Artificial neural network controller for automatic ship berthing using head-up coordinate system

Directory of Open Access Journals (Sweden)

Nam-Kyun Im

2018-05-01

Full Text Available The Artificial Neural Network (ANN model has been known as one of the most effective theories for automatic ship berthing, as it has learning ability and mimics the actions of the human brain when performing the stages of ship berthing. However, existing ANN controllers can only bring a ship into a berth in a certain port, where the inputs of the ANN are the same as those of the teaching data. This means that those ANN controllers must be retrained when the ship arrives to a new port, which is time-consuming and costly. In this research, by using the head-up coordinate system, which includes the relative bearing and distance from the ship to the berth, a novel ANN controller is proposed to automatically control the ship into the berth in different ports without retraining the ANN structure. Numerical simulations were performed to verify the effectiveness of the proposed controller. First, teaching data were created in the original port to train the neural network; then, the controller was tested for automatic berthing in other ports, where the initial conditions of the inputs in the head-up coordinate system were similar to those of the teaching data in the original port. The results showed that the proposed controller has good performance for ship berthing in ports. Keywords: Automatic ship berthing, ANN controller, Head-up coordinate system, Low speed, Relative bearing

Fund allocation using capacitated vehicle routing problem

Science.gov (United States)

Mamat, Nur Jumaadzan Zaleha; Jaaman, Saiful Hafizah; Ahmad, Rokiah Rozita; Darus, Maslina

2014-09-01

In investment fund allocation, it is unwise for an investor to distribute his fund into several assets simultaneously due to economic reasons. One solution is to allocate the fund into a particular asset at a time in a sequence that will either maximize returns or minimize risks depending on the investor's objective. The vehicle routing problem (VRP) provides an avenue to this issue. VRP answers the question on how to efficiently use the available fleet of vehicles to meet a given service demand, subjected to a set of operational requirements. This paper proposes an idea of using capacitated vehicle routing problem (CVRP) to optimize investment fund allocation by employing data of selected stocks in the FTSE Bursa Malaysia. Results suggest that CRVP can be applied to solve the issue of investment fund allocation and increase the investor's profit.

Properties and solution methods for large location-allocation problems

DEFF Research Database (Denmark)

Juel, Henrik; Love, Robert F.

1982-01-01

Location-allocation with l$ _p$ distances is studied. It is shown that this structure can be expressed as a concave minimization programming problem. Since concave minimization algorithms are not yet well developed, five solution methods are developed which utilize the special properties of the l......Location-allocation with l$ _p$ distances is studied. It is shown that this structure can be expressed as a concave minimization programming problem. Since concave minimization algorithms are not yet well developed, five solution methods are developed which utilize the special properties...... of the location-allocation problem. Using the rectilinear distance measure, two of these algorithms achieved optimal solutions in all 102 test problems for which solutions were known. The algorithms can be applied to much larger problems than any existing exact methods....

Fuel consumption and associated emissions from seagoing ships at berth derived from an on-board survey

NARCIS (Netherlands)

Hulskotte, J.H.J.; Denier van der Gon, H.A.C.

2010-01-01

A methodology is presented to estimate the emissions of ships at berth based on their actual fuel consumption and the fuel quality. Accurate estimates of emissions from ships at berth demand reliable knowledge of the fuel consumption while at berth and associated fuel characteristics. However,

A trust-based sensor allocation algorithm in cooperative space search problems

Science.gov (United States)

Shen, Dan; Chen, Genshe; Pham, Khanh; Blasch, Erik

2011-06-01

Sensor allocation is an important and challenging problem within the field of multi-agent systems. The sensor allocation problem involves deciding how to assign a number of targets or cells to a set of agents according to some allocation protocol. Generally, in order to make efficient allocations, we need to design mechanisms that consider both the task performers' costs for the service and the associated probability of success (POS). In our problem, the costs are the used sensor resource, and the POS is the target tracking performance. Usually, POS may be perceived differently by different agents because they typically have different standards or means of evaluating the performance of their counterparts (other sensors in the search and tracking problem). Given this, we turn to the notion of trust to capture such subjective perceptions. In our approach, we develop a trust model to construct a novel mechanism that motivates sensor agents to limit their greediness or selfishness. Then we model the sensor allocation optimization problem with trust-in-loop negotiation game and solve it using a sub-game perfect equilibrium. Numerical simulations are performed to demonstrate the trust-based sensor allocation algorithm in cooperative space situation awareness (SSA) search problems.

Reliability allocation problem in a series-parallel system

International Nuclear Information System (INIS)

Yalaoui, Alice; Chu, Chengbin; Chatelet, Eric

2005-01-01

In order to improve system reliability, designers may introduce in a system different technologies in parallel. When each technology is composed of components in series, the configuration belongs to the series-parallel systems. This type of system has not been studied as much as the parallel-series architecture. There exist no methods dedicated to the reliability allocation in series-parallel systems with different technologies. We propose in this paper theoretical and practical results for the allocation problem in a series-parallel system. Two resolution approaches are developed. Firstly, a one stage problem is studied and the results are exploited for the multi-stages problem. A theoretical condition for obtaining the optimal allocation is developed. Since this condition is too restrictive, we secondly propose an alternative approach based on an approximated function and the results of the one-stage study. This second approach is applied to numerical examples

Analysis of dangerous area of single berth oil tanker operations based on CFD

Science.gov (United States)

Shi, Lina; Zhu, Faxin; Lu, Jinshu; Wu, Wenfeng; Zhang, Min; Zheng, Hailin

2018-04-01

Based on the single process in the liquid cargo tanker berths in the state as the research object, we analyzed the single berth oil tanker in the process of VOCs diffusion theory, built network model of VOCs diffusion with Gambit preprocessor, set up the simulation boundary conditions and simulated the five detection point sources in specific factors under the influence of VOCs concentration change with time by using Fluent software. We analyzed the dangerous area of single berth oil tanker operations through the diffusion of VOCs, so as to ensure the safe operation of oil tanker.

A Generalization of the Aumann-Shapley Value for Risk Capital Allocation Problems

NARCIS (Netherlands)

Boonen, T.J.; De Waegenaere, A.M.B.; Norde, H.W.

2012-01-01

Abstract: This paper analyzes risk capital allocation problems. For risk capital allocation problems, the aim is to allocate the risk capital of a firm to its divisions. Risk capital allocation is of central importance in risk-based performance measurement. We consider a case in which the aggregate

Efficient exact optimization of multi-objective redundancy allocation problems in series-parallel systems

International Nuclear Information System (INIS)

Cao, Dingzhou; Murat, Alper; Chinnam, Ratna Babu

2013-01-01

This paper proposes a decomposition-based approach to exactly solve the multi-objective Redundancy Allocation Problem for series-parallel systems. Redundancy allocation problem is a form of reliability optimization and has been the subject of many prior studies. The majority of these earlier studies treat redundancy allocation problem as a single objective problem maximizing the system reliability or minimizing the cost given certain constraints. The few studies that treated redundancy allocation problem as a multi-objective optimization problem relied on meta-heuristic solution approaches. However, meta-heuristic approaches have significant limitations: they do not guarantee that Pareto points are optimal and, more importantly, they may not identify all the Pareto-optimal points. In this paper, we treat redundancy allocation problem as a multi-objective problem, as is typical in practice. We decompose the original problem into several multi-objective sub-problems, efficiently and exactly solve sub-problems, and then systematically combine the solutions. The decomposition-based approach can efficiently generate all the Pareto-optimal solutions for redundancy allocation problems. Experimental results demonstrate the effectiveness and efficiency of the proposed method over meta-heuristic methods on a numerical example taken from the literature.

Target berthing and base reorientation of free-floating space robotic system after capturing

Science.gov (United States)

Xu, Wenfu; Li, Cheng; Liang, Bin; Xu, Yangsheng; Liu, Yu; Qiang, Wenyi

2009-01-01

Space robots are playing an increasingly important role in on-orbital servicing, including repairing, refueling, or de-orbiting the satellite. The target must be captured and berthed before the servicing task starts. However, the attitude of the base may lean much and needs re-orientating after capturing. In this paper, a method is proposed to berth the target, and re-orientate the base at the same time, using manipulator motion only. Firstly, the system state is formed of the attitude quaternion and joint variables, and the joint paths are parameterized by sinusoidal functions. Then, the trajectory planning is transformed to an optimization problem. The cost function, defined according to the accuracy requirements of system variables, is the function of the parameters to be determined. Finally, we solve the parameters using the particle swarm optimization algorithm. Two typical cases of the spacecraft with a 6-DOF manipulator are dynamically simulated, one is that the variation of base attitude is limited; the other is that both the base attitude and the joint rates are constrained. The simulation results verify the presented method.

Optimizing investment fund allocation using vehicle routing problem framework

Science.gov (United States)

Mamat, Nur Jumaadzan Zaleha; Jaaman, Saiful Hafizah; Ahmad, Rokiah Rozita

2014-07-01

The objective of investment is to maximize total returns or minimize total risks. To determine the optimum order of investment, vehicle routing problem method is used. The method which is widely used in the field of resource distribution shares almost similar characteristics with the problem of investment fund allocation. In this paper we describe and elucidate the concept of using vehicle routing problem framework in optimizing the allocation of investment fund. To better illustrate these similarities, sectorial data from FTSE Bursa Malaysia is used. Results show that different values of utility for risk-averse investors generate the same investment routes.

Guidance and Control of Position and Attitude for Rendezvous and Dock/Berthing with a Noncooperative/Target Spacecraft

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Gilberto Arantes

2014-01-01

Full Text Available Noncooperative target spacecrafts are those assets in orbit that cannot convey any information about their states (position, attitude, and velocities or facilitate rendezvous and docking/berthing (RVD/B process. Designing a guidance, navigation, and control (GNC module for the chaser in a RVD/B mission with noncooperative target should be inevitably solved for on-orbit servicing technologies. The proximity operations and the guidance for achieving rendezvous problems are addressed in this paper. The out-of-plane maneuvers of proximity operations are explored with distinct subphases, including a chaser far approach in the target’s orbit to the first hold point and a closer approach to the final berthing location. Accordingly, guidance solutions are chosen for each subphase from the standard Hill based Closhessy-Willtshire (CW solution, elliptical fly-around, and Glideslope algorithms. The control is based on a linear quadratic regulator approach (LQR. At the final berthing location, attitude tracker based on a proportional derivative (PD form is tested to synchronize the chaser and target attitudes. The paper analyzes the performance of both controllers in terms of the tracking ability and the robustness. Finally, it prescribes any restrictions that may be imposed on the guidance during any subphase which can help to improve the controllers tracking ability.

Practical Solutions for Reducing Container Ships’ Waiting Times at Ports Using Simulation Model

Institute of Scientific and Technical Information of China (English)

Abdorreza Sheikholeslami; Gholamreza Ilati; Yones Eftekhari Yeganeh

2013-01-01

The main challenge for container ports is the planning required for berthing container ships while docked in port. Growth of containerization is creating problems for ports and container terminals as they reach their capacity limits of various resources which increasingly leads to traffic and port congestion. Good planning and management of container terminal operations reduces waiting time for liner ships. Reducing the waiting time improves the terminal’s productivity and decreases the port difficulties. Two important keys to reducing waiting time with berth allocation are determining suitable access channel depths and increasing the number of berths which in this paper are studied and analyzed as practical solutions. Simulation based analysis is the only way to understand how various resources interact with each other and how they are affected in the berthing time of ships. We used the Enterprise Dynamics software to produce simulation models due to the complexity and nature of the problems. We further present case study for berth allocation simulation of the biggest container terminal in Iran and the optimum access channel depth and the number of berths are obtained from simulation results. The results show a significant reduction in the waiting time for container ships and can be useful for major functions in operations and development of container ship terminals.

Some dynamic resource allocation problems in wireless networks

Science.gov (United States)

Berry, Randall

2001-07-01

We consider dynamic resource allocation problems that arise in wireless networking. Specifically transmission scheduling problems are studied in cases where a user can dynamically allocate communication resources such as transmission rate and power based on current channel knowledge as well as traffic variations. We assume that arriving data is stored in a transmission buffer, and investigate the trade-off between average transmission power and average buffer delay. A general characterization of this trade-off is given and the behavior of this trade-off in the regime of asymptotically large buffer delays is explored. An extension to a more general utility based quality of service definition is also discussed.

Analysis of Protection Measures for Naval Vessels Berthed at Harbor Against Terrorist Attacks

Science.gov (United States)

2016-06-01

of discriminating neutral vessels from threats. A naval vessel berthed at harbor is more susceptible to attack than a vessel in open seas. The...discriminating neutral vessels from threats. A naval vessel berthed at harbor is more susceptible to attack than a vessel in open seas. The chances of...this thesis. He was a source of inspiration, encouragement, and reassurance. Captain Jeffery E. Kline, I am really thankful to you for your ideas

76 FR 38155 - California State Nonroad Engine Pollution Control Standards; Ocean-Going Vessels At-Berth in...

Science.gov (United States)

2011-06-29

... ENVIRONMENTAL PROTECTION AGENCY [FRL-9426-9] California State Nonroad Engine Pollution Control... toxic control measures for auxiliary diesel engines operated on ocean-going vessels at-berth in... control measures (ATCM) for auxiliary diesel engines operated on ocean-going vessels at-berth in...

Ship nonlinear-feedback course keeping algorithm based on MMG model driven by bipolar sigmoid function for berthing

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Qiang Zhang

2017-09-01

Full Text Available Course keeping is hard to implement under the condition of the propeller stopping or reversing at slow speed for berthing due to the ship's dynamic motion becoming highly nonlinear. To solve this problem, a practical Maneuvering Modeling Group (MMG ship mathematic model with propeller reversing transverse forces and low speed correction is first discussed to be applied for the right-handed single-screw ship. Secondly, a novel PID-based nonlinear feedback algorithm driven by bipolar sigmoid function is proposed. The PID parameters are determined by a closed-loop gain shaping algorithm directly, while the closed-loop gain shaping theory was employed for effects analysis of this algorithm. Finally, simulation experiments were carried out on an LPG ship. It is shown that the energy consumption and the smoothness performance of the nonlinear feedback control are reduced by 4.2% and 14.6% with satisfactory control effects; the proposed algorithm has the advantages of robustness, energy saving and safety in berthing practice.

Resource allocation on computational grids using a utility model and the knapsack problem

CERN Document Server

Van der ster, Daniel C; Parra-Hernandez, Rafael; Sobie, Randall J

2009-01-01

This work introduces a utility model (UM) for resource allocation on computational grids and formulates the allocation problem as a variant of the 0–1 multichoice multidimensional knapsack problem. The notion of task-option utility is introduced, and it is used to effect allocation policies. We present a variety of allocation policies, which are expressed as functions of metrics that are both intrinsic and external to the task and resources. An external user-defined credit-value metric is shown to allow users to intervene in the allocation of urgent or low priority tasks. The strategies are evaluated in simulation against random workloads as well as those drawn from real systems. We measure the sensitivity of the UM-derived schedules to variations in the allocation policies and their corresponding utility functions. The UM allocation strategy is shown to optimally allocate resources congruent with the chosen policies.

Vehicle routing problem in investment fund allocation

Science.gov (United States)

Mamat, Nur Jumaadzan Zaleha; Jaaman, Saiful Hafizah; Ahmad, Rokiah Rozita; Mohd, Ismail

2013-04-01

Since its introduction by Dantzig and Ramser in 1959, vehicle routing problem keeps evolving in theories, applications and variability. The evolution in computing and technology are also important contributors to research in solving vehicle routing problem. The main sectors of interests among researchers and practitioners for vehicle routing problem are transportation, distribution and logistics. However, literature found that concept and benefits of vehicle routing problem are not taken advantages of by researchers in the field of investment. Other methods found used in investment include multi-objective programming, linear programming, goal programming and integer programming. Yet the application of vehicle routing problem is not fully explored. A proposal on a framework of the fund allocation optimization using vehicle routing problem is presented here. Preliminary results using FTSE Bursa Malaysia data testing the framework are also given.

Econophysics of a ranked demand and supply resource allocation problem

Science.gov (United States)

Priel, Avner; Tamir, Boaz

2018-01-01

We present a two sided resource allocation problem, between demands and supplies, where both parties are ranked. For example, in Big Data problems where a set of different computational tasks is divided between a set of computers each with its own resources, or between employees and employers where both parties are ranked, the employees by their fitness and the employers by their package benefits. The allocation process can be viewed as a repeated game where in each iteration the strategy is decided by a meta-rule, based on the ranks of both parties and the results of the previous games. We show the existence of a phase transition between an absorbing state, where all demands are satisfied, and an active one where part of the demands are always left unsatisfied. The phase transition is governed by the ratio between supplies and demand. In a job allocation problem we find positive correlation between the rank of the workers and the rank of the factories; higher rank workers are usually allocated to higher ranked factories. These all suggest global emergent properties stemming from local variables. To demonstrate the global versus local relations, we introduce a local inertial force that increases the rank of employees in proportion to their persistence time in the same factory. We show that such a local force induces non trivial global effects, mostly to benefit the lower ranked employees.

Bandwidth allocation and pricing problem for a duopoly market

Directory of Open Access Journals (Sweden)

You Peng-Sheng

2011-01-01

Full Text Available This research discusses the Internet service provider (ISP bandwidth allocation and pricing problems for a duopoly bandwidth market with two competitive ISPs. According to the contracts between Internet subscribers and ISPs, Internet subscribers can enjoy their services up to their contracted bandwidth limits. However, in reality, many subscribers may experience the facts that their on-line requests are denied or their connection speeds are far below their contracted speed limits. One of the reasons is that ISPs accept too many subscribers as their subscribers. To avoid this problem, ISPs can set limits for their subscribers to enhance their service qualities. This paper develops constrained nonlinear programming to deal with this problem for two competitive ISPs. The condition for reaching the equilibrium between the two competitive firms is derived. The market equilibrium price and bandwidth resource allocations are derived as closed form solutions.

