to their typically developing (TD) peers. However, the studies are few in number and are restricted in terms of the number and age range of participants, which limits our understanding of the nature and extent of any delays. Moreover, no study has examined the performance of a significant subset of children with SLI, those who have hyperactive and inattentive behaviours. This cross-sectional study aimed to compare the performance of young children with SLI (aged 4-7 years) with that of their TD peers on a planning and problem-solving task and to examine the use of SRS while performing the task. Within each language group, the performance of children with and without hyperactive and inattentive behaviours was further examined. Children with SLI (n = 91) and TD children (n = 81), with and without hyperactive and inattentive behaviours across the three earliest school years (Kindergarten, Preprimary and Year 1) were video-taped while they completed the Tower of London (TOL), a planning and problem-solving task. Their recorded speech was coded and analysed to look at differences in SRS and its relation to TOL performance across the groups. Children with SLI scored lower on the TOL than TD children. Additionally, children with hyperactive and inattentive behaviours performed worse than those without hyperactive and inattentive behaviours, but only in the SLI group. This suggests that children with SLI with hyperactive and inattentive behaviours experience a double deficit. Children with SLI produced less inaudible muttering than TD children, and showed no reduction in social speech across the first three years of school. Finally, for children with SLI, a higher percentage performed better on the TOL when they used SRS than when they did not. The results point towards a significant delay
An Advanced Tabu Search Approach to Solving the Mixed Payload Airlift Load Planning Problem
2009-03-01
cargo, and the problem therefore becomes trivial. 3. Shoring: Some cargo requires shoring which is small planks of plywood stacked on top of each...Integer Programming Method In 1989, Kevin Ng examined the bin-packing MPALP for Canada’s C-130 aircraft (Ng 1992). His goal was to move a set of... leadership & ethics [ ] warfighting [ ] international security [ ] doctrine [X] other (specify): Military Airlift
Lagrangian relaxation technique in power systems operation planning: Multipliers updating problem
Ruzic, S. [Electric Power Utility of Serbia, Belgrade (Yugoslavia)
1995-11-01
All Lagrangian relaxation based approaches to the power systems operation planning have an important common part: the Lagrangian multipliers correction procedure. It is the subject of this paper. Different approaches presented in the literature are discussed and an original method for the Lagrangian multipliers updating is proposed. The basic idea of this new method is to update Lagrangian multipliers trying to satisfy Khun-Tucker optimality conditions. Instead of the dual function maximization the `distance of optimality function` is defined and minimized. If Khun-Tucker optimality conditions are satisfied the value of this function is in range (-1,0); otherwise the function has a big positive value. This method called `the distance of optimality method` takes into account future changes in planning generations due to the Lagrangian multipliers updating. The influence of changes in a multiplier associated to one system constraint to the satisfaction of some other system requirements is also considered. The numerical efficiency of the proposed method is analyzed and compared with results obtained using the sub-gradient technique. 20 refs, 2 tabs
Euclidean shortest paths exact or approximate algorithms
Li, Fajie
2014-01-01
This book reviews algorithms for the exact or approximate solution of shortest-path problems, with a specific focus on a class of algorithms called rubberband algorithms. The coverage includes mathematical proofs for many of the given statements.
The Study of Intelligent Vehicle Navigation Path Based on Behavior Coordination of Particle Swarm.
Han, Gaining; Fu, Weiping; Wang, Wen
2016-01-01
In the behavior dynamics model, behavior competition leads to the shock problem of the intelligent vehicle navigation path, because of the simultaneous occurrence of the time-variant target behavior and obstacle avoidance behavior. Considering the safety and real-time of intelligent vehicle, the particle swarm optimization (PSO) algorithm is proposed to solve these problems for the optimization of weight coefficients of the heading angle and the path velocity. Firstly, according to the behavior dynamics model, the fitness function is defined concerning the intelligent vehicle driving characteristics, the distance between intelligent vehicle and obstacle, and distance of intelligent vehicle and target. Secondly, behavior coordination parameters that minimize the fitness function are obtained by particle swarm optimization algorithms. Finally, the simulation results show that the optimization method and its fitness function can improve the perturbations of the vehicle planning path and real-time and reliability.