Hydrodynamic loads of sea waves on horizontal elements of berths with wave quenching chambers

Directory of Open Access Journals (Sweden)

Leshchenko Sergey Vladimirovich

2014-05-01

Full Text Available In the process of hydraulic structures design, in particular berths with wave cancelling structures, which serve to decrease the wave impact on structures, there appears a problem of vertical wave hydrodynamic loads calculation on floor slabs. In the existing normative documents there are no requirements on calculating vertical wave loads on the horizontal floor slabs of open-type structures (enveloping, mooring, approach trestles, etc. and stairs of sloping-staired open-type structures. A mathematical model is proposed for calculation of the vertical wave loads on the floor slab through moorings. The model is based on the theory of jet impact on a solid surface. The width of the wave crest, striking in the overlap of the pier, and its vertical velocity is determined by the linear wave theory. The coefficient of transmission of waves through wave quenching chambers is calculated according to the previously developed methods. Vertical wave loading is adjusted based on the ratio of the wave length and width of the overlay. Model validation is performed according to the hydraulic modelling interaction of waves with through berths in the port of Tuapse. 7 variants of their design were considered. Data mapping mathematical and hydraulic modeling showed them a close match.

Models of resource allocation optimization when solving the control problems in organizational systems

Science.gov (United States)

Menshikh, V.; Samorokovskiy, A.; Avsentev, O.

2018-03-01

The mathematical model of optimizing the allocation of resources to reduce the time for management decisions and algorithms to solve the general problem of resource allocation. The optimization problem of choice of resources in organizational systems in order to reduce the total execution time of a job is solved. This problem is a complex three-level combinatorial problem, for the solving of which it is necessary to implement the solution to several specific problems: to estimate the duration of performing each action, depending on the number of performers within the group that performs this action; to estimate the total execution time of all actions depending on the quantitative composition of groups of performers; to find such a distribution of the existing resource of performers in groups to minimize the total execution time of all actions. In addition, algorithms to solve the general problem of resource allocation are proposed.

Partial safety factors for berthing velocity and loads on marine structures

NARCIS (Netherlands)

Roubos, A.A.; Peters, D.J.; Groenewegen, Leon; Steenbergen, R.

2018-01-01

Design methods for marine structures have evolved into load and resistance factor design, however existing partial safety factors related to berthing velocity and loads have not been verified and validated by measurement campaigns. In this study, field observations of modern seagoing vessels

Improved Models to Integrated Berth Allocation-Quay Crane Assignment Problem: A Computational Comparison and Novel Solution Approaches

DEFF Research Database (Denmark)

Iris, Cagatay; Pacino, Dario; Røpke, Stefan

of the vessels primarily depends on the number of containers to be handled and the number of cranes deployed, it would be beneficial to consider the integration of those two problems. This work extends the state-of-the-art by strengthening the current best mathematical formulation. Computational experiments...

A Compromise Programming Model for Highway Maintenance Resources Allocation Problem

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Hui Xiong

2012-01-01

Full Text Available This paper formulates a bilevel compromise programming model for allocating resources between pavement and bridge deck maintenances. The first level of the model aims to solve the resource allocation problems for pavement management and bridge deck maintenance, without considering resource sharing between them. At the second level, the model uses the results from the first step as an input and generates the final solution to the resource-sharing problem. To solve the model, the paper applies genetic algorithms to search for the optimal solution. We use a combination of two digits to represent different maintenance types. Results of numerical examples show that the conditions of both pavements and bridge decks are improved significantly by applying compromise programming, rather than conventional methods. Resources are also utilized more efficiently when the proposed method is applied.

A robust optimisation approach to the problem of supplier selection and allocation in outsourcing

Science.gov (United States)

Fu, Yelin; Keung Lai, Kin; Liang, Liang

2016-03-01

We formulate the supplier selection and allocation problem in outsourcing under an uncertain environment as a stochastic programming problem. Both the decision-maker's attitude towards risk and the penalty parameters for demand deviation are considered in the objective function. A service level agreement, upper bound for each selected supplier's allocation and the number of selected suppliers are considered as constraints. A novel robust optimisation approach is employed to solve this problem under different economic situations. Illustrative examples are presented with managerial implications highlighted to support decision-making.

Research on allocation efficiency of the daisy chain allocation algorithm

Science.gov (United States)

Shi, Jingping; Zhang, Weiguo

2013-03-01

With the improvement of the aircraft performance in reliability, maneuverability and survivability, the number of the control effectors increases a lot. How to distribute the three-axis moments into the control surfaces reasonably becomes an important problem. Daisy chain method is simple and easy to be carried out in the design of the allocation system. But it can not solve the allocation problem for entire attainable moment subset. For the lateral-directional allocation problem, the allocation efficiency of the daisy chain can be directly measured by the area of its subset of attainable moments. Because of the non-linear allocation characteristic, the subset of attainable moments of daisy-chain method is a complex non-convex polygon, and it is difficult to solve directly. By analyzing the two-dimensional allocation problems with a "micro-element" idea, a numerical calculation algorithm is proposed to compute the area of the non-convex polygon. In order to improve the allocation efficiency of the algorithm, a genetic algorithm with the allocation efficiency chosen as the fitness function is proposed to find the best pseudo-inverse matrix.

A dynamic programming algorithm for the space allocation and aisle positioning problem

DEFF Research Database (Denmark)

Bodnar, Peter; Lysgaard, Jens

2014-01-01

The space allocation and aisle positioning problem (SAAPP) in a material handling system with gravity flow racks is the problem of minimizing the total number of replenishments over a period subject to practical constraints related to the need for aisles granting safe and easy access to storage...

Distributed Services with Foreseen and Unforeseen Tasks: The Mobile Re-allocation Problem

NARCIS (Netherlands)

J.A. Larco Martinelli (Jose); R. Dekker (Rommert); U. Kaymak (Uzay)

2007-01-01

textabstractIn this paper we deal with a common problem found in the operations of security and preventive/corrective maintenance services: that of routing a number of mobile resources to serve foreseen and unforeseen tasks during a shift. We define the (Mobile Re-Allocation Problem) MRAP as the

A genetic algorithm approach to optimization for the radiological worker allocation problem

International Nuclear Information System (INIS)

Yan Chen; Masakuni Narita; Masashi Tsuji; Sangduk Sa

1996-01-01

The worker allocation optimization problem in radiological facilities inevitably involves various types of requirements and constraints relevant to radiological protection and labor management. Some of these goals and constraints are not amenable to a rigorous mathematical formulation. Conventional methods for this problem rely heavily on sophisticated algebraic or numerical algorithms, which cause difficulties in the search for optimal solutions in the search space of worker allocation optimization problems. Genetic algorithms (GAB) are stochastic search algorithms introduced by J. Holland in the 1970s based on ideas and techniques from genetic and evolutionary theories. The most striking characteristic of GAs is the large flexibility allowed in the formulation of the optimal problem and the process of the search for the optimal solution. In the formulation, it is not necessary to define the optimal problem in rigorous mathematical terms, as required in the conventional methods. Furthermore, by designing a model of evolution for the optimal search problem, the optimal solution can be sought efficiently with computational simple manipulations without highly complex mathematical algorithms. We reported a GA approach to the worker allocation problem in radiological facilities in the previous study. In this study, two types of hard constraints were employed to reduce the huge search space, where the optimal solution is sought in such a way as to satisfy as many of soft constraints as possible. It was demonstrated that the proposed evolutionary method could provide the optimal solution efficiently compared with conventional methods. However, although the employed hard constraints could localize the search space into a very small region, it brought some complexities in the designed genetic operators and demanded additional computational burdens. In this paper, we propose a simplified evolutionary model with less restrictive hard constraints and make comparisons between

Two-stage simplified swarm optimization for the redundancy allocation problem in a multi-state bridge system

International Nuclear Information System (INIS)

Lai, Chyh-Ming; Yeh, Wei-Chang

2016-01-01

The redundancy allocation problem involves configuring an optimal system structure with high reliability and low cost, either by alternating the elements with more reliable elements and/or by forming them redundantly. The multi-state bridge system is a special redundancy allocation problem and is commonly used in various engineering systems for load balancing and control. Traditional methods for redundancy allocation problem cannot solve multi-state bridge systems efficiently because it is impossible to transfer and reduce a multi-state bridge system to series and parallel combinations. Hence, a swarm-based approach called two-stage simplified swarm optimization is proposed in this work to effectively and efficiently solve the redundancy allocation problem in a multi-state bridge system. For validating the proposed method, two experiments are implemented. The computational results indicate the advantages of the proposed method in terms of solution quality and computational efficiency. - Highlights: • Propose two-stage SSO (SSO_T_S) to deal with RAP in multi-state bridge system. • Dynamic upper bound enhances the efficiency of searching near-optimal solution. • Vector-update stages reduces the problem dimensions. • Statistical results indicate SSO_T_S is robust both in solution quality and runtime.

The Ordered Capacitated Multi-Objective Location-Allocation Problem for Fire Stations Using Spatial Optimization

Directory of Open Access Journals (Sweden)

Samira Bolouri

2018-01-01

Full Text Available Determining the positions of facilities, and allocating demands to them, is a vitally important problem. Location-allocation problems are optimization NP-hard procedures. This article evaluates the ordered capacitated multi-objective location-allocation problem for fire stations, using simulated annealing and a genetic algorithm, with goals such as minimizing the distance and time as well as maximizing the coverage. After tuning the parameters of the algorithms using sensitivity analysis, they were used separately to process data for Region 11, Tehran. The results showed that the genetic algorithm was more efficient than simulated annealing, and therefore, the genetic algorithm was used in later steps. Next, we increased the number of stations. Results showed that the model can successfully provide seven optimal locations and allocate high demands (280,000 to stations in a discrete space in a GIS, assuming that the stations’ capacities are known. Following this, we used a weighting program so that in each repetition, we could allot weights to each target randomly. Finally, by repeating the model over 10 independent executions, a set of solutions with the least sum and the highest number of non-dominated solutions was selected from among many non-dominated solutions as the best set of optimal solutions.

Reliability–redundancy allocation problem considering optimal redundancy strategy using parallel genetic algorithm

International Nuclear Information System (INIS)

Kim, Heungseob; Kim, Pansoo

2017-01-01

To maximize the reliability of a system, the traditional reliability–redundancy allocation problem (RRAP) determines the component reliability and level of redundancy for each subsystem. This paper proposes an advanced RRAP that also considers the optimal redundancy strategy, either active or cold standby. In addition, new examples are presented for it. Furthermore, the exact reliability function for a cold standby redundant subsystem with an imperfect detector/switch is suggested, and is expected to replace the previous approximating model that has been used in most related studies. A parallel genetic algorithm for solving the RRAP as a mixed-integer nonlinear programming model is presented, and its performance is compared with those of previous studies by using numerical examples on three benchmark problems. - Highlights: • Optimal strategy is proposed to solve reliability redundancy allocation problem. • The redundancy strategy uses parallel genetic algorithm. • Improved reliability function for a cold standby subsystem is suggested. • Proposed redundancy strategy enhances the system reliability.

Uncertain multiobjective redundancy allocation problem of repairable systems based on artificial bee colony algorithm

Institute of Scientific and Technical Information of China (English)

Guo Jiansheng; Wang Zutong; Zheng Mingfa; Wang Ying

2014-01-01

Based on the uncertainty theory, this paper is devoted to the redundancy allocation problem in repairable parallel-series systems with uncertain factors, where the failure rate, repair rate and other relative coefficients involved are considered as uncertain variables. The availability of the system and the corresponding designing cost are considered as two optimization objectives. A crisp multiobjective optimization formulation is presented on the basis of uncertainty theory to solve this resultant problem. For solving this problem efficiently, a new multiobjective artificial bee colony algorithm is proposed to search the Pareto efficient set, which introduces rank value and crowding distance in the greedy selection strategy, applies fast non-dominated sort procedure in the exploitation search and inserts tournament selection in the onlooker bee phase. It shows that the proposed algorithm outperforms NSGA-II greatly and can solve multiobjective redundancy allocation problem efficiently. Finally, a numerical example is provided to illustrate this approach.

A Non-Cooperative Approach to the Joint Subcarrier and Power Allocation Problem in Multi-Service SCFDMA Networks

Directory of Open Access Journals (Sweden)

E. E. Tsiropoulou

2016-06-01

Full Text Available In this paper a joint resource allocation problem is studied in a multi-service Single Carrier FDMA (SC-FDMA wireless network. Mobile users request various services with different Quality of Service (QoS characteristics and they determine in a distributed and non-cooperative manner a joint subcarrier and power allocation towards fulfilling their QoS prerequisites. Initially, a well-designed utility function is formulated to appropriately represent users’ diverse QoS prerequisites with respect to their requested service. The subcarriers allocation problem is solved based on a multilateral bargaining model, where users are able to select different discount factors to enter the bargaining game, thus better expressing their different needs in system resources with respect to their requested service. The subcarriers mapping is realized based either on the localized SC-FDMA method where the subcarriers are sequentially allocated to the users or the distributed SC-FDMA via considering the maximum channel gain policy, where each subcarrier is allocated to the user with the maximum channel gain. Given the subcarriers assignment, an optimization problem with respect to users’ uplink transmission power is formulated and solved, in order to determine the optimal power allocation per subcarrier assigned to each user. Finally, the performance of the proposed framework is evaluated via modeling and simulation and extensive numerical results are presented.

Application of goal programming to decision problem on optimal allocation of radiation workers

International Nuclear Information System (INIS)

Sa, Sangduk; Narita, Masakuni

1993-01-01

This paper is concerned with an optimal planning in a multiple objective decision-making problem of allocating radiation workers to workplaces associated with occupational exposure. The model problem is formulated with the application of goal programming which effectively followed up diverse and conflicting factors influencing the optimal decision. The formulation is based on the data simulating the typical situations encountered at the operating facilities such as nuclear power plants where exposure control is critical to the management. Multiple goals set by the decision-maker/manager who has the operational responsibilities for radiological protection are illustrated in terms of work requirements, exposure constraints of the places, desired allocation of specific personnel and so on. Test results of the model are considered to indicate that the model structure and its solution process can provide the manager with a good set of analysis of his problems in implementing the optimization review of radiation protection during normal operation. (author)

Emissions allocation in transportation routes

NARCIS (Netherlands)

Leenders, B.P.J.; Velázquez Martínez, J.; Fransoo, J.C.

2017-01-01

This article studies the allocation of CO2 emissions to a specific shipment in routing transportation. The authors show that this problem differs from a cost allocation problem specifically because the concavity condition does not hold necessarily in the CO2 allocation problem. This implies that a

Bidding for surplus in network allocation problems

NARCIS (Netherlands)

Slikker, M.

2007-01-01

In this paper we study non-cooperative foundations of network allocation rules. We focus on three allocation rules: the Myerson value, the position value and the component-wise egalitarian solution. For any of these three rules we provide a characterization based on component efficiency and some

Transport Infrastructure Slot Allocation

NARCIS (Netherlands)

Koolstra, K.

2005-01-01

In this thesis, transport infrastructure slot allocation has been studied, focusing on selection slot allocation, i.e. on longer-term slot allocation decisions determining the traffic patterns served by infrastructure bottlenecks, rather than timetable-related slot allocation problems. The

Multiobjective optimal allocation problem with probabilistic non ...

African Journals Online (AJOL)

user

In multivariate stratified sampling where more than one characteristic are to be estimated, an allocation which is optimum for one characteristic may not be optimum for other characteristics also. In such situations a compromise criterion is needed to work out a usable allocation which is optimum for all characteristics in some ...

Simulation for assessment of bulk cargo berths number

Science.gov (United States)

Kuznetsov, A. L.; Kirichenko, A. V.; Slitsan, A. E.

2017-10-01

The world trade volumes of mineral resources have been growing constantly for decades, notwithstanding any economical crises. At the same time, the proximity of the bulk materials as products to the starting point of the integrated value added or logistic supply chain makes their unit price relatively low. This fact automatically causes a strong economic sensitivity of the supply chain to the level of operational expenses in every link. The core of the integrated logistic supply chain is its maritime segment, with the fleet and terminals (i.e. the cargo transportation system) serving as the base platform for it. In its turn, the terminal berths play a role of the interface between the fleet and the land-transportation sub-system. Current development of the maritime transportation technologies, ships and terminal specialization, vessel size growth, rationalization of route patterns, regionalization of trade etc., has made conventional calculation methods inadequate. The solution of the problem is in using object oriented simulation. At the same time, this approch usually assumes only ad hoc models. Thus, it does not provide the generality of its conventional analytical predecessors. The time and labor consumpting procedure of simulation results in a very narrow application domain of the model. This article describes a new simulation instrument, combining the generality of the analytical technoques with the efficiency of the object-oriented simulation. The approach implemented as a software module, which validity and adequacy are proved. The software was tested on several sea terminal design projects and confirmed its efficiency.

Counting, scoring and classifying hunger to allocate resources targeted to solve the problem

OpenAIRE

Afonso Gallegos, Ana; Trueba Jainaga, Jose Ignacio; Tarancon Juanas, Monica

2011-01-01

A proper allocation of resources targeted to solve hunger is essential to optimize the efficacy of actions and maximize results. This requires an adequate measurement and formulation of the problem as, paraphrasing Einstein, the formulation of a problem is essential to reach a solution. Different measurement methods have been designed to count, score, classify and compare hunger at local level and to allow comparisons between different places. However, the alternative methods produce sig...

Memory allocation and computations for Laplace’s equation of 3-D arbitrary boundary problems

Directory of Open Access Journals (Sweden)

Tsay Tswn-Syau

2017-01-01

Full Text Available Computation iteration schemes and memory allocation technique for finite difference method were presented in this paper. The transformed form of a groundwater flow problem in the generalized curvilinear coordinates was taken to be the illustrating example and a 3-dimensional second order accurate 19-point scheme was presented. Traditional element-by-element methods (e.g. SOR are preferred since it is simple and memory efficient but time consuming in computation. For efficient memory allocation, an index method was presented to store the sparse non-symmetric matrix of the problem. For computations, conjugate-gradient-like methods were reported to be computationally efficient. Among them, using incomplete Choleski decomposition as preconditioner was reported to be good method for iteration convergence. In general, the developed index method in this paper has the following advantages: (1 adaptable to various governing and boundary conditions, (2 flexible for higher order approximation, (3 independence of problem dimension, (4 efficient for complex problems when global matrix is not symmetric, (5 convenience for general sparse matrices, (6 computationally efficient in the most time consuming procedure of matrix multiplication, and (7 applicable to any developed matrix solver.

A heuristic for solving the redundancy allocation problem for multi-state series-parallel systems

International Nuclear Information System (INIS)

Ramirez-Marquez, Jose E.; Coit, David W.

2004-01-01

The redundancy allocation problem is formulated with the objective of minimizing design cost, when the system exhibits a multi-state reliability behavior, given system-level performance constraints. When the multi-state nature of the system is considered, traditional solution methodologies are no longer valid. This study considers a multi-state series-parallel system (MSPS) with capacitated binary components that can provide different multi-state system performance levels. The different demand levels, which must be supplied during the system-operating period, result in the multi-state nature of the system. The new solution methodology offers several distinct benefits compared to traditional formulations of the MSPS redundancy allocation problem. For some systems, recognizing that different component versions yield different system performance is critical so that the overall system reliability estimation and associated design models the true system reliability behavior more realistically. The MSPS design problem, solved in this study, has been previously analyzed using genetic algorithms (GAs) and the universal generating function. The specific problem being addressed is one where there are multiple component choices, but once a component selection is made, only the same component type can be used to provide redundancy. This is the first time that the MSPS design problem has been addressed without using GAs. The heuristic offers more efficient and straightforward analyses. Solutions to three different problem types are obtained illustrating the simplicity and ease of application of the heuristic without compromising the intended optimization needs

A new model for the redundancy allocation problem with component mixing and mixed redundancy strategy

International Nuclear Information System (INIS)

Gholinezhad, Hadi; Zeinal Hamadani, Ali

2017-01-01

This paper develops a new model for redundancy allocation problem. In this paper, like many recent papers, the choice of the redundancy strategy is considered as a decision variable. But, in our model each subsystem can exploit both active and cold-standby strategies simultaneously. Moreover, the model allows for component mixing such that components of different types may be used in each subsystem. The problem, therefore, boils down to determining the types of components, redundancy levels, and number of active and cold-standby units of each type for each subsystem to maximize system reliability by considering such constraints as available budget, weight, and space. Since RAP belongs to the NP-hard class of optimization problems, a genetic algorithm (GA) is developed for solving the problem. Finally, the performance of the proposed algorithm is evaluated by applying it to a well-known test problem from the literature with relatively satisfactory results. - Highlights: • A new model for the redundancy allocation problem in series–parallel systems is proposed. • The redundancy strategy of each subsystem is considered as a decision variable and can be active, cold-standby or mixed. • Component mixing is allowed, in other words components of any subsystem can be non-identical. • A genetic algorithm is developed for solving the problem. • Computational experiments demonstrate that the new model leads to interesting results.

Redundancy allocation problem of a system with increasing failure rates of components based on Weibull distribution: A simulation-based optimization approach

International Nuclear Information System (INIS)

Guilani, Pedram Pourkarim; Azimi, Parham; Niaki, S.T.A.; Niaki, Seyed Armin Akhavan

2016-01-01

The redundancy allocation problem (RAP) is a useful method to enhance system reliability. In most works involving RAP, failure rates of the system components are assumed to follow either exponential or k-Erlang distributions. In real world problems however, many systems have components with increasing failure rates. This indicates that as time passes by, the failure rates of the system components increase in comparison to their initial failure rates. In this paper, the redundancy allocation problem of a series–parallel system with components having an increasing failure rate based on Weibull distribution is investigated. An optimization method via simulation is proposed for modeling and a genetic algorithm is developed to solve the problem. - Highlights: • The redundancy allocation problem of a series–parallel system is aimed. • Components possess an increasing failure rate based on Weibull distribution. • An optimization method via simulation is proposed for modeling. • A genetic algorithm is developed to solve the problem.

Cost allocation in distribution planning

International Nuclear Information System (INIS)

Engevall, S.

1996-01-01

This thesis concerns cost allocation problems in distribution planning. The cost allocation problems we study are illustrated using the distribution planning situation at the Logistics department of Norsk Hydro Olje AB. The planning situation is modeled as a Traveling Salesman Problem and a Vehicle Routing Problem with an inhomogeneous fleet. The cost allocation problems are the problems of how to divide the transportation costs among the customers served in each problem. The cost allocation problems are formulated as cooperative games, in characteristic function form, where the customers are defined to be the players. The games contain five and 21 players respectively. Game theoretical solution concepts such as the core, the nucleolus, the Shapley value and the τ-value are discussed. From the empirical results we can, among other things, conclude that the core of the Traveling Salesman Game is large, and that the core of the Vehicle Routing Game is empty. In the accounting of Norsk Hydro the cost per m 3 can be found for each tour. We conclude that for a certain definition of the characteristic function, a cost allocation according to this principle will not be included in the core of the Traveling Salesman Game. The models and methods presented in this thesis can be applied to transportation problems similar to that of Norsk Hydro, independent of the type of products that are delivered. 96 refs, 11 figs, 26 tabs

Cost allocation in distribution planning

Energy Technology Data Exchange (ETDEWEB)

Engevall, S.

1996-12-31

This thesis concerns cost allocation problems in distribution planning. The cost allocation problems we study are illustrated using the distribution planning situation at the Logistics department of Norsk Hydro Olje AB. The planning situation is modeled as a Traveling Salesman Problem and a Vehicle Routing Problem with an inhomogeneous fleet. The cost allocation problems are the problems of how to divide the transportation costs among the customers served in each problem. The cost allocation problems are formulated as cooperative games, in characteristic function form, where the customers are defined to be the players. The games contain five and 21 players respectively. Game theoretical solution concepts such as the core, the nucleolus, the Shapley value and the {tau}-value are discussed. From the empirical results we can, among other things, conclude that the core of the Traveling Salesman Game is large, and that the core of the Vehicle Routing Game is empty. In the accounting of Norsk Hydro the cost per m{sup 3} can be found for each tour. We conclude that for a certain definition of the characteristic function, a cost allocation according to this principle will not be included in the core of the Traveling Salesman Game. The models and methods presented in this thesis can be applied to transportation problems similar to that of Norsk Hydro, independent of the type of products that are delivered. 96 refs, 11 figs, 26 tabs

Cost allocation in distribution planning

Energy Technology Data Exchange (ETDEWEB)

Engevall, S

1997-12-31

This thesis concerns cost allocation problems in distribution planning. The cost allocation problems we study are illustrated using the distribution planning situation at the Logistics department of Norsk Hydro Olje AB. The planning situation is modeled as a Traveling Salesman Problem and a Vehicle Routing Problem with an inhomogeneous fleet. The cost allocation problems are the problems of how to divide the transportation costs among the customers served in each problem. The cost allocation problems are formulated as cooperative games, in characteristic function form, where the customers are defined to be the players. The games contain five and 21 players respectively. Game theoretical solution concepts such as the core, the nucleolus, the Shapley value and the {tau}-value are discussed. From the empirical results we can, among other things, conclude that the core of the Traveling Salesman Game is large, and that the core of the Vehicle Routing Game is empty. In the accounting of Norsk Hydro the cost per m{sup 3} can be found for each tour. We conclude that for a certain definition of the characteristic function, a cost allocation according to this principle will not be included in the core of the Traveling Salesman Game. The models and methods presented in this thesis can be applied to transportation problems similar to that of Norsk Hydro, independent of the type of products that are delivered. 96 refs, 11 figs, 26 tabs

Optimal allocation of resources in systems

International Nuclear Information System (INIS)

Derman, C.; Lieberman, G.J.; Ross, S.M.

1975-01-01

In the design of a new system, or the maintenance of an old system, allocation of resources is of prime consideration. In allocating resources it is often beneficial to develop a solution that yields an optimal value of the system measure of desirability. In the context of the problems considered in this paper the resources to be allocated are components already produced (assembly problems) and money (allocation in the construction or repair of systems). The measure of desirability for system assembly will usually be maximizing the expected number of systems that perform satisfactorily and the measure in the allocation context will be maximizing the system reliability. Results are presented for these two types of general problems in both a sequential (when appropriate) and non-sequential context

HERMES docking/berthing system pilot study. Quantitative assessment

International Nuclear Information System (INIS)

Munoz Blasco, J.; Goicoechea Sanchez, F.J.

1993-01-01

This study falls within the framework of the incorporation of quantitative risk assessment to the activities planned for the ESA-HERMES project (ESA/ CNES). The main objective behind the study was the analysis and evaluation of the potential contribution of so-called probabilistic or quantitative safety analysis to the optimization of the safety development process for the systems carrying out the safety functions required by the new and complex HERMES Space Vehicle. For this purpose, a pilot study was considered a good start in quantitative safety assessments (QSA), as this approach has been frequently used in the past to establish a solid base in large-scale QSA application programs while avoiding considerable economic risks. It was finally decided to select the HERMES docking/berthing system with Man Tender Free Flyer as the case-study. This report describes the different steps followed in the study, along with the main insights obtained and the general conclusions drawn from the study results. (author)

Modeling Multioperator Multi-UAV Operator Attention Allocation Problem Based on Maximizing the Global Reward

Directory of Open Access Journals (Sweden)

Yuhang Wu

2016-01-01

Full Text Available This paper focuses on the attention allocation problem (AAP in modeling multioperator multi-UAV (MOMU, with the operator model and task properties taken into consideration. The model of MOMU operator AAP based on maximizing the global reward is established and used to allocate tasks to all operators as well as set work time and rest time to each task simultaneously for operators. The proposed model is validated in Matlab simulation environment, using the immune algorithm and dynamic programming algorithm to evaluate the performance of the model in terms of the reward value with regard to the work time, rest time, and task allocation. The result shows that the total reward of the proposed model is larger than the one obtained from previously published methods using local maximization and the total reward of our method has an exponent-like relation with the task arrival rate. The proposed model can improve the operators’ task processing efficiency in the MOMU command and control scenarios.

Coupling ant colony and the degraded ceiling algorithm for the redundancy allocation problem of series-parallel systems

International Nuclear Information System (INIS)

Nahas, Nabil; Nourelfath, Mustapha; Ait-Kadi, Daoud

2007-01-01

The redundancy allocation problem (RAP) is a well known NP-hard problem which involves the selection of elements and redundancy levels to maximize system reliability given various system-level constraints. As telecommunications and internet protocol networks, manufacturing and power systems are becoming more and more complex, while requiring short developments schedules and very high reliability, it is becoming increasingly important to develop efficient solutions to the RAP. This paper presents an efficient algorithm to solve this reliability optimization problem. The idea of a heuristic approach design is inspired from the ant colony meta-heuristic optimization method and the degraded ceiling local search technique. Our hybridization of the ant colony meta-heuristic with the degraded ceiling performs well and is competitive with the best-known heuristics for redundancy allocation. Numerical results for the 33 test problems from previous research are reported and compared. The solutions found by our approach are all better than or are in par with the well-known best solutions

Risk capital allocation

DEFF Research Database (Denmark)

Hougaard, Jens Leth; Smilgins, Aleksandrs

Risk capital allocation problems have been widely discussed in the academic literature. We consider a company with multiple subunits having individual portfolios. Hence, when portfolios of subunits are merged, a diversification benefit arises: the risk of the company as a whole is smaller than...... the sum of the risks of the individual sub-units. The question is how to allocate the risk capital of the company among the subunits in a fair way. In this paper we propose to use the Lorenz set as an allocation method. We show that the Lorenz set is operational and coherent. Moreover, we propose a set...... of new axioms related directly to the problem of risk capital allocation and show that the Lorenz set satisfies these new axioms in contrast to other well-known coherent methods. Finally, we discuss how to deal with non-uniqueness of the Lorenz set....

Multicriterion problem of allocation of resources in the heterogeneous distributed information processing systems

Science.gov (United States)

Antamoshkin, O. A.; Kilochitskaya, T. R.; Ontuzheva, G. A.; Stupina, A. A.; Tynchenko, V. S.

2018-05-01

This study reviews the problem of allocation of resources in the heterogeneous distributed information processing systems, which may be formalized in the form of a multicriterion multi-index problem with the linear constraints of the transport type. The algorithms for solution of this problem suggest a search for the entire set of Pareto-optimal solutions. For some classes of hierarchical systems, it is possible to significantly speed up the procedure of verification of a system of linear algebraic inequalities for consistency due to the reducibility of them to the stream models or the application of other solution schemes (for strongly connected structures) that take into account the specifics of the hierarchies under consideration.

Indistinguishability Operators Applied to Task Allocation Problems in Multi-Agent Systems

Directory of Open Access Journals (Sweden)

José Guerrero

2017-09-01

Full Text Available In this paper we show an application of indistinguishability operators to model response functions. Such functions are used in the mathematical modeling of the task allocation problem in multi-agent systems when the stimulus, perceived by the agent, to perform a task is assessed by means of the response threshold model. In particular, we propose this kind of operators to represent a response function when the stimulus only depends on the distance between the agent and a determined task, since we prove that two celebrated response functions used in the literature can be reproduced by appropriate indistinguishability operators when the stimulus only depends on the distance to each task that must be carried out. Despite the fact there is currently no systematic method to generate response functions, this paper provides, for the first time, a theoretical foundation to generate them and study their properties. To validate the theoretical results, the aforementioned indistinguishability operators have been used to simulate, with MATLAB, the allocation of a set of tasks in a multi-robot system with fuzzy Markov chains.

A dynamic programming algorithm for the buffer allocation problem in homogeneous asymptotically reliable serial production lines

Directory of Open Access Journals (Sweden)

Diamantidis A. C.

2004-01-01

Full Text Available In this study, the buffer allocation problem (BAP in homogeneous, asymptotically reliable serial production lines is considered. A known aggregation method, given by Lim, Meerkov, and Top (1990, for the performance evaluation (i.e., estimation of throughput of this type of production lines when the buffer allocation is known, is used as an evaluative method in conjunction with a newly developed dynamic programming (DP algorithm for the BAP. The proposed algorithm is applied to production lines where the number of machines is varying from four up to a hundred machines. The proposed algorithm is fast because it reduces the volume of computations by rejecting allocations that do not lead to maximization of the line's throughput. Numerical results are also given for large production lines.

Performance impact of mutation operators of a subpopulation-based genetic algorithm for multi-robot task allocation problems.

Science.gov (United States)

Liu, Chun; Kroll, Andreas

2016-01-01

Multi-robot task allocation determines the task sequence and distribution for a group of robots in multi-robot systems, which is one of constrained combinatorial optimization problems and more complex in case of cooperative tasks because they introduce additional spatial and temporal constraints. To solve multi-robot task allocation problems with cooperative tasks efficiently, a subpopulation-based genetic algorithm, a crossover-free genetic algorithm employing mutation operators and elitism selection in each subpopulation, is developed in this paper. Moreover, the impact of mutation operators (swap, insertion, inversion, displacement, and their various combinations) is analyzed when solving several industrial plant inspection problems. The experimental results show that: (1) the proposed genetic algorithm can obtain better solutions than the tested binary tournament genetic algorithm with partially mapped crossover; (2) inversion mutation performs better than other tested mutation operators when solving problems without cooperative tasks, and the swap-inversion combination performs better than other tested mutation operators/combinations when solving problems with cooperative tasks. As it is difficult to produce all desired effects with a single mutation operator, using multiple mutation operators (including both inversion and swap) is suggested when solving similar combinatorial optimization problems.

Economics and the refinery's CO2 emissions allocation problem

International Nuclear Information System (INIS)

Pierru, A.

2007-01-01

The establishment of a market for CO 2 emission rights in Europe leads oil-refining companies to add a cost associated with carbon emissions to the objective function of linear programming models used to manage refineries. These models may be used to compute the marginal contribution of each finished product to the CO 2 emissions of the refinery. Babusiaux (Oil. Gas Sci. Technol., 58, 2003, 685-692) has shown that, under some conditions, this marginal contribution is a relevant means of allocating the carbon emissions of the refinery. Thus, it can be used in a well-to-wheel Life Cycle Assessment. In fact, this result holds if the demand equations are the only binding constraints with a non-zero right-hand side coefficient. This is not the case for short-run models with fixed capacity. Then, allocating CO 2 emissions on a marginal basis tends to over-value (or undervalue) the total volume of emissions. In order to extend the existing methodology, we discuss two distinct solutions to this problem, inspired by economic theory: adapting either the Aumann-Shapley cost sharing method (Values of non-atomic games, 1974, Princeton University Press) or the Ramsey pricing formula (Econ. J., 37, 1927, 47-61; J. Econ. Theory, 3, 1971, 219-240). We compare these two solutions, with a strong argument in favour of Ramsey prices, based on the determination of the optimal environmental tax rate to which imported finished products should be subject. (author)

Quayside Operations Planning Under Uncertainty

DEFF Research Database (Denmark)

Iris, Cagatay; Jin, Jian Gang; Lee, Der-Hong

The quayside operation problem is one of the key components in the management system for a container terminal. This work focuses on three important problems that represent a bottleneck on terminal operations: Berth Allocation Problem (BAP), Quay Crane Assignment and Scheduling Problems (QCASP......).The state-of-art models mostly rely on forecasted, deterministic vessel arrivals, and they mostly assume that uniform QC operations is maintained. However, in reality, these parameters are mostly random. In this study, we present a stochastic programming approach based on a decomposition algorithm to solve...