H∞ control for path tracking of autonomous underwater vehicle motion
Lin-Lin Wang
2015-05-01
Full Text Available In order to simplify the design of path tracking controller and solve the problem relating to nonlinear dynamic model of autonomous underwater vehicle motion planning, feedback linearization method is first adopted to transform the nonlinear dynamic model into an equivalent pseudo-linear dynamic model in horizontal coordinates. Then considering wave disturbance effect, mixed-sensitivity method of H∞ robust control is applied to design state-feedback controller for this equivalent dynamic model. Finally, control law of pseudo-linear dynamic model is transformed into state (surge velocity and yaw angular rate tracking control law of nonlinear dynamic model through inverse coordinate transformation. Simulation indicates that autonomous underwater vehicle path tracking is successfully implemented with this proposed method, and the influence of parameter variation in autonomous underwater vehicle dynamic model on its tracking performance is reduced by H∞ controller. All the results show that the method proposed in this article is effective and feasible.
Lattice Paths and the Constant Term
Brak, R; Essam, J; Osborn, J; Owczarek, A L; Rechnitzer, A
2006-01-01
We firstly review the constant term method (CTM), illustrating its combinatorial connections and show how it can be used to solve a certain class of lattice path problems. We show the connection between the CTM, the transfer matrix method (eigenvectors and eigenvalues), partial difference equations, the Bethe Ansatz and orthogonal polynomials. Secondly, we solve a lattice path problem first posed in 1971. The model stated in 1971 was only solved for a special case - we solve the full model
The Problems of Planning a Timetable for Transport by Road in Terms of Theft Protection
Gnap Jozef
2017-05-01
Full Text Available In each transport, it is necessary to take into account the risks that may occur during transport. Most of these risks are associated with criminal activity, whether on a shipment, the driver himself or the vehicles used in potentially hazardous segments. The aim is to design a planning and verification process on a selected route or routes within Europe. The proposed transport route starts with load in the Kechnec Industrial Park and continues with two unloadings in Teplička nad Váhom in the Kia Motors Slovakia and in the town of Wolfsburg in the Volkswagen The transport route was designed in three alternatives by internet application Map&Guide.
Heuristic methods for single link shared backup path protection
Haahr, Jørgen Thorlund; Stidsen, Thomas Riis; Zachariasen, Martin
2014-01-01
schemes are employed. In contrast to manual intervention, automatic protection schemes such as shared backup path protection (SBPP) can recover from failure quickly and efficiently. SBPP is a simple but efficient protection scheme that can be implemented in backbone networks with technology available...... heuristic algorithms and lower bound methods for the SBPP planning problem. Experimental results show that the heuristic algorithms are able to find good quality solutions in minutes. A solution gap of less than 3.5 % was achieved for 5 of 7 benchmark instances (and a gap of less than 11 % for the remaining...
On path generation and feedforward control for a class of surface sailing vessels
Xiao, Lin; Jouffroy, Jerome
2010-01-01
Sailing vessels with wind as their main means of propulsion possess a unique property that the paths they take depend on the wind direction, which, in the literature, has attracted less attention than normal vehicles propelled by propellers or thrusters. This paper considers the problem of motion...... planning and controllability for sailing vehicles representing the no-sailing zone effect in sailing. Following our previous work, we present an extended algorithm for automatic path generation with a prescribed initial heading for a simple model of sailing vehicles, together with a feedforward controller...