Simulation-Based Optimization for Storage Allocation Problem of Outbound Containers in Automated Container Terminals

Directory of Open Access Journals (Sweden)

Ning Zhao

2015-01-01

Full Text Available Storage allocation of outbound containers is a key factor of the performance of container handling system in automated container terminals. Improper storage plans of outbound containers make QC waiting inevitable; hence, the vessel handling time will be lengthened. A simulation-based optimization method is proposed in this paper for the storage allocation problem of outbound containers in automated container terminals (SAPOBA. A simulation model is built up by Timed-Colored-Petri-Net (TCPN, used to evaluate the QC waiting time of storage plans. Two optimization approaches, based on Particle Swarm Optimization (PSO and Genetic Algorithm (GA, are proposed to form the complete simulation-based optimization method. Effectiveness of this method is verified by experiment, as the comparison of the two optimization approaches.

Participation behavior and social welfare in repeated task allocations

NARCIS (Netherlands)

Ye, Q.C.; Zhang, Y.

2016-01-01

Task allocation problems have focused on achieving one-shot optimality. In practice, many task allocation problems are of repeated nature, where the allocation outcome of previous rounds may influence the participation of agents in subsequent rounds, and consequently, the quality of the allocations

Solving a Location, Allocation, and Capacity Planning Problem with Dynamic Demand and Response Time Service Level

Directory of Open Access Journals (Sweden)

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.

Two-Stage Multiobjective Optimization for Emergency Supplies Allocation Problem under Integrated Uncertainty

Directory of Open Access Journals (Sweden)

Xuejie Bai

2016-01-01

Full Text Available This paper proposes a new two-stage optimization method for emergency supplies allocation problem with multisupplier, multiaffected area, multirelief, and multivehicle. The triplet of supply, demand, and the availability of path is unknown prior to the extraordinary event and is descriptive with fuzzy random variable. Considering the fairness, timeliness, and economical efficiency, a multiobjective expected value model is built for facility location, vehicle routing, and supply allocation decisions. The goals of proposed model aim to minimize the proportion of demand nonsatisfied and response time of emergency reliefs and the total cost of the whole process. When the demand and the availability of path are discrete, the expected values in the objective functions are converted into their equivalent forms. When the supply amount is continuous, the equilibrium chance in the constraint is transformed to its equivalent one. To overcome the computational difficulty caused by multiple objectives, a goal programming model is formulated to obtain a compromise solution. Finally, an example is presented to illustrate the validity of the proposed model and the effectiveness of the solution method.

Fuzzy bicriteria multi-index transportation problems for coal allocation planning of Taipower

International Nuclear Information System (INIS)

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

Online Job Allocation with Hard Allocation Ratio Requirement (Author’s Manuscript)

Science.gov (United States)

2016-04-14

server divided by its capacity. Specifically , let nj be the number of jobs that have already been allocated to server j. When job i arrives, it is...decisions solely based on current system state is needed. The problem of online job allocation has attracted much attention . Most current studies study...closed-form expressions for their performance. Specifically , we prove that, in order to allocate at least 1− 1θ of jobs , the two policies only need to

Arithmetic and algebraic problem solving and resource allocation: the distinct impact of fluid and numerical intelligence.

Science.gov (United States)

Dix, Annika; van der Meer, Elke

2015-04-01

This study investigates cognitive resource allocation dependent on fluid and numerical intelligence in arithmetic/algebraic tasks varying in difficulty. Sixty-six 11th grade students participated in a mathematical verification paradigm, while pupil dilation as a measure of resource allocation was collected. Students with high fluid intelligence solved the tasks faster and more accurately than those with average fluid intelligence, as did students with high compared to average numerical intelligence. However, fluid intelligence sped up response times only in students with average but not high numerical intelligence. Further, high fluid but not numerical intelligence led to greater task-related pupil dilation. We assume that fluid intelligence serves as a domain-general resource that helps to tackle problems for which domain-specific knowledge (numerical intelligence) is missing. The allocation of this resource can be measured by pupil dilation. Copyright © 2014 Society for Psychophysiological Research.

A Novel Joint Problem of Routing, Scheduling, and Variable-Width Channel Allocation in WMNs

Directory of Open Access Journals (Sweden)

Chun-Cheng Lin

2014-01-01

Full Text Available This paper investigates a novel joint problem of routing, scheduling, and channel allocation for single-radio multichannel wireless mesh networks in which multiple channel widths can be adjusted dynamically through a new software technology so that more concurrent transmissions and suppressed overlapping channel interference can be achieved. Although the previous works have studied this joint problem, their linear programming models for the problem were not incorporated with some delicate constraints. As a result, this paper first constructs a linear programming model with more practical concerns and then proposes a simulated annealing approach with a novel encoding mechanism, in which the configurations of multiple time slots are devised to characterize the dynamic transmission process. Experimental results show that our approach can find the same or similar solutions as the optimal solutions for smaller-scale problems and can efficiently find good-quality solutions for a variety of larger-scale problems.

Allocation of resources in the presence of indivisibilities: Scarf's problem revisited

International Nuclear Information System (INIS)

Bjoerndal, Mette; Joernsten, Kurt

2004-06-01

In his article ''The Allocation of Resources in the Presence of Indivisibilities,'' Scarf points out that the major problem presented to economic theory by the presence of indivisibilities is the impossibility of detecting optimality at the level of the firm, or the economy as a whole, using the creation of profitability based on competitive linear prices. In the absence of such competitive prices, Scarf instead introduces a quantity test. Further development of the quantity test idea has lead to algorithms that are used to solve parametric integer programming problems. However, the quantity test is not a fully acceptable replacement of prices to analyse markets with indivisibilities. Recently, O'Neill et al. have suggested a new scheme that generates discriminatory equilibrium prices in markets with non-convexities- In this paper we elaborate this idea even further and use it to generate non-linear price functions that can be interpreted as a non-linear pricing scheme for markets with non-convexities. (Author)

Treatment of uncertainties in the existence of free berths with risk analysis techniques. Establishment of policies in port of Cadiz (SPAIN)

Energy Technology Data Exchange (ETDEWEB)

Awad Nuñez, S.; Camarero Orive, A.; Romero Sanchez-Brunete, M.; Camarero Orive, A.; Gonzalez Cancelas, N.

2016-07-01

This research discusses the challenges involved in the treatment of uncertainties in the existence of free berths during the arrival of cruise ships at seaports. Pursuing this goal, a three-step methodology is adopted: 1) Identifying risk sources and critical risk variables and how they are related; 2) Fitting the Probability Distribution Functions that best represent the behaviour of each critical risk variable; and 3) Simulating the probability of a ship having to wait because there are no free berths using a technique that combines statistical concepts (random sampling) with the ability of computers to generate pseudo-random numbers and automate estimations of the values of the set of critical risk variables. The innovative use of risk analysis techniques in this field allows the establishment of policies to improve the planning and management of port infrastructure, for example, deciding when it is necessary to work to increase the number of berths. As a case of study, we applied this methodology to study whether the enlargement of the wharf in the port of Cadiz (Spain) is necessary right now considering the number of cruise ships that have arrived at the port in the past three years, their date and hour of arrival, their length and draught, the duration of their stay in port and their waiting time before being able to enter the port. This action would require moving logistics activities to a new terminal, but would bring to the city the opportunity to rethink the seafront, introducing new cruiser links with the city centre and developing a better seaport-city integration. (Author)

Multiobjective optimal allocation problem with probabilistic non ...

African Journals Online (AJOL)

This paper considers the optimum compromise allocation in multivariate stratified sampling with non-linear objective function and probabilistic non-linear cost constraint. The probabilistic non-linear cost constraint is converted into equivalent deterministic one by using Chance Constrained programming. A numerical ...

A hybrid Jaya algorithm for reliability-redundancy allocation problems

Science.gov (United States)

Ghavidel, Sahand; Azizivahed, Ali; Li, Li

2018-04-01

This article proposes an efficient improved hybrid Jaya algorithm based on time-varying acceleration coefficients (TVACs) and the learning phase introduced in teaching-learning-based optimization (TLBO), named the LJaya-TVAC algorithm, for solving various types of nonlinear mixed-integer reliability-redundancy allocation problems (RRAPs) and standard real-parameter test functions. RRAPs include series, series-parallel, complex (bridge) and overspeed protection systems. The search power of the proposed LJaya-TVAC algorithm for finding the optimal solutions is first tested on the standard real-parameter unimodal and multi-modal functions with dimensions of 30-100, and then tested on various types of nonlinear mixed-integer RRAPs. The results are compared with the original Jaya algorithm and the best results reported in the recent literature. The optimal results obtained with the proposed LJaya-TVAC algorithm provide evidence for its better and acceptable optimization performance compared to the original Jaya algorithm and other reported optimal results.

DYNAMIC PROGRAMMING APPROACH TO TESTING RESOURCE ALLOCATION PROBLEM FOR MODULAR SOFTWARE

Directory of Open Access Journals (Sweden)

P.K. Kapur

2003-02-01

Full Text Available Testing phase of a software begins with module testing. During this period modules are tested independently to remove maximum possible number of faults within a specified time limit or testing resource budget. This gives rise to some interesting optimization problems, which are discussed in this paper. Two Optimization models are proposed for optimal allocation of testing resources among the modules of a Software. In the first model, we maximize the total fault removal, subject to budgetary Constraint. In the second model, additional constraint representing aspiration level for fault removals for each module of the software is added. These models are solved using dynamic programming technique. The methods have been illustrated through numerical examples.

Characterizing contract-based multiagent resource allocation in networks.

Science.gov (United States)

An, Bo; Lesser, Victor

2010-06-01

We consider a multiagent resource allocation problem where individual users intend to route traffic by requesting the help of entities across a network, and a cost is incurred at each network node that depends on the amount of traffic to be routed. We propose to study contract-based network resource allocation. In our model, users and nodes in the network make contracts before nodes route traffic for the users. The problem is an interesting self-interested negotiation problem because it requires the complete assembly of a set of distinct resources, and there are multiple combinations of distinct resources that could satisfy the goal of negotiation. First, we characterize the network allocation problem and show that finding optimal allocations is NP-complete and is inapproximable. We take both Nash equilibrium and pairwise Nash equilibrium as the solution concepts to characterize the equilibrium allocations. We find that, for any resource allocation game, Nash equilibrium and pairwise Nash equilibrium always exist. In addition, socially optimal allocations are always supported by Nash equilibrium and pairwise Nash equilibrium. We introduce best-response dynamics in which each agent takes a myopic best-response strategy and interacts with each other to dynamically form contracts. We analyze the convergence of the dynamics in some special cases. We also experimentally study the convergence rate of the dynamics and how efficient the evolved allocation is as compared with the optimal allocation in a variety of environments.

A New Biobjective Model to Optimize Integrated Redundancy Allocation and Reliability-Centered Maintenance Problems in a System Using Metaheuristics

Directory of Open Access Journals (Sweden)

Shima MohammadZadeh Dogahe

2015-01-01

Full Text Available A novel integrated model is proposed to optimize the redundancy allocation problem (RAP and the reliability-centered maintenance (RCM simultaneously. A system of both repairable and nonrepairable components has been considered. In this system, electronic components are nonrepairable while mechanical components are mostly repairable. For nonrepairable components, a redundancy allocation problem is dealt with to determine optimal redundancy strategy and number of redundant components to be implemented in each subsystem. In addition, a maintenance scheduling problem is considered for repairable components in order to identify the best maintenance policy and optimize system reliability. Both active and cold standby redundancy strategies have been taken into account for electronic components. Also, net present value of the secondary cost including operational and maintenance costs has been calculated. The problem is formulated as a biobjective mathematical programming model aiming to reach a tradeoff between system reliability and cost. Three metaheuristic algorithms are employed to solve the proposed model: Nondominated Sorting Genetic Algorithm (NSGA-II, Multiobjective Particle Swarm Optimization (MOPSO, and Multiobjective Firefly Algorithm (MOFA. Several test problems are solved using the mentioned algorithms to test efficiency and effectiveness of the solution approaches and obtained results are analyzed.

A GA based penalty function technique for solving constrained redundancy allocation problem of series system with interval valued reliability of components

Science.gov (United States)

Gupta, R. K.; Bhunia, A. K.; Roy, D.

2009-10-01

In this paper, we have considered the problem of constrained redundancy allocation of series system with interval valued reliability of components. For maximizing the overall system reliability under limited resource constraints, the problem is formulated as an unconstrained integer programming problem with interval coefficients by penalty function technique and solved by an advanced GA for integer variables with interval fitness function, tournament selection, uniform crossover, uniform mutation and elitism. As a special case, considering the lower and upper bounds of the interval valued reliabilities of the components to be the same, the corresponding problem has been solved. The model has been illustrated with some numerical examples and the results of the series redundancy allocation problem with fixed value of reliability of the components have been compared with the existing results available in the literature. Finally, sensitivity analyses have been shown graphically to study the stability of our developed GA with respect to the different GA parameters.

An efficient simulated annealing algorithm for the redundancy allocation problem with a choice of redundancy strategies

International Nuclear Information System (INIS)

Chambari, Amirhossain; Najafi, Amir Abbas; Rahmati, Seyed Habib A.; Karimi, Aida

2013-01-01

The redundancy allocation problem (RAP) is an important reliability optimization problem. This paper studies a specific RAP in which redundancy strategies are chosen. To do so, the choice of the redundancy strategies among active and cold standby is considered as decision variables. The goal is to select the redundancy strategy, component, and redundancy level for each subsystem such that the system reliability is maximized. Since RAP is a NP-hard problem, we propose an efficient simulated annealing algorithm (SA) to solve it. In addition, to evaluating the performance of the proposed algorithm, it is compared with well-known algorithms in the literature for different test problems. The results of the performance analysis show a relatively satisfactory efficiency of the proposed SA algorithm

Heuristic for solving capacitor allocation problems in electric energy radial distribution networks

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Maria A. Biagio

2012-04-01

Full Text Available The goal of the capacitor allocation problem in radial distribution networks is to minimize technical losses with consequential positive impacts on economic and environmental areas. The main objective is to define the size and location of the capacitors while considering load variations in a given horizon. The mathematical formulation for this planning problem is given by an integer nonlinear mathematical programming model that demands great computational effort to be solved. With the goal of solving this problem, this paper proposes a methodology that is composed of heuristics and Tabu Search procedures. The methodology presented explores network system characteristics of the network system reactive loads for identifying regions where procedures of local and intensive searches should be performed. A description of the proposed methodology and an analysis of computational results obtained which are based on several test systems including actual systems are presented. The solutions reached are as good as or better than those indicated by well referenced methodologies. The technique proposed is simple in its use and does not require calibrating an excessive amount of parameters, making it an attractive alternative for companies involved in the planning of radial distribution networks.

Methodology for allocating reliability and risk

International Nuclear Information System (INIS)

Cho, N.Z.; Papazoglou, I.A.; Bari, R.A.

1986-05-01

This report describes a methodology for reliability and risk allocation in nuclear power plants. The work investigates the technical feasibility of allocating reliability and risk, which are expressed in a set of global safety criteria and which may not necessarily be rigid, to various reactor systems, subsystems, components, operations, and structures in a consistent manner. The report also provides general discussions on the problem of reliability and risk allocation. The problem is formulated as a multiattribute decision analysis paradigm. The work mainly addresses the first two steps of a typical decision analysis, i.e., (1) identifying alternatives, and (2) generating information on outcomes of the alternatives, by performing a multiobjective optimization on a PRA model and reliability cost functions. The multiobjective optimization serves as the guiding principle to reliability and risk allocation. The concept of ''noninferiority'' is used in the multiobjective optimization problem. Finding the noninferior solution set is the main theme of the current approach. The final step of decision analysis, i.e., assessment of the decision maker's preferences could then be performed more easily on the noninferior solution set. Some results of the methodology applications to a nontrivial risk model are provided, and several outstanding issues such as generic allocation, preference assessment, and uncertainty are discussed. 29 refs., 44 figs., 39 tabs

Box-triangular multiobjective linear programs for resource allocation with application to load management and energy market problems

International Nuclear Information System (INIS)

Ekel, P.Y.; Galperin, E.A.

2003-01-01

Models for multicriteria resource allocation are constructed with the specific box-triangular structure of a feasible region. The method of balance set equations is extended for the satisfaction level representation of the cost function space including the case of linearly dependent cost functions. On this basis, different goal criteria on the balance set are investigated for linear cases. Procedures for determining the balance set and finding goal-optimal Pareto solutions are illustrated on examples. The results of the paper are of universal character and can find wide applications in allocating diverse types of resources on the multiobjective basis in planning and control of complex systems including load management and energy market problems. (Author)

Downlink resource allocation for multichannel TDMA visible light communications

KAUST Repository

Abdelhady, Amr Mohamed Abdelaziz; Amin, Osama; Chaaban, Anas; Alouini, Mohamed-Slim

2017-01-01

Optical wireless communications (OWC) in general and resource allocation in OWC networks particularly have gained lots of attention recently. In this work, we consider the resource allocation problem of a visible light communication downlink transmission system based on time division multiple access with the objective of maximizing spectral efficiency (SE). As for the operational conditions, we impose constraints on the average optical intensity, the energy consumption and the quality-of-service. To solve the non-convex problem, we transform the objective function into a difference of concave functions by solving a second order differential inequality. Then, we propose a low-complexity algorithm to solve the resource allocation problem. Finally, we show by simulations the SE performance gains achieved by optimizing the power allocation over equal power allocation in the considered system. Numerical results show the SE gains achieved by using this solution.

Downlink resource allocation for multichannel TDMA visible light communications

KAUST Repository

Abdelhady, Amr Mohamed Abdelaziz

2017-05-12

Optical wireless communications (OWC) in general and resource allocation in OWC networks particularly have gained lots of attention recently. In this work, we consider the resource allocation problem of a visible light communication downlink transmission system based on time division multiple access with the objective of maximizing spectral efficiency (SE). As for the operational conditions, we impose constraints on the average optical intensity, the energy consumption and the quality-of-service. To solve the non-convex problem, we transform the objective function into a difference of concave functions by solving a second order differential inequality. Then, we propose a low-complexity algorithm to solve the resource allocation problem. Finally, we show by simulations the SE performance gains achieved by optimizing the power allocation over equal power allocation in the considered system. Numerical results show the SE gains achieved by using this solution.

Marine environmental radioactivity surveys at nuclear submarine berths 2001

International Nuclear Information System (INIS)

Cowling, E.; Ball, R.; Simpson, C.

2002-01-01

This report presents the results of the marine environmental radioactivity monitoring surveys of intertidal and underwater areas around nuclear submarine berths which were carried out by DRPS during 2001. Also included are results of smaller scale intertidal surveys carried out by local staff but co-ordinated by DRPS. Cobalt-60, the nuclide of major importance in naval discharges, was detected in a number of samples but in many cases was attributable to discharges by other operators. Concentrations in any case were found to be low, and at no survey location did the calculated annual radiation dose commitment to the most exposed members of the general public due to the presence of cobalt-60 exceed 1% of the ICRP principal dose limit for members of the public (1000μSv). These results are consistent with those obtained in the independent monitoring programmes as reported in the Radioactivity in Food and the Environment (RIFE) annual reports. It is concluded that existing discharge arrangements are providing effective control over environmental levels of radioactivity, and that there has been no radiological hazard to any member of the general public during 2001 from the operation of nuclear powered submarines. (author)

SOME NOTES ON COST ALLOCATION IN MULTICASTING

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Darko Skorin-Kapov

2012-12-01

Full Text Available We analyze the cost allocation strategies with the problef of broadcasting information from some source to a number of communication network users. A multicast routing chooses a minimum cost tree network that spans the source and all the receivers. The cost of such a network is distributed among its receivers who may be individuals or organizations with possibly conflicting interests. Providing network developers, users and owners with practical computable 'fair' cost allocation solution procedures is of great importance for network mamagement. Consequently, this multidisciplinary problem was extensively studied by Operational Researchers, Economists, Mathematicians and Computer Scientists. The fairness of various proposed solutions was even argued in US courts. This presentation overviews some previously published, as well as some recent results, in the development of algorithmic mechanisms to efficiently compute 'attractive' cost allocation solutions for multicast networks. Specifically, we will analyze cooperative game theory based cost allocation models that avoid cross subsidies and/or are distance and population monotonic. We will also present some related open cost allocation problems and the potential contribution that such models might make to this problem in the future.

Railway Track Allocation: Models and Methods

DEFF Research Database (Denmark)

Lusby, Richard Martin; Larsen, Jesper; Ehrgott, Matthias

2011-01-01

Efficiently coordinating the movement of trains on a railway network is a central part of the planning process for a railway company. This paper reviews models and methods that have been proposed in the literature to assist planners in finding train routes. Since the problem of routing trains......, and train routing problems, group them by railway network type, and discuss track allocation from a strategic, tactical, and operational level....... on a railway network entails allocating the track capacity of the network (or part thereof) over time in a conflict-free manner, all studies that model railway track allocation in some capacity are considered relevant. We hence survey work on the train timetabling, train dispatching, train platforming...

Railway Track Allocation: Models and Methods

DEFF Research Database (Denmark)

Lusby, Richard Martin; Larsen, Jesper; Ehrgott, Matthias

Eciently coordinating the movement of trains on a railway network is a central part of the planning process for a railway company. This paper reviews models and methods that have been proposed in the literature to assist planners in nding train routes. Since the problem of routing trains......, and train routing problems, group them by railway network type, and discuss track allocation from a strategic, tactical, and operational level....... on a railway network entails allocating the track capacity of the network (or part thereof) over time in a con ict-free manner, all studies that model railway track allocation in some capacity are considered relevant. We hence survey work on the train timetabling, train dispatching, train platforming...

Application of genetic algorithm for reliability allocation in nuclear power plants

International Nuclear Information System (INIS)

Yang, Joon-Eon; Hwang, Mee-Jung; Sung, Tae-Yong; Jin, Youngho

1999-01-01

Reliability allocation is an optimization process of minimizing the total plant costs subject to the overall plant safety goal constraints. Reliability allocation was applied to determine the reliability characteristics of reactor systems, subsystems, major components and plant procedures that are consistent with a set of top-level performance goals; the core melt frequency, acute fatalities and latent fatalities. Reliability allocation can be performed to improve the design, operation and safety of new and/or existing nuclear power plants. Reliability allocation is a kind of a difficult multi-objective optimization problem as well as a global optimization problem. The genetic algorithm, known as one of the most powerful tools for most optimization problems, is applied to the reliability allocation problem of a typical pressurized water reactor in this article. One of the main problems of reliability allocation is defining realistic objective functions. Hence, in order to optimize the reliability of the system, the cost for improving and/or degrading the reliability of the system should be included in the reliability allocation process. We used techniques derived from the value impact analysis to define the realistic objective function in this article

Resource allocation based on cost efficiency

DEFF Research Database (Denmark)

Dehnokhalaji, Akram; Ghiyasi, Mojtaba; Korhonen, Pekka

2017-01-01

-objective linear programming problem using two different strategies. First, we propose an RA model which keeps the cost efficiencies of units unchanged. This is done assuming fixed technical and allocative efficiencies. The approach is based on the assumption that the decision maker (DM) may not have big changes......In this paper, we consider a resource allocation (RA) problem and develop an approach based on cost (overall) efficiency. The aim is to allocate some inputs among decision making units (DMUs) in such way that their cost efficiencies improve or stay unchanged after RA. We formulate a multi...... in the structure of DMUs within a short term. The second strategy does not impose any restrictions on technical and allocative efficiencies. It guarantees that none of the cost efficiencies of DMUs get worse after RA, and the improvement for units is possible if it is feasible and beneficial. Two numerical...

Consistently Trained Artificial Neural Network for Automatic Ship Berthing Control

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Y.A. Ahmed

2015-09-01

Full Text Available In this paper, consistently trained Artificial Neural Network controller for automatic ship berthing is discussed. Minimum time course changing manoeuvre is utilised to ensure such consistency and a new concept named ‘virtual window’ is introduced. Such consistent teaching data are then used to train two separate multi-layered feed forward neural networks for command rudder and propeller revolution output. After proper training, several known and unknown conditions are tested to judge the effectiveness of the proposed controller using Monte Carlo simulations. After getting acceptable percentages of success, the trained networks are implemented for the free running experiment system to judge the network’s real time response for Esso Osaka 3-m model ship. The network’s behaviour during such experiments is also investigated for possible effect of initial conditions as well as wind disturbances. Moreover, since the final goal point of the proposed controller is set at some distance from the actual pier to ensure safety, therefore a study on automatic tug assistance is also discussed for the final alignment of the ship with actual pier.

Joint overbooking and seat allocation for fare families

DEFF Research Database (Denmark)

Hjorth, Robert; Fiig, Thomas; Bondoux, Nicolas

2016-01-01

Revenue Management Systems (RMS) traditionally solve the seat allocation problem separately from the overbooking problem. Overbooking is managed by inflating the authorization levels obtained from seat allocation by various heuristics. This approach although suboptimal, is necessitated because...... independent demand model, which is readily solved. The resulting availability control can easily by implemented in existing RMS...

The Manpower Allocation Problem with Time Windows and Job-Teaming Constraints: A Branch-and-Price Approach

DEFF Research Database (Denmark)

Hansen, Anders Dohn; Kolind, Esben; Clausen, Jens

2009-01-01

In this paper, we consider the Manpower Allocation Problem with Time Windows, Job-Teaming Constraints and a limited number of teams (m-MAPTWTC). Given a set of teams and a set of tasks, the problem is to assign to each team a sequential order of tasks to maximize the total number of assigned tasks....... Both teams and tasks may be restricted by time windows outside which operation is not possible. Some tasks require cooperation between teams, and all teams cooperating must initiate execution simultaneously. We present an IP-model for the problem, which is decomposed using Dantzig-Wolfe decomposition....... The problem is solved by column generation in a Branch-and-Price framework. Simultaneous execution of tasks is enforced by the branching scheme. To test the efficiency of the proposed algorithm, 12 realistic test instances are introduced. The algorithm is able to find the optimal solution in 11 of the test...

Resource allocation in networks via coalitional games

NARCIS (Netherlands)

Shams, F.

2016-01-01

The main goal of this dissertation is to manage resource allocation in network engineering problems and to introduce efficient cooperative algorithms to obtain high performance, ensuring fairness and stability. Specifically, this dissertation introduces new approaches for resource allocation in

Cognitive radio networks dynamic resource allocation schemes

CERN Document Server

Wang, Shaowei

2014-01-01

This SpringerBrief presents a survey of dynamic resource allocation schemes in Cognitive Radio (CR) Systems, focusing on the spectral-efficiency and energy-efficiency in wireless networks. It also introduces a variety of dynamic resource allocation schemes for CR networks and provides a concise introduction of the landscape of CR technology. The author covers in detail the dynamic resource allocation problem for the motivations and challenges in CR systems. The Spectral- and Energy-Efficient resource allocation schemes are comprehensively investigated, including new insights into the trade-off

4G femtocells resource allocation and interference management

CERN Document Server

Zhang, Haijun; Wen, Xiangming

2014-01-01

This brief examines resource allocation and interference management for 4G femtocells. It introduces 4G femtocells in the context of 4G mobile networks and discusses related technical challenges in resource allocation and interference management. Topics include ant colony algorithm based downlink resource allocation, intelligent scheduling and power control, uplink and downlink for two-tier networks, quality of service (QoS) constraints and the cross-tier interference constraint. The authors present algorithms to alleviate common femtocell-related problems such as subchannel power allocation. The complexity of the proposed resource allocation algorithms is analyzed, and the effectiveness of the proposed algorithms is verified by simulations. This concise and practical book directly addresses common problems relating to femtocells and resource management. It serves as a useful tool for researchers in the field. Advanced-level students or professionals interested in femtocells and networks will also find the co...

Resource allocation using ANN in LTE

Science.gov (United States)

Yigit, Tuncay; Ersoy, Mevlut

2017-07-01

LTE is the 4th generation wireless network technology, which provides flexible bandwidth, higher data speeds and lower delay. Difficulties may be experienced upon an increase in the number of users in LTE. The objective of this study is to ensure a faster solution to any such resource allocation problems which might arise upon an increase in the number of users. A fast and effective solution has been obtained by making use of Artificial Neural Network. As a result, fast working artificial intelligence methods may be used in resource allocation problems during operation.

Modelling and Metaheuristic for Gantry Crane Scheduling and Storage Space Allocation Problem in Railway Container Terminals

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Ming Zeng

2017-01-01

Full Text Available The gantry crane scheduling and storage space allocation problem in the main containers yard of railway container terminal is studied. A mixed integer programming model which comprehensively considers the handling procedures, noncrossing constraints, the safety margin and traveling time of gantry cranes, and the storage modes in the main area is formulated. A metaheuristic named backtracking search algorithm (BSA is then improved to solve this intractable problem. A series of computational experiments are carried out to evaluate the performance of the proposed algorithm under some randomly generated cases based on the practical operation conditions. The results show that the proposed algorithm can gain the near-optimal solutions within a reasonable computation time.

Cost Allocation and Convex Data Envelopment

DEFF Research Database (Denmark)

Hougaard, Jens Leth; Tind, Jørgen

such as Data Envelopment Analysis (DEA). The convexity constraint of the BCC model introduces a non-zero slack in the objective function of the multiplier problem and we show that the cost allocation rules discussed in this paper can be used as candidates to allocate this slack value on to the input (or output...

Integrated Yard Space Allocation and Yard Crane Deployment Problem in Resource-Limited Container Terminals

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Caimao Tan

2016-01-01

Full Text Available Yard storage space and yard crane equipment are the core resources in the container terminal yard area. This paper studies the integrated yard space allocation (outbound container space and yard crane deployment problem in resource-limited container terminals where yard space and yard cranes are extremely scarce. Two corresponding counterstrategies are introduced, respectively, and the integrated problem is solved as mixed integer programming. The model this paper formulated considers the container volume fluctuation of the service line, and the objective is a trade-off between yard sharing space and terminal operation cost. In numerical experiments, this paper tries to reveal the management meaning in practical operation of container terminal and provides decision support for terminal managers; therefore a series of scenarios are presented to analyze the relations among the yard sharing space, the number of yard cranes, the size of yard subblock, and the cost of terminal operation.

The kidney allocation score: methodological problems, moral concerns and unintended consequences.

Science.gov (United States)

Hippen, B

2009-07-01

The growing disparity between the demand for and supply of kidneys for transplantation has generated interest in alternative systems of allocating kidneys from deceased donors. This personal viewpoint focuses attention on the Kidney Allocation Score (KAS) proposal promulgated by the UNOS/OPTN Kidney Committee. I identify several methodological and moral flaws in the proposed system, concluding that any iteration of the KAS proposal should be met with more skepticism than sanguinity.

Nash social welfare in multiagent resource allocation

NARCIS (Netherlands)

Ramezani, S.; Endriss, U.; David, E.; Gerding, E.; Sarne, D.; Shehory, O.

2010-01-01

We study different aspects of the multiagent resource allocation problem when the objective is to find an allocation that maximizes Nash social welfare, the product of the utilities of the individual agents. The Nash solution is an important welfare criterion that combines efficiency and fairness

PTM Modeling of Dredged Suspended Sediment at Proposed Polaris Point and Ship Repair Facility CVN Berthing Sites - Apra Harbor, Guam

Science.gov (United States)

2017-09-01

sedimentation outside of the channel footprint. For example, dredging near the edge of the footprint can be confined to time periods when tidal currents...Cases 1 or 2 due to the lower loss rate. Sedimentation rates outside the channel prism are further reduced because all sediment is introduced in the...ER D C/ CH L TR -1 7- 16 PTM Modeling of Dredged Suspended Sediment at Proposed Polaris Point and Ship Repair Facility CVN Berthing

Fund Allocation in Complex Rehabilitation Programs

Directory of Open Access Journals (Sweden)

Tarek Hegazy

2013-12-01

Full Text Available Civil Infrastructure assets require continuous renewal actions to sustain their operability and safety. Allocating limited renewal funds amongst numerous building components, however, represents a large-scale optimization problem and earlier efforts utilized genetic algorithms (GAs to optimize medium size problems yet exhibit steep performance degradation as problem size increases. In this research, after experimenting with various approaches of segmenting a large problem into multiple smaller sub-problems, clustered segmentation proved to be the most promising. The paper discusses the underlying life cycle analysis model, the various segmentation methods, and the optimization results using the improved GAs + clustered segmentation, which proved to be able to optimize asset renewals for 50,000 components with no noticeable performance degradation. The proposed method is simple and logical, and can be used on variety of asset types to improve infrastructure fund allocation. Future extension of this research is then highlighted.

Marine environmental radioactivity surveys at nuclear submarine berths in the UK 1988

International Nuclear Information System (INIS)

1989-10-01

This report presents results of the marine environmental radioactivity monitoring surveys of intertidal and underwater areas around nuclear submarine berths in the UK, including the US Naval Base at Holy Loch, carried out by DRPS during 1988. Also included are results of smaller scale intertidal surveys carried out by local staff but co-ordinated by DRPS, and as an Appendix a report by the US Navy detailing results of their environmental radioactivity monitoring programme at Holy Loch. Cobalt-60, the nuclide of major importance in naval discharges, was detected in a number of samples but in most cases attributable to discharges by other operators. Concentrations in any case were found to be low, and at no survey location did the calculated annual radiation dose commitment to the most exposed members of the general public due to the presence of cobalt-60 exceed 1% of the ICRP principal dose limit for members of the public (1mSv). (author)

Tabu search for the redundancy allocation problem of homogenous series-parallel multi-state systems

International Nuclear Information System (INIS)

Ouzineb, Mohamed; Nourelfath, Mustapha; Gendreau, Michel

2008-01-01

This paper develops an efficient tabu search (TS) heuristic to solve the redundancy allocation problem for multi-state series-parallel systems. The system has a range of performance levels from perfect functioning to complete failure. Identical redundant elements are included in order to achieve a desirable level of availability. The elements of the system are characterized by their cost, performance and availability. These elements are chosen from a list of products available in the market. System availability is defined as the ability to satisfy consumer demand, which is represented as a piecewise cumulative load curve. A universal generating function technique is applied to evaluate system availability. The proposed TS heuristic determines the minimal cost system configuration under availability constraints. An originality of our approach is that it proceeds by dividing the search space into a set of disjoint subsets, and then by applying TS to each subset. The design problem, solved in this study, has been previously analyzed using genetic algorithms (GAs). Numerical results for the test problems from previous research are reported, and larger test problems are randomly generated. Comparisons show that the proposed TS out-performs GA solutions, in terms of both the solution quality and the execution time

Mechanism Design for the Online Allocation of Items without Monetary Payments

NARCIS (Netherlands)

Jalilzadeh, B.; Planken, L.; De Weerdt, M.M.