Masoud Rabbani
2017-02-01
Full Text Available Nowadays, fiber-optic due to having greater bandwidth and being more efficient compared with other similar technologies, are counted as one the most important tools for data transfer. In this article, an integrated mathematical model for a three-level fiber-optic distribution network with consideration of simultaneous backbone and local access networks is presented in which the backbone network is a ring and the access networks has a star-star topology. The aim of the model is to determine the location of the central offices and splitters, how connections are made between central offices, and allocation of each demand node to a splitter or central office in a way that the wiring cost of fiber optical and concentrator installation are minimized. Moreover, each user’s desired bandwidth should be provided efficiently. Then, the proposed model is validated by GAMS software in small-sized problems, afterwards the model is solved by two meta-heuristic methods including differential evolution (DE and genetic algorithm (GA in large-scaled problems and the results of two algorithms are compared with respect to computational time and objective function obtained value. Finally, a sensitivity analysis is provided. Keyword: Fiber-optic, telecommunication network, hub-location, passive splitter, three-level network.
Carrie Ka Yuk Lin
2014-01-01
Full Text Available Logistic systems with uncertain demand, travel time, and on-site processing time are studied here where sequential trip travel is allowed. The relationship between three levels of decisions: facility location, demand allocation, and resource capacity (number of service units, satisfying the response time requirement, is analysed. The problem is formulated as a stochastic mixed integer program. A simulation-based hybrid heuristic is developed to solve the dynamic problem under different response time service level. An initial solution is obtained from solving static location-allocation models, followed by iterative improvement of the three levels of decisions by ejection, reinsertion procedure with memory of feasible and infeasible service regions. Results indicate that a higher response time service level could be achieved by allocating a given resource under an appropriate decentralized policy. Given a response time requirement, the general trend is that the minimum total capacity initially decreases with more facilities. During this stage, variability in travel time has more impact on capacity than variability in demand arrivals. Thereafter, the total capacity remains stable and then gradually increases. When service level requirement is high, the dynamic dispatch based on first-come-first-serve rule requires smaller capacity than the one by nearest-neighbour rule.
Giovski, Nikola
2014-01-01
The fundamental difficulties of integrating wind energy into the power system arise from its large temporal variability and limited predictability. That's why the integration of wind power presents major challenge for today's operating and planning practices of the power system operators. Accurate predictions of the possible wind power output, in time intervals relevant for creating schedules for production and exchange capacity, allows to system operators and dispatching personnel more efficient power system management. Despite the challenges and problems that arise due to integration of wind power into power systems, which need to be solved or reduced, wind power has its advantages that should be utilized. The effective integration of wind power plants into the transmission grid should allow them to represent the backbone of future energy systems. Modern wind generators represent production units that have the ability to participate in the management of energy systems e.g. in the regulation of frequency, voltage and other network operating requirements. This paper provides a brief overview of global experiences with the challenges, problems and possible solutions that appear in wind generator systems from the aspect of forecasting, planning and delivery of wind energy. (author)
Conservation and Planning Problems in Diyarbakır Castle City
D. Türkan KEJANLI
2011-05-01
Full Text Available Suriçi region, the first settlement part of Diyarbakir, has been a settlement area with specific values throughout its history. It has been the cradle of many civilizations, located as it is, in an important commercial transportation axis serving the commercial center, These factors have affected the development of the city. The cultures found in Anatolia and the Mesopotamia regions have influenced the development of Diyarbakir city and it developed a mixed urban morphology because of its position in the region. The walls around the city played an important part in the urban settlement pattern by preserving the integrity of the city. However, the Diyarbakir Suriçi region has begun to lose this important tissue in the last several decades. Prepared city plans and the approaches of enforcement agencies have played a role in this process. This study aims to offer ways in which the conservation of the Diyarbakir Suriçi region and its historical texture can be sustained.
Marks, Ralf; Eilks, Ingo
2010-01-01
A case is described of the development of a lesson plan for 10th grade (age range 15-16) chemistry classes on the chemistry of shower gels. The lesson plan follows a socio-critical and problem-oriented approach to chemistry teaching. This means that, aside from learning about the basic chemistry of the components making up modern shower gels in…
Fiorot Astoures, H.; Alvarenga Rosa, R. de; Silva Rosa, A.