2010-01-01

We consider online mechanism design without money, where agents are allowed to trade items with other agents, in an attempt to improve their own allocation. In an off-line context, this problem is known as the House Allocation Problem (HAP). We extend HAP to an online problem and call it the Online

Comparison of systems for memory allocation in the C programming language

OpenAIRE

Zavrtanik, Matej

2016-01-01

The bachelor thesis describes memory allocation. Work begins with description of mechanism, system calls and data structures used in memory allocators. Goals of memory allocation ares listed along with problems which must be avoided. Afterwards construction and allocating of popular memory allocators is described. Work ends with comparison of memory allocators based on time of execution of programs and memory usage, on which conclusion is based.

Multi-robot Task Allocation for Search and Rescue Missions

International Nuclear Information System (INIS)

Hussein, Ahmed; Adel, Mohamed; Bakr, Mohamed; Shehata, Omar M; Khamis, Alaa

2014-01-01

Many researchers from academia and industry are attracted to investigate how to design and develop robust versatile multi-robot systems by solving a number of challenging and complex problems such as task allocation, group formation, self-organization and much more. In this study, the problem of multi-robot task allocation (MRTA) is tackled. MRTA is the problem of optimally allocating a set of tasks to a group of robots to optimize the overall system performance while being subjected to a set of constraints. A generic market-based approach is proposed in this paper to solve this problem. The efficacy of the proposed approach is quantitatively evaluated through simulation and real experimentation using heterogeneous Khepera-III mobile robots. The results from both simulation and experimentation indicate the high performance of the proposed algorithms and their applicability in search and rescue missions

Obtaining a Proportional Allocation by Deleting Items

NARCIS (Netherlands)

Dorn, B.; de Haan, R.; Schlotter, I.; Röthe, J.

2017-01-01

We consider the following control problem on fair allocation of indivisible goods. Given a set I of items and a set of agents, each having strict linear preference over the items, we ask for a minimum subset of the items whose deletion guarantees the existence of a proportional allocation in the

Energy-Efficient Power Allocation for MIMO-SVD Systems

KAUST Repository

Sboui, Lokman; Rezki, Zouheir; Alouini, Mohamed-Slim

2017-01-01

In this paper, we address the problem of energyefficient power allocation in MIMO systems. In fact, the widely adopted water-filling power allocation does not ensure the maximization of the energy efficiency (EE). Since the EE maximization is a non

Constrained control allocation for systems with redundant control effectors

OpenAIRE

Bordignon, Kenneth A

1996-01-01

Control allocation is examined for linear time-invariant problems that have more controls than degrees of freedom. The controls are part of a physical system and are subject to limits on their maximum positions. A control allocation scheme commands control deflections in response to some desired output. The ability of a control allocation scheme to produce the desired output without violating the physical position constraints is used to compare allocation schemes. Methods are develop...

Stochastic Resource Allocation for Energy-Constrained Systems

Directory of Open Access Journals (Sweden)

Sachs DanielGrobe

2009-01-01

Full Text Available Battery-powered wireless systems running media applications have tight constraints on energy, CPU, and network capacity, and therefore require the careful allocation of these limited resources to maximize the system's performance while avoiding resource overruns. Usually, resource-allocation problems are solved using standard knapsack-solving techniques. However, when allocating conservable resources like energy (which unlike CPU and network remain available for later use if they are not used immediately knapsack solutions suffer from excessive computational complexity, leading to the use of suboptimal heuristics. We show that use of Lagrangian optimization provides a fast, elegant, and, for convex problems, optimal solution to the allocation of energy across applications as they enter and leave the system, even if the exact sequence and timing of their entrances and exits is not known. This permits significant increases in achieved utility compared to heuristics in common use. As our framework requires only a stochastic description of future workloads, and not a full schedule, we also significantly expand the scope of systems that can be optimized.

An intelligent allocation algorithm for parallel processing

Science.gov (United States)

Carroll, Chester C.; Homaifar, Abdollah; Ananthram, Kishan G.

1988-01-01

The problem of allocating nodes of a program graph to processors in a parallel processing architecture is considered. The algorithm is based on critical path analysis, some allocation heuristics, and the execution granularity of nodes in a program graph. These factors, and the structure of interprocessor communication network, influence the allocation. To achieve realistic estimations of the executive durations of allocations, the algorithm considers the fact that nodes in a program graph have to communicate through varying numbers of tokens. Coarse and fine granularities have been implemented, with interprocessor token-communication duration, varying from zero up to values comparable to the execution durations of individual nodes. The effect on allocation of communication network structures is demonstrated by performing allocations for crossbar (non-blocking) and star (blocking) networks. The algorithm assumes the availability of as many processors as it needs for the optimal allocation of any program graph. Hence, the focus of allocation has been on varying token-communication durations rather than varying the number of processors. The algorithm always utilizes as many processors as necessary for the optimal allocation of any program graph, depending upon granularity and characteristics of the interprocessor communication network.

Analysing collaborative performance and cost allocation for the joint route planning problem

OpenAIRE

Verdonck, Lotte; Ramaekers, Katrien; Depaire, Benoît; Caris, An; Janssens, Gerrit K.

2017-01-01

Although organisations become increasingly aware of the inevitable character of horizontal collaboration, surveys report failure rates up to 70 percent for starting strategic partnerships. While a growing body of research acknowledges the importance of the partner selection and cost allocation process, no extensive study has been performed on the numerical relationship between specific company traits, applied allocation mechanisms and collaborative performance. This paper investigates the imp...

Irrational time allocation in decision-making.

Science.gov (United States)

Oud, Bastiaan; Krajbich, Ian; Miller, Kevin; Cheong, Jin Hyun; Botvinick, Matthew; Fehr, Ernst

2016-01-13

Time is an extremely valuable resource but little is known about the efficiency of time allocation in decision-making. Empirical evidence suggests that in many ecologically relevant situations, decision difficulty and the relative reward from making a correct choice, compared to an incorrect one, are inversely linked, implying that it is optimal to use relatively less time for difficult choice problems. This applies, in particular, to value-based choices, in which the relative reward from choosing the higher valued item shrinks as the values of the other options get closer to the best option and are thus more difficult to discriminate. Here, we experimentally show that people behave sub-optimally in such contexts. They do not respond to incentives that favour the allocation of time to choice problems in which the relative reward for choosing the best option is high; instead they spend too much time on problems in which the reward difference between the options is low. We demonstrate this by showing that it is possible to improve subjects' time allocation with a simple intervention that cuts them off when their decisions take too long. Thus, we provide a novel form of evidence that organisms systematically spend their valuable time in an inefficient way, and simultaneously offer a potential solution to the problem. © 2016 The Author(s).

Reconceptualizing perceptual load as a rate problem: The role of time in the allocation of selective attention.

Science.gov (United States)

Li, Zhi; Xin, Keyun; Li, Wei; Li, Yanzhe

2018-04-30

In the literature about allocation of selective attention, a widely studied question is when will attention be allocated to information that is clearly irrelevant to the task at hand. The present study, by using convergent evidence, demonstrated that there is a trade-off between quantity of information present in a display and the time allowed to process it. Specifically, whether or not there is interference from irrelevant distractors depends not only on the amount of information present, but also on the amount of time allowed to process that information. When processing time is calibrated to the amount of information present, irrelevant distractors can be selectively ignored successfully. These results suggest that the perceptual load in the load theory of selective attention (i.e., Lavie, 2005) should be thought about as a dynamic rate problem rather than a static capacity limitation. The authors thus propose that rather than conceiving of perceptual load as a quantity of information, they should consider it as a quantity of information per unit of time. In other words, it is the relationship between the quantity of information in the task and the time for processing the information that determines the allocation of selective attention. Thus, the present findings extended load theory, allowing it to explain findings that were previously considered as counter evidence of load theory. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Adaptive Control Allocation for Fault Tolerant Overactuated Autonomous Vehicles

Science.gov (United States)

2007-11-01

Tolerant Overactuated Autonomous Vehicles Casavola, A.; Garone, E. (2007) Adaptive Control Allocation for Fault Tolerant Overactuated Autonomous ...Adaptive Control Allocation for Fault Tolerant Overactuated Autonomous Vehicles 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6...Tolerant Overactuated Autonomous Vehicles 3.2 - 2 RTO-MP-AVT-145 UNCLASSIFIED/UNLIMITED Control allocation problem (CAP) - Given a virtual input v(t

Dynamism in a Semiconductor Industrial Machine Allocation Problem using a Hybrid of the Bio-inspired and Musical-Harmony Approach

Science.gov (United States)

Kalsom Yusof, Umi; Nor Akmal Khalid, Mohd

2015-05-01

Semiconductor industries need to constantly adjust to the rapid pace of change in the market. Most manufactured products usually have a very short life cycle. These scenarios imply the need to improve the efficiency of capacity planning, an important aspect of the machine allocation plan known for its complexity. Various studies have been performed to balance productivity and flexibility in the flexible manufacturing system (FMS). Many approaches have been developed by the researchers to determine the suitable balance between exploration (global improvement) and exploitation (local improvement). However, not much work has been focused on the domain of machine allocation problem that considers the effects of machine breakdowns. This paper develops a model to minimize the effect of machine breakdowns, thus increasing the productivity. The objectives are to minimize system unbalance and makespan as well as increase throughput while satisfying the technological constraints such as machine time availability. To examine the effectiveness of the proposed model, results for throughput, system unbalance and makespan on real industrial datasets were performed with applications of intelligence techniques, that is, a hybrid of genetic algorithm and harmony search. The result aims to obtain a feasible solution to the domain problem.

A NOVEL NUMERICAL MODEL APPROACH FOR EXAMINING SHIP BERTHING IMPACT ON FLOATING PIERS

Directory of Open Access Journals (Sweden)

AMIN CHEGENIZADEH

2015-08-01

Full Text Available This paper presents the results of an investigation into the impact of ship berthing upon floating piers using highly advanced numerical software Abaqus. The ship and floating piers were modeled as solid bodies. For the first time, the effect of soil on the total energy absorption of the system was considered using both elastic and elastic-perfectly plastic soil models. First the results for the elastic soil model were compared to and verified by the existing literature using a spring soil model.Then a continuum soil model was utilized instead of a spring soil model, with the results showing 27% higher energy absorption compared to the spring model. The investigation also considered a model with soil as an elastic-perfectly plastic material, being more aligned with the soil material’s real behavior. With this model the results produced 1% more energy absorption as the soil did not reach plastic failure.

The Manpower Allocation Problem with Time Windows and Job-Teaming Constraints: A Branch-and-Price Approach - Technical Report

DEFF Research Database (Denmark)

Hansen, Anders Dohn; Kolind, Esben; Clausen, Jens

In this paper, we consider the Manpower Allocation Problem with Time Windows, Job-Teaming Constraints and a limited number of teams (m-MAPTWTC). Given a set of teams and a set of tasks, the problem is to assign to each team a sequential order of tasks to maximize the total number of assigned tasks....... Both teams and tasks may be restricted by time windows outside which operation is not possible. Some tasks require cooperation between teams, and all teams cooperating must initiate execution simultaneously. We present an IP-model for the problem, which is decomposed using Dantzig-Wolfe decomposition....... The problem is solved by column generation in a Branch-and-Price framework. Simultaneous execution of tasks is enforced by the branching scheme. To test the efficiency of the proposed algorithm, 12 realistic test instances are introduced. The algorithm is able to find the optimal solution in 11 of the test...

Optimal allocation of trend following strategies

Science.gov (United States)

Grebenkov, Denis S.; Serror, Jeremy

2015-09-01

We consider a portfolio allocation problem for trend following (TF) strategies on multiple correlated assets. Under simplifying assumptions of a Gaussian market and linear TF strategies, we derive analytical formulas for the mean and variance of the portfolio return. We construct then the optimal portfolio that maximizes risk-adjusted return by accounting for inter-asset correlations. The dynamic allocation problem for n assets is shown to be equivalent to the classical static allocation problem for n2 virtual assets that include lead-lag corrections in positions of TF strategies. The respective roles of asset auto-correlations and inter-asset correlations are investigated in depth for the two-asset case and a sector model. In contrast to the principle of diversification suggesting to treat uncorrelated assets, we show that inter-asset correlations allow one to estimate apparent trends more reliably and to adjust the TF positions more efficiently. If properly accounted for, inter-asset correlations are not deteriorative but beneficial for portfolio management that can open new profit opportunities for trend followers. These concepts are illustrated using daily returns of three highly correlated futures markets: the E-mini S&P 500, Euro Stoxx 50 index, and the US 10-year T-note futures.

Transnational Energy Companies' Investment Allocation Decisions

International Nuclear Information System (INIS)

Osmundsen, Petter; Emhjellen, Magne; Halleraker, Morten

2001-10-01

When making international capital budgeting decisions, energy companies are often faced with capital and organisational constraints. The constraints may be real or management imposed. In addition, when entering into a new country or region the companies will incur fixed new area costs that must be considered before investment approval. The decision problem is therefore not a linear problem where the standard net present value rule applies, but a non-linear problem of selecting the combination of projects with the maximum aggregate net present value. New project investments will therefore be selected based on the size of the net present value (often referred to as financial volume or materiality) compared to the projects' use of capital and scarce personnel and organisational capacity. Consequently, projects with a positive net present value, but with low materiality, may not be approved. The portfolio choice has a parallel to the company's choice of core areas. Instead of complex portfolio models, the companies often apply simpler allocation mechanisms, e.g., combinations of fixed investment budgets and materiality requirements. Analysing petroleum cases, we compare the allocations decisions generated by portfolio models and simpler mechanisms. We also discuss the implications of this capital allocation pattern for governments' design of tax systems and license conditions. (author)

Security cost allocation under combined bilateral-pool market dispatch

International Nuclear Information System (INIS)

Abdullah, M.P.; Hassan, M.Y.; Hussin, F.

2008-01-01

Most electricity markets around the world are a combination of bilateral and pool markets, such as NordPool and NYPOOL. In these models, market participants bid into the pool and also make bilateral contracts with each other. This paper addressed the issue of congestion management and security cost allocation in a power pool market model. The basic idea of security cost allocation is to divide the incurred security cost due to congestion relief into pool and bilateral market based on their flow contribution to the congested line. A newly proposed security cost allocation strategy of the combined bilateral-pool market was also presented along with case studies using IEEE-14 bus system that tested the proposed method. Using the proposed method, it was shown that security costs are allocated to market participants at different prices which reflect the load contribution to the security problem. This solves the problem of the uniform security cost allocation in a pure pool market system having uniform pricing, and provides a proper security signal to market participants. 11 refs., 3 tabs., 4 figs

Mobile Ocean Test Berth Support: Cooperative Research and Development Final Report, CRADA Number CRD-10-413

Energy Technology Data Exchange (ETDEWEB)

LiVecchi, Albert [National Renewable Energy Lab. (NREL), Golden, CO (United States)

2015-12-01

The Northwest National Marine Renewable Energy Center (NNMREC), headquartered at the Oregon State University, is establishing the capabilities to test prototype wave energy conversion devices in the ocean. This CRADA will leverage the technical expertise and resources at NREL in the wind industry and in ocean engineering to support and enhance the development of the NNMREC Mobile Ocean Test Berth (MOTB). This CRADA will provide direct support to NNMREC by providing design evaluation and review of the MOTB, developing effective protocols for testing of the MOTB and wave energy conversion devices in the ocean, assisting in the specification of appropriate instrumentation and data acquisition packages, and providing guidance on obtaining and maintaining A2LA (American Association for Laboratory Accreditation) accreditation.

Research on air and missile defense task allocation based on extended contract net protocol

Science.gov (United States)

Zhang, Yunzhi; Wang, Gang

2017-10-01

Based on the background of air and missile defense distributed element corporative engagement, the interception task allocation problem of multiple weapon units with multiple targets under network condition is analyzed. Firstly, a mathematical model of task allocation is established by combat task decomposition. Secondly, the initialization assignment based on auction contract and the adjustment allocation scheme based on swap contract were introduced to the task allocation. Finally, through the simulation calculation of typical situation, the model can be used to solve the task allocation problem in complex combat environment.

Dynamic Energy Consumption and Emission Modelling of Container Terminal based on Multi Agents

Directory of Open Access Journals (Sweden)

Hou Jue

2017-01-01

Full Text Available Environmental protection and energy saving pressure press the increasing attention of container terminal operators. In order to comply with the more and more strict environmental regulation, reducing energy consumption and air pollution emissions, meanwhile, optimizing the operation efficiency, which, is an urgent problem to container terminal operator of China. This paper based on the characteristic of Container Terminal Operation System (CTOS, which includes several sections of container product processes, consist of berth allocation problem, truck dispatching problem, yard allocation problem and auxiliary process. Dynamic energy consumption and emissions characteristic of each equipment and process is modelled, this paper presents the architecture of CTOS based on the multi agent system with early-warning model, which is based on multi-class support vector machines (SVM. A simulation on container terminal is built on the JADE platform to support the decision-making of container terminal, which can reduce energy consumption and air pollution emissions, allows the container terminal operator to be more flexible in their decision to meet the Emission Control Area regulation and Green Port Plan of China.