2016-07-01
Oil exploration in Brazil is mainly held by offshore platforms which require the supply of several products, including diesel to maintain its engines. One strategy to supply diesel to the platforms is to keep a vessel filled with diesel nearby the exploration basin. An empty boat leaves the port and goes directly to this vessel, then it is loaded with diesel. After that, it makes a trip to supply the platforms and when the boat is empty, it returns to the vessel to be reloaded with more diesel going to another trip. Based on this description, this paper proposes a mathematical model based on the Vehicle Routing Problem with Intermediate Replenishment Facilities (VRPIRF) to solve the problem. The purpose of the model is to plan the routes for the boats to meet the diesel requests of the platform. Given the fact that in the literature, papers about the VRPIRF are scarce and papers about the VRPIRF applied to offshore platforms were not found in the published papers, this paper is important to contribute with the evolution of this class of problem, bringing also a solution for a real application that is very important for the oil and gas business. The mathematical model was tested using the CPLEX 12.6. In order to assess the mathematical model, tests were done with data from the major Brazilian oil and gas company and several strategies were tested. (Author)
Decentralized flight trajectory planning of multiple aircraft
Yokoyama, Nobuhiro; 横山 信宏
2008-01-01
Conventional decentralized algorithms for optimal trajectory planning tend to require prohibitive computational time as the number of aircraft increases. To overcome this drawback, this paper proposes a novel decentralized trajectory planning algorithm adopting a constraints decoupling approach for parallel optimization. The constraints decoupling approach is formulated as the path constraints of the real-time trajectory optimization problem based on nonlinear programming. Due to the parallel...
Al-Khatib, Sana M; Calkins, Hugh; Eloff, Benjamin C; Packer, Douglas L; Ellenbogen, Kenneth A; Hammill, Stephen C; Natale, Andrea; Page, Richard L; Prystowsky, Eric; Jackman, Warren M; Stevenson, William G; Waldo, Albert L; Wilber, David; Kowey, Peter; Yaross, Marcia S; Mark, Daniel B; Reiffel, James; Finkle, John K; Marinac-Dabic, Danica; Pinnow, Ellen; Sager, Phillip; Sedrakyan, Art; Canos, Daniel; Gross, Thomas; Berliner, Elise; Krucoff, Mitchell W
2010-01-01
Atrial fibrillation (AF) is a major public health problem in the United States that is associated with increased mortality and morbidity. Of the therapeutic modalities available to treat AF, the use of percutaneous catheter ablation of AF is expanding rapidly. Randomized clinical trials examining the efficacy and safety of AF ablation are currently underway; however, such trials can only partially determine the safety and durability of the effect of the procedure in routine clinical practice, in more complex patients, and over a broader range of techniques and operator experience. These limitations of randomized trials of AF ablation, particularly with regard to safety issues, could be addressed using a synergistically structured national registry, which is the intention of the SAFARI. To facilitate discussions about objectives, challenges, and steps for such a registry, the Cardiac Safety Research Consortium and the Duke Clinical Research Institute, Durham, NC, in collaboration with the US Food and Drug Administration, the American College of Cardiology, and the Heart Rhythm Society, organized a Think Tank meeting of experts in the field. Other participants included the National Heart, Lung and Blood Institute, the Centers for Medicare and Medicaid Services, the Agency for Healthcare Research and Quality, the Society of Thoracic Surgeons, the AdvaMed AF working group, and additional industry representatives. The meeting took place on April 27 to 28, 2009, at the US Food and Drug Administration headquarters in Silver Spring, MD. This article summarizes the issues and directions presented and discussed at the meeting. Copyright 2010 Mosby, Inc. All rights reserved.
Khrapko, R.I.
1985-01-01
A uniform description of various path-dependent functions is presented with the help of expansion of the type of the Taylor series. So called ''path-integrals'' and ''path-tensor'' are introduced which are systems of many-component quantities whose values are defined for arbitrary paths in coordinated region of space in such a way that they contain a complete information on the path. These constructions are considered as elementary path-dependent functions and are used instead of power monomials in the usual Taylor series. Coefficients of such an expansion are interpreted as partial derivatives dependent on the order of the differentiations or else as nonstandard cavariant derivatives called two-point derivatives. Some examples of pathdependent functions are presented.Space curvature tensor is considered whose geometrica properties are determined by the (non-transitive) translator of parallel transport of a general type. Covariant operation leading to the ''extension'' of tensor fiels is pointed out
Path Integrals in Quantum Mechanics
Louko, J
2005-01-01
Jean Zinn-Justin's textbook Path Integrals in Quantum Mechanics aims to familiarize the reader with the path integral as a calculational tool in quantum mechanics and field theory. The emphasis is on quantum statistical mechanics, starting with the partition function Tr exp(-β H) and proceeding through the diffusion equation to barrier penetration problems and their semiclassical limit. The 'real time' path integral is defined via analytic continuation and used for the path-integral representation of the nonrelativistic S-matrix and its perturbative expansion. Holomorphic and Grassmannian path integrals are introduced and applied to nonrelativistic quantum field theory. There is also a brief discussion of path integrals in phase space. The introduction includes a brief historical review of path integrals, supported by a bibliography with some 40 entries. As emphasized in the introduction, mathematical rigour is not a central issue in the book. This allows the text to present the calculational techniques in a very readable manner: much of the text consists of worked-out examples, such as the quartic anharmonic oscillator in the barrier penetration chapter. At the end of each chapter there are exercises, some of which are of elementary coursework type, but the majority are more in the style of extended examples. Most of the exercises indeed include the solution or a sketch thereof. The book assumes minimal previous knowledge of quantum mechanics, and some basic quantum mechanical notation is collected in an appendix. The material has a large overlap with selected chapters in the author's thousand-page textbook Quantum Field Theory and Critical Phenomena (2002 Oxford: Clarendon). The stand-alone scope of the present work has, however, allowed a more focussed organization of this material, especially in the chapters on, respectively, holomorphic and Grassmannian path integrals. In my view the book accomplishes its aim admirably and is eminently usable as a textbook
Iterated Leavitt Path Algebras
Hazrat, R.
2009-11-01
Leavitt path algebras associate to directed graphs a Z-graded algebra and in their simplest form recover the Leavitt algebras L(1,k). In this note, we introduce iterated Leavitt path algebras associated to directed weighted graphs which have natural ± Z grading and in their simplest form recover the Leavitt algebras L(n,k). We also characterize Leavitt path algebras which are strongly graded. (author)
STATE AND PROBLEMS TRAINING, ADVANCED TRAINING AND RETRAINING IN THE FIELD OF LAND PLANNING
Tretiak A.
2016-05-01
Full Text Available Scientific and technological progress and improve land relations, land use and organization of work makes the need for systematic improvement of forms and methods of preparation, training and retraining in the land. Training in the land - is the formation of staff knowledge and skills in a particular professional field, that training people who want to get a profession in the field of land relations and the use and protection of land and other natural resources. In this connection the question the quality of the professionals who work in the system of land and land management enterprises. So in recent years, the system of land worked by 25 thousand. People .. to 28 thousand. People. The number of employees of DerzhzemahenstvaUkraine(and today DerzhheokadastruUkraine ranged from 9.5 - 10 thousand. People. Thus, in stateenterprisesLandManagement Institute, Centre of state land cadastre and land management of private enterprises and entrepreneurs are about 18 thousand. People. In the system of fixed services is almost 90% of workers with higher education. But of these, only about about 70% have higher education universities III-IV accreditation levels, and only about 50% - land management. Managers and professionals who have land management and land use close to education up together with the Bachelor education only 64% of the total number of employees. Thus, the problem of professional education in the field of land is very relevant. It is necessary to consider further training of land-management education for integrated communities. The article is justification for expanding areas of training in the field of land management and the introduction of new professions (specializations and the management of natural areas. According to Article 66 of the Law of Ukraine "On Land Management" of 22.05.2003 number 858-IV, professional activities in the field of land may engage citizens with special higher education levels and appropriate professional