Accounting of allocation of production enterprises’ overhead costs

Directory of Open Access Journals (Sweden)

О.V. Ivaniuta

2016-12-01

Full Text Available Taking into account the complexity of engineering technological cycles, the use of traditional approaches to the allocation of overhead costs at the researching enterprises is inexpedient and inefficient. The authors find out that to solve this problem it is not enough to choose only one base of allocation because the formed prime cost with such an approach will not meet the reality. That is why it is suggested to use a multilevel allocation of overhead costs. The proposed approach involves the allocation of overhead costs at the following levels: fixed and variable, with shops of main and auxiliary production, calculation stations, some orders. Each level involves the selection of individual allocation bases that are grouped on economic, technological and integrated ones.

Portfolio allocation under the vendor managed inventory: A Markov ...

African Journals Online (AJOL)

Portfolio allocation under the vendor managed inventory: A Markov decision process. ... Journal of Applied Sciences and Environmental Management ... This study provides a review of Markov decision processes and investigates its suitability for solutions to portfolio allocation problems under vendor managed inventory in ...

A cross-layer resource allocation scheme for spatial multiplexing-based MIMO-OFDMA systems

Directory of Open Access Journals (Sweden)

Al-Shatri Hussein

2011-01-01

Full Text Available Abstract We investigate the resource allocation problem for the downlink of a multiple-input multiple-output orthogonal frequency division multiple access (MIMO-OFDMA system. The sum rate maximization itself cannot cope with fairness among users. Hence, we address this problem in the context of the utility-based resource allocation presented in earlier papers. This resource allocation method allows to enhance the efficiency and guarantee fairness among users by exploiting multiuser diversity, frequency diversity, as well as time diversity. In this paper, we treat the overall utility as the quality of service indicator and design utility functions with respect to the average transmission rate in order to simultaneously provide two services, real-time and best-effort. Since the optimal solutions are extremely computationally complex to obtain, we propose a suboptimal joint subchannel and power control algorithm that converges very fast and simplifies the MIMO resource allocation problem into a single-input single-output resource allocation problem. Simulation results indicate that using the proposed method achieves near-optimum solutions, and the available resources are distributed more fairly among users.

A game-theoretical pricing mechanism for multiuser rate allocation for video over WiMAX

Science.gov (United States)

Chen, Chao-An; Lo, Chi-Wen; Lin, Chia-Wen; Chen, Yung-Chang

2010-07-01

In multiuser rate allocation in a wireless network, strategic users can bias the rate allocation by misrepresenting their bandwidth demands to a base station, leading to an unfair allocation. Game-theoretical approaches have been proposed to address the unfair allocation problems caused by the strategic users. However, existing approaches rely on a timeconsuming iterative negotiation process. Besides, they cannot completely prevent unfair allocations caused by inconsistent strategic behaviors. To address these problems, we propose a Search Based Pricing Mechanism to reduce the communication time and to capture a user's strategic behavior. Our simulation results show that the proposed method significantly reduce the communication time as well as converges stably to an optimal allocation.

A Hybrid Heuristic Approach to Provider Selection and Task Allocation Problem in Telecommunications with Varying QoS Levels

Directory of Open Access Journals (Sweden)

Nihat Kasap

2017-01-01

Full Text Available In this research, we study a cost minimization problem for a firm that acquires capacity from providers to accomplish daily operations on telecommunication networks. We model the related optimization problem considering quality of service and capacity requirements and offer a solution approach based on genetic algorithm (GA. Our model reckons the tradeoff between the network capacity acquisition cost and opportunity cost arise when data transmission quality for real-time tasks manifested at undesired levels. To better represent the related features and complexities, we model both capacity and loss probability requirements explicitly, and then, formulate delay and jitter requirements as level matching constraints. Using an experimental framework, we analyze how optimal behavior of the firm is affected by different price schemes, transmission quality and task distributions. We also compare three GA based heuristic solution approaches and comment on the suitability of them on resource selection and task allocation problems.

Efficient power allocation for fixed-gain amplify-and-forward relaying in rayleigh fading

KAUST Repository

Zafar, Ammar

2013-06-01

In this paper, we study power allocation strategies for a fixed-gain amplify-and-forward relay network employing multiple relays. We consider two optimization problems for the relay network: 1) optimal power allocation to maximize the end-to-end signal-to-noise ratio (SNR) and 2) minimizing the total consumed power while maintaining the end-to-end SNR over a threshold value. We assume that the relays have knowledge of only the channel statistics of all the links. We show that the SNR maximization problem is concave and the power minimization problem is convex. Hence, we solve the problems through convex programming. Numerical results show the benefit of allocating power optimally rather than uniformly. © 2013 IEEE.

Simulated Annealing-Based Ant Colony Algorithm for Tugboat Scheduling Optimization

Directory of Open Access Journals (Sweden)

Qi Xu

2012-01-01

Full Text Available As the “first service station” for ships in the whole port logistics system, the tugboat operation system is one of the most important systems in port logistics. This paper formulated the tugboat scheduling problem as a multiprocessor task scheduling problem (MTSP after analyzing the characteristics of tugboat operation. The model considers factors of multianchorage bases, different operation modes, and three stages of operations (berthing/shifting-berth/unberthing. The objective is to minimize the total operation times for all tugboats in a port. A hybrid simulated annealing-based ant colony algorithm is proposed to solve the addressed problem. By the numerical experiments without the shifting-berth operation, the effectiveness was verified, and the fact that more effective sailing may be possible if tugboats return to the anchorage base timely was pointed out; by the experiments with the shifting-berth operation, one can see that the objective is most sensitive to the proportion of the shifting-berth operation, influenced slightly by the tugboat deployment scheme, and not sensitive to the handling operation times.

Cross-Layer Optimal Rate Allocation for Heterogeneous Wireless Multicast

Directory of Open Access Journals (Sweden)

Amr Mohamed

2009-01-01

Full Text Available Heterogeneous multicast is an efficient communication scheme especially for multimedia applications running over multihop networks. The term heterogeneous refers to the phenomenon when multicast receivers in the same session require service at different rates commensurate with their capabilities. In this paper, we address the problem of resource allocation for a set of heterogeneous multicast sessions over multihop wireless networks. We propose an iterative algorithm that achieves the optimal rates for a set of heterogeneous multicast sessions such that the aggregate utility for all sessions is maximized. We present the formulation of the multicast resource allocation problem as a nonlinear optimization model and highlight the cross-layer framework that can solve this problem in a distributed ad hoc network environment with asynchronous computations. Our simulations show that the algorithm achieves optimal resource utilization, guarantees fairness among multicast sessions, provides flexibility in allocating rates over different parts of the multicast sessions, and adapts to changing conditions such as dynamic channel capacity and node mobility. Our results show that the proposed algorithm not only provides flexibility in allocating resources across multicast sessions, but also increases the aggregate system utility and improves the overall system throughput by almost 30% compared to homogeneous multicast.

Methodology for reliability allocation based on fault tree analysis and dualistic contrast

Institute of Scientific and Technical Information of China (English)

TONG Lili; CAO Xuewu

2008-01-01

Reliability allocation is a difficult multi-objective optimization problem.This paper presents a methodology for reliability allocation that can be applied to determine the reliability characteristics of reactor systems or subsystems.The dualistic contrast,known as one of the most powerful tools for optimization problems,is applied to the reliability allocation model of a typical system in this article.And the fault tree analysis,deemed to be one of the effective methods of reliability analysis,is also adopted.Thus a failure rate allocation model based on the fault tree analysis and dualistic contrast is achieved.An application on the emergency diesel generator in the nuclear power plant is given to illustrate the proposed method.

Using linear integer programming for multi-site land-use allocation

NARCIS (Netherlands)

Aerts, J.C.J.H.; Eisinger, E.; Heuvelink, G.B.M.; Stewart, Th.J.

2003-01-01

Research in the area of spatial decision support (SDS) and resource allocation has recently generated increased attention for integrating optimization techniques with GIS. In this paper we address the use of spatial optimization techniques for solving multi-site land-use allocation (MLUA) problems,

Transnational Energy Companies' Investment Allocation Decisions

Energy Technology Data Exchange (ETDEWEB)

Osmundsen, Petter; Emhjellen, Magne; Halleraker, Morten

2001-10-01

When making international capital budgeting decisions, energy companies are often faced with capital and organisational constraints. The constraints may be real or management imposed. In addition, when entering into a new country or region the companies will incur fixed new area costs that must be considered before investment approval. The decision problem is therefore not a linear problem where the standard net present value rule applies, but a non-linear problem of selecting the combination of projects with the maximum aggregate net present value. New project investments will therefore be selected based on the size of the net present value (often referred to as financial volume or materiality) compared to the projects' use of capital and scarce personnel and organisational capacity. Consequently, projects with a positive net present value, but with low materiality, may not be approved. The portfolio choice has a parallel to the company's choice of core areas. Instead of complex portfolio models, the companies often apply simpler allocation mechanisms, e.g., combinations of fixed investment budgets and materiality requirements. Analysing petroleum cases, we compare the allocations decisions generated by portfolio models and simpler mechanisms. We also discuss the implications of this capital allocation pattern for governments' design of tax systems and license conditions. (author)

Radio resource allocation over fading channels under statistical delay constraints

CERN Document Server

Le-Ngoc, Tho

2017-01-01

This SpringerBrief presents radio resource allocation schemes for buffer-aided communications systems over fading channels under statistical delay constraints in terms of upper-bounded average delay or delay-outage probability. This Brief starts by considering a source-destination communications link with data arriving at the source transmission buffer. The first scenario, the joint optimal data admission control and power allocation problem for throughput maximization is considered, where the source is assumed to have a maximum power and an average delay constraints. The second scenario, optimal power allocation problems for energy harvesting (EH) communications systems under average delay or delay-outage constraints are explored, where the EH source harvests random amounts of energy from renewable energy sources, and stores the harvested energy in a battery during data transmission. Online resource allocation algorithms are developed when the statistical knowledge of the random channel fading, data arrivals...

Resource Allocation for Downlink Multi-Cell OFDMA Cognitive Radio Network Using Hungarian Method

Directory of Open Access Journals (Sweden)

N. Forouzan

2013-12-01

Full Text Available This paper considers the problem of resource allocation for downlink part of an OFDM-based multi-cell cognitive radio network which consists of multiple secondary transmitters and receivers communicating simultaneously in the presence of multiple primary users. We present a new framework to maximize the total data throughput of secondary users by means of subchannel assignment, while ensuring interference leakage to PUs is below a threshold. In this framework, we first formulate the resource allocation problem as a nonlinear and non-convex optimization problem. Then we represent the problem as a maximum weighted matching in a bipartite graph and propose an iterative algorithm based on Hungarian method to solve it. The present contribution develops an efficient subchannel allocation algorithm that assigns subchannels to the secondary users without the perfect knowledge of fading channel gain between cognitive radio transmitter and primary receivers. The performance of the proposed subcarrier allocation algorithm is compared with a blind subchannel allocation as well as another scheme with the perfect knowledge of channel-state information. Simulation results reveal that a significant performance advantage can still be realized, even if the optimization at the secondary network is based on imperfect network information.

Matching Theory for Channel Allocation in Cognitive Radio Networks

Directory of Open Access Journals (Sweden)

L. Cao

2016-12-01

Full Text Available For a cognitive radio network (CRN in which a set of secondary users (SUs competes for a limited number of channels (spectrum resources belonging to primary users (PUs, the channel allocation is a challenge and dominates the throughput and congestion of the network. In this paper, the channel allocation problem is first formulated as the 0-1 integer programming optimization, with considering the overall utility both of primary system and secondary system. Inspired by matching theory, a many-to-one matching game is used to remodel the channel allocation problem, and the corresponding PU proposing deferred acceptance (PPDA algorithm is also proposed to yield a stable matching. We compare the performance and computation complexity between these two solutions. Numerical results demonstrate the efficiency and obtain the communication overhead of the proposed scheme.

Supply chain collaboration: A Game-theoretic approach to profit allocation

Energy Technology Data Exchange (ETDEWEB)

Ponte, B.; Fernández, I.; Rosillo, R.; Parreño, J.; García, N.

2016-07-01

Purpose: This paper aims to develop a theoretical framework for profit allocation, as a mechanism for aligning incentives, in collaborative supply chains. Design/methodology/approach: The issue of profit distribution is approached from a game-theoretic perspective. We use the nucleolus concept. The framework is illustrated through a numerical example based on the Beer Game scenario. Findings: The nucleolus offers a powerful perspective to tackle this problem, as it takes into consideration the bargaining power of the different echelons. We show that this framework outperforms classical alternatives. Research limitations/implications: The allocation of the overall supply chain profit is analyzed from a static perspective. Considering the dynamic nature of the problem would be an interesting next step. Practical implications: We provide evidence of drawbacks derived from classical solutions to the profit allocation problem. Real-world collaborative supply chains need of robust mechanisms like the one tackled in this work to align incentives from the various actors. Originality/value: Adopting an efficient collaborative solution is a major challenge for supply chains, since it is a wide and complex process that requires an appropriate scheme. Within this framework, profit allocation is essential.

Supply chain collaboration: A Game-theoretic approach to profit allocation

International Nuclear Information System (INIS)

Ponte, B.; Fernández, I.; Rosillo, R.; Parreño, J.; García, N.

2016-01-01

Purpose: This paper aims to develop a theoretical framework for profit allocation, as a mechanism for aligning incentives, in collaborative supply chains. Design/methodology/approach: The issue of profit distribution is approached from a game-theoretic perspective. We use the nucleolus concept. The framework is illustrated through a numerical example based on the Beer Game scenario. Findings: The nucleolus offers a powerful perspective to tackle this problem, as it takes into consideration the bargaining power of the different echelons. We show that this framework outperforms classical alternatives. Research limitations/implications: The allocation of the overall supply chain profit is analyzed from a static perspective. Considering the dynamic nature of the problem would be an interesting next step. Practical implications: We provide evidence of drawbacks derived from classical solutions to the profit allocation problem. Real-world collaborative supply chains need of robust mechanisms like the one tackled in this work to align incentives from the various actors. Originality/value: Adopting an efficient collaborative solution is a major challenge for supply chains, since it is a wide and complex process that requires an appropriate scheme. Within this framework, profit allocation is essential.

Hybrid Optimization-Based Approach for Multiple Intelligent Vehicles Requests Allocation

Directory of Open Access Journals (Sweden)

Ahmed Hussein

2018-01-01

Full Text Available Self-driving cars are attracting significant attention during the last few years, which makes the technology advances jump fast and reach a point of having a number of automated vehicles on the roads. Therefore, the necessity of cooperative driving for these automated vehicles is exponentially increasing. One of the main issues in the cooperative driving world is the Multirobot Task Allocation (MRTA problem. This paper addresses the MRTA problem, specifically for the problem of vehicles and requests allocation. The objective is to introduce a hybrid optimization-based approach to solve the problem of multiple intelligent vehicles requests allocation as an instance of MRTA problem, to find not only a feasible solution, but also an optimized one as per the objective function. Several test scenarios were implemented in order to evaluate the efficiency of the proposed approach. These scenarios are based on well-known benchmarks; thus a comparative study is conducted between the obtained results and the suboptimal results. The analysis of the experimental results shows that the proposed approach was successful in handling various scenarios, especially with the increasing number of vehicles and requests, which displays the proposed approach efficiency and performance.

System dynamics model developement for R and D budget allocation strategy

International Nuclear Information System (INIS)

Kwack, S. M.; Kim, D. H.; Lee, Y. S.; Jung, M. T.

2003-01-01

A computer simulation model was developed for R and D budget allocation problems that usually contain very complex and non-linear social issues. The System Dynamics approach was employed, which is proper to complex and non-linear social problem modeling. An issue of budget allocation to each step in five research areas was analyzed for an application example. The base scenario, that assumes to allocate a large portion of budget to demonstration step, was found to have a weakness in long-term sense. To overcome this weakness, some other better alternatives were recommended through the analysis. In addition, this paper suggests the ways to utilize the updated model in the future

Coordination Incentives, Performance Measurement and Resource Allocation in Public Sector Organizations

OpenAIRE

Dietrichson, Jens

2013-01-01

Why are coordination problems common when public sector organizations share responsibilities, and what can be done to mitigate such problems? This paper uses a multi-task principal-agent model to examine two related reasons: the incentives to coordinate resource allocation and the difficulties of measuring performance. The analysis shows that when targets are set individually for each organization, the resulting incentives normally induce inefficient resource allocations. If the principal imp...

Function allocation in distributed safeguards and security systems

International Nuclear Information System (INIS)

Barlich, G.L.

1991-01-01

Computerized distributed systems are being used to collect and manage data for activities such as nuclear materials accounting, process control, laboratory coordination, and security. Poor choices made in allocating functions to individual processors can make a system unusable by burdening machines with excessive network retrievals and updates. During system design phases, data allocation algorithms based on operation frequencies, field sizes, security information, and reliability requirements can be applied in sensitivity studies to mathematically ensure processor efficiency. The Los Alamos Network Design System (NDS) implements such an allocation algorithm. The authors analyzed a large, existing distributed system to test the cost functions and to compare actual network problems with NDS results. Several common configurations were also designed and studied using the software. From these studies, some basic principles for allocating functions emerged. In this paper recommendations for function allocation in generic systems and related design options are discussed

Integration and Task Allocation: Evidence from Patient Care.

Science.gov (United States)

David, Guy; Rawley, Evan; Polsky, Daniel

2013-01-01

Using the universe of patient transitions from inpatient hospital care to skilled nursing facilities and home health care in 2005, we show how integration eliminates task misallocation problems between organizations. We find that vertical integration allows hospitals to shift patient recovery tasks downstream to lower-cost organizations by discharging patients earlier (and in poorer health) and increasing post-hospitalization service intensity. While integration facilitates a shift in the allocation of tasks and resources, health outcomes either improved or were unaffected by integration on average. The evidence suggests that integration solves coordination problems that arise in market exchange through improvements in the allocation of tasks across care settings.

Integration and Task Allocation: Evidence from Patient Care*

Science.gov (United States)

David, Guy; Rawley, Evan; Polsky, Daniel

2013-01-01

Using the universe of patient transitions from inpatient hospital care to skilled nursing facilities and home health care in 2005, we show how integration eliminates task misallocation problems between organizations. We find that vertical integration allows hospitals to shift patient recovery tasks downstream to lower-cost organizations by discharging patients earlier (and in poorer health) and increasing post-hospitalization service intensity. While integration facilitates a shift in the allocation of tasks and resources, health outcomes either improved or were unaffected by integration on average. The evidence suggests that integration solves coordination problems that arise in market exchange through improvements in the allocation of tasks across care settings. PMID:24415893

Resource allocation for multichannel broadcasting visible light communication

Science.gov (United States)

Le, Nam-Tuan; Jang, Yeong Min

2015-11-01

Visible light communication (VLC), which offers the possibility of using light sources for both illumination and data communications simultaneously, will be a promising incorporation technique with lighting applications. However, it still remains some challenges especially coverage because of field-of-view limitation. In this paper, we focus on this issue by suggesting a resource allocation scheme for VLC broadcasting system. By using frame synchronization and a network calculus QoS approximation, as well as diversity technology, the proposed VLC architecture and QoS resource allocation for the multichannel-broadcasting MAC (medium access control) protocol can solve the coverage limitation problem and the link switching problem of exhibition service.

Energy-Efficient Power Allocation for MIMO-SVD Systems

KAUST Repository

Sboui, Lokman

2017-05-24

In this paper, we address the problem of energyefficient power allocation in MIMO systems. In fact, the widely adopted water-filling power allocation does not ensure the maximization of the energy efficiency (EE). Since the EE maximization is a non-convex problem, numerical methods based on fractional programming were introduced to find the optimal power solutions. In this paper, we present a novel and simple power allocation scheme based on the explicit expressions of the optimal power. We also present a low-complexity algorithm that complements the proposed scheme for low circuit-power regime. Furthermore, we analyze power-constrained and rate-constrained systems and present the corresponding optimal power control. In the numerical results, we show that the presented analytical expressions are accurate and that the algorithm converges within two iterations. We also show that as the number of antenna increases, the system becomes more energy-efficient. Also, a saturation of the EE is observed at high power budget and low minimal rate regimes.

Land use allocation model considering climate change impact

Science.gov (United States)

Lee, D. K.; Yoon, E. J.; Song, Y. I.

2017-12-01

In Korea, climate change adaptation plans are being developed for each administrative district based on impact assessments constructed in various fields. This climate change impact assessments are superimposed on the actual space, which causes problems in land use allocation because the spatial distribution of individual impacts may be different each other. This implies that trade-offs between climate change impacts can occur depending on the composition of land use. Moreover, the actual space is complexly intertwined with various factors such as required area, legal regulations, and socioeconomic values, so land use allocation in consideration of climate change can be very difficult problem to solve (Liu et al. 2012; Porta et al. 2013).Optimization techniques can generate a sufficiently good alternatives for land use allocation at the strategic level if only the fitness function of relationship between impact and land use composition are derived. It has also been noted that land use optimization model is more effective than the scenario-based prediction model in achieving the objectives for problem solving (Zhang et al. 2014). Therefore in this study, we developed a quantitative tool, MOGA (Multi Objective Genetic Algorithm), which can generate a comprehensive land use allocations considering various climate change impacts, and apply it to the Gangwon-do in Korea. Genetic Algorithms (GAs) are the most popular optimization technique to address multi-objective in land use allocation. Also, it allows for immediate feedback to stake holders because it can run a number of experiments with different parameter values. And it is expected that land use decision makers and planners can formulate a detailed spatial plan or perform additional analysis based on the result of optimization model. Acknowledgments: This work was supported by the Korea Ministry of Environment (MOE) as "Climate Change Correspondence Program (Project number: 2014001310006)"

Green Maritime Logistics

DEFF Research Database (Denmark)

Psaraftis, Harilaos N.

2014-01-01

Typical problems in maritime logistics include, among others, optimal ship speed, ship routing and scheduling, fleet deployment, fleet size and mix, weather routing, intermodal network design, modal split, transshipment, queuing at ports, terminal management, berth allocation, and total supply...... chain management. The traditional analysis of these problems has been in terms of cost- benefit and other optimization criteria from the point of view of the logistics provider, carrier, shipper, or other end-user. Such traditional analysis by and large either ignores environmental issues, or considers...... them of secondary importance. Green maritime logistics tries to bring the environmental dimension into the problem, and specifically the dimension of emissions reduction, by analyzing various trade-offs and exploring ‘win-win’ solutions. This talk takes a look at the trade-offs that are at stake...

Optimized maritime emergency resource allocation under dynamic demand.

Directory of Open Access Journals (Sweden)

Wenfen Zhang

Full Text Available Emergency resource is important for people evacuation and property rescue when accident occurs. The relief efforts could be promoted by a reasonable emergency resource allocation schedule in advance. As the marine environment is complicated and changeful, the place, type, severity of maritime accident is uncertain and stochastic, bringing about dynamic demand of emergency resource. Considering dynamic demand, how to make a reasonable emergency resource allocation schedule is challenging. The key problem is to determine the optimal stock of emergency resource for supplier centers to improve relief efforts. This paper studies the dynamic demand, and which is defined as a set. Then a maritime emergency resource allocation model with uncertain data is presented. Afterwards, a robust approach is developed and used to make sure that the resource allocation schedule performs well with dynamic demand. Finally, a case study shows that the proposed methodology is feasible in maritime emergency resource allocation. The findings could help emergency manager to schedule the emergency resource allocation more flexibly in terms of dynamic demand.

A simulation-based optimization approach for free distributed repairable multi-state availability-redundancy allocation problems

International Nuclear Information System (INIS)

Attar, Ahmad; Raissi, Sadigh; Khalili-Damghani, Kaveh

2017-01-01

A simulation-based optimization (SBO) method is proposed to handle multi-objective joint availability-redundancy allocation problem (JARAP). Here, there is no emphasis on probability distributions of time to failures and repair times for multi-state multi-component series-parallel configuration under active, cold and hot standby strategies. Under such conditions, estimation of availability is not a trivial task. First, an efficient computer simulation model is proposed to estimate the availability of the aforementioned system. Then, the estimated availability values are used in a repetitive manner as parameter of a two-objective joint availability-redundancy allocation optimization model through SBO mechanism. The optimization model is then solved using two well-known multi-objective evolutionary computation algorithms, i.e., non-dominated sorting genetic algorithm (NSGA-II), and Strength Pareto Evolutionary Algorithm (SPEA2). The proposed SBO approach is tested using non-exponential numerical example with multi-state repairable components. The results are presented and discussed through different demand scenarios under cold and hot standby strategies. Furthermore, performance of NSGA-II and SPEA2 are statistically compared regarding multi-objective accuracy, and diversity metrics. - Highlights: • A Simulation-Based Optimization (SBO) procedure is introduced for JARAP. • The proposed SBO works for any given failure and repair times. • An efficient simulation procedure is developed to estimate availability. • Customized NSGA-II and SPEA2 are proposed to solve the bi-objective JARAP. • Statistical analysis is employed to test the performance of optimization methods.

Cogenerational sources of energies and their allocating problem

Directory of Open Access Journals (Sweden)

Badida Miroslav

1997-12-01

Full Text Available Energy production in industrial communities consume a main part of primary raw materials and it is one of the sources of ecologicall impact. Electric power plants and warm produce plants are mostly important investment – consuming establishments with a long time of return, what stress along with the economical, predictional, logistical and environmental decision making aspect of their allocating. Already input of the mentioned aspects along with the price movement after the energy depression motivate a formation of new conception of combinated so-called items, which are able to use the energetic potential of fuels with a higher concurrent efficiency and, on the other hand, can reduce ecologic impacts of fossil combustion.

The incidence of local government allocations in Tanzania

OpenAIRE

Jameson Boex

2003-01-01

Since 1999, Tanzania has been actively pursuing reforms of the way in which the central government finances local government activities. This paper looks at the current incidence of central government allocations to local authorities in Tanzania through: 1) examining of potential problems with the current financing method, 2) showing large variations between local government allocations, and 3) finding that surprisingly what drives t his distribution of resources maybe substantial pro-wealthy...

Dépôt exceptionnel d'un portrait signé Berthe Morisot: le portrait de Jeanne Pontillon dans les collections du MAH

OpenAIRE

2016-01-01

Tiré du site internet du blog des Musées d'art et d'histoire (http://blog.mahgeneve.ch): "Le Musée d'art et d'histoire a le privilège de s'être vu confier par la Société des Amis du MAH (SAMAH) le Portrait de Jeanne Pontillon par Berthe Morisot (1841–1895). Donné à l'association par l'un de ses fidèles membres, ce tableau représente un enrichissement de taille pour l'institution genevoise.".

A particle-based simplified swarm optimization algorithm for reliability redundancy allocation problems

International Nuclear Information System (INIS)

Huang, Chia-Ling

2015-01-01

This paper proposes a new swarm intelligence method known as the Particle-based Simplified Swarm Optimization (PSSO) algorithm while undertaking a modification of the Updating Mechanism (UM), called N-UM and R-UM, and simultaneously applying an Orthogonal Array Test (OA) to solve reliability–redundancy allocation problems (RRAPs) successfully. One difficulty of RRAP is the need to maximize system reliability in cases where the number of redundant components and the reliability of corresponding components in each subsystem are simultaneously decided with nonlinear constraints. In this paper, four RRAP benchmarks are used to display the applicability of the proposed PSSO that advances the strengths of both PSO and SSO to enable optimizing the RRAP that belongs to mixed-integer nonlinear programming. When the computational results are compared with those of previously developed algorithms in existing literature, the findings indicate that the proposed PSSO is highly competitive and performs well. - Highlights: • This paper proposes a particle-based simplified swarm optimization algorithm (PSSO) to optimize RRAP. • Furthermore, the UM and an OA are adapted to advance in optimizing RRAP. • Four systems are introduced and the results demonstrate the PSSO performs particularly well

Cognitive allocation and the control room

International Nuclear Information System (INIS)

Paradies, M.W.

1985-01-01

One of the weakest links in the design of nuclear power plants is the inattention to the needs and capabilities of the operators. This flaw causes decreased plant reliability and reduced plant safety. To solve this problem the designer must, in the earliest stages of the design process, consider the operator's abilities. After the system requirements have been established, the designer must consider what functions to allocate to each part of the system. The human must be considered as part of this system. The allocation of functions needs to consider not only the mechanical tasks to be performed, but also the control requirements and the overall control philosophy. In order for the designers to consider the control philosophy, they need to know what control decisions should be automated and what decisions should be made by an operator. They also need to know how these decisions will be implemented: by an operator or by automation. ''Cognitive Allocation'' is the allocation of the decision making process between operators and machines. It defines the operator's role in the system. When designing a power plant, a cognitive allocation starts the process of considering the operator's abilities. This is the first step to correcting the weakest link in the current plant design

Task mapping for non-contiguous allocations.

Energy Technology Data Exchange (ETDEWEB)

Leung, Vitus Joseph; Bunde, David P.; Ebbers, Johnathan; Price, Nicholas W.; Swank, Matthew.; Feer, Stefan P.; Rhodes, Zachary D.

2013-02-01

This paper examines task mapping algorithms for non-contiguously allocated parallel jobs. Several studies have shown that task placement affects job running time for both contiguously and non-contiguously allocated jobs. Traditionally, work on task mapping either uses a very general model where the job has an arbitrary communication pattern or assumes that jobs are allocated contiguously, making them completely isolated from each other. A middle ground between these two cases is the mapping problem for non-contiguous jobs having a specific communication pattern. We propose several task mapping algorithms for jobs with a stencil communication pattern and evaluate them using experiments and simulations. Our strategies improve the running time of a MiniApp by as much as 30% over a baseline strategy. Furthermore, this improvement increases markedly with the job size, demonstrating the importance of task mapping as systems grow toward exascale.

Multi-robot task allocation based on two dimensional artificial fish swarm algorithm

Science.gov (United States)

Zheng, Taixiong; Li, Xueqin; Yang, Liangyi

2007-12-01

The problem of task allocation for multiple robots is to allocate more relative-tasks to less relative-robots so as to minimize the processing time of these tasks. In order to get optimal multi-robot task allocation scheme, a twodimensional artificial swarm algorithm based approach is proposed in this paper. In this approach, the normal artificial fish is extended to be two dimension artificial fish. In the two dimension artificial fish, each vector of primary artificial fish is extended to be an m-dimensional vector. Thus, each vector can express a group of tasks. By redefining the distance between artificial fish and the center of artificial fish, the behavior of two dimension fish is designed and the task allocation algorithm based on two dimension artificial swarm algorithm is put forward. At last, the proposed algorithm is applied to the problem of multi-robot task allocation and comparer with GA and SA based algorithm is done. Simulation and compare result shows the proposed algorithm is effective.

Modeling of nitrogen oxides (NO(x)) concentrations resulting from ships at berth.

Science.gov (United States)

Abdul-Wahab, Sabah A; Elkamel, Ali; Al Balushi, Abdullah S; Al-Damkhi, Ali M; Siddiqui, Rafiq A

2008-12-01

Oxides of nitrogen (NO(x)) emissions from ships (marine vessels) contribute to poor air quality that negatively impacts public health and communities in coastal areas and far inland. These emissions often excessively harm human health, environment, wildlife habituates, and quality of life of communities and indigenous of people who live near ports. This study was conducted to assess the impact of NO(x) emissions origination from ships at berth on a nearby community. It was undertaken at Said Bin Sultan Naval base in Wullayat Al-Mussana (Sultanate of Oman) during the year 2005. The Industrial Source Complex Short Term (ISCST) model was adopted to determine the dispersion of NO(x) into port and beyond into surrounding urban areas. The hourly and monthly contours (isopleths) of NO(x) concentrations in and around the port were plotted. The results were analyzed to determine the affected area and the level of NO(x) concentrations. The highest concentration points in the studied area were also identified. The isopleths of NO(x) indicated that most shipping emissions of NO(x) occur at the port can be transported over land. The output results can help to derive advice of recommendations ships operators and environmentalists to take the correct decision to prevent workers and surrounded environment from pollution.

Minimizing Sum-MSE Implies Identical Downlink and Dual Uplink Power Allocations

OpenAIRE

Tenenbaum, Adam J.; Adve, Raviraj S.

2009-01-01

In the multiuser downlink, power allocation for linear precoders that minimize the sum of mean squared errors under a sum power constraint is a non-convex problem. Many existing algorithms solve an equivalent convex problem in the virtual uplink and apply a transformation based on uplink-downlink duality to find a downlink solution. In this letter, we analyze the optimality criteria for the power allocation subproblem in the virtual uplink, and demonstrate that the optimal solution leads to i...

Coordinating energy allocation and process performance using an agent-based approach

DEFF Research Database (Denmark)

Umair, Aisha; Clausen, Anders; Jørgensen, Bo Nørregaard

2015-01-01

Energy efficient systems are receiving worldwide attention in response to the negative effects of global warming. Energy efficient systems are concerned with allocation of adequate resources in the energy domain to meet the energy demand in the process domain. In allocation, a balancing problem a...

Fairness-Aware and Energy Efficiency Resource Allocation in Multiuser OFDM Relaying System

Directory of Open Access Journals (Sweden)

Guangjun Liang

2016-01-01

Full Text Available A fairness-aware resource allocation scheme in a cooperative orthogonal frequency division multiple (OFDM network is proposed based on jointly optimizing the subcarrier pairing, power allocation, and channel-user assignment. Compared with traditional OFDM relaying networks, the source is permitted to retransfer the same data transmitted by it in the first time slot, further improving the system capacity performance. The problem which maximizes the energy efficiency (EE of the system with total power constraint and minimal spectral efficiency constraint is formulated into a mixed-integer nonlinear programming (MINLP problem which has an intractable complexity in general. The optimization model is simplified into a typical fractional programming problem which is testified to be quasiconcave. Thus we can adopt Dinkelbach method to deal with MINLP problem proposed to achieve the optimal solution. The simulation results show that the joint resource allocation method proposed can achieve an optimal EE performance under the minimum system service rate requirement with a good global convergence.

Optimization of Joint Power and Bandwidth Allocation in Multi-Spot-Beam Satellite Communication Systems

Directory of Open Access Journals (Sweden)

Heng Wang

2014-01-01

Full Text Available Multi-spot-beam technique has been widely applied in modern satellite communication systems. However, the satellite power and bandwidth resources in a multi-spot-beam satellite communication system are scarce and expensive; it is urgent to utilize the resources efficiently. To this end, dynamically allocating the power and bandwidth is an available way. This paper initially formulates the problem of resource joint allocation as a convex optimization problem, taking into account a compromise between the maximum total system capacity and the fairness among the spot beams. A joint bandwidth and power allocation iterative algorithm based on duality theory is then proposed to obtain the optimal solution of this optimization problem. Compared with the existing separate bandwidth or power optimal allocation algorithms, it is shown that the joint allocation algorithm improves both the total system capacity and the fairness among spot beams. Moreover, it is easy to be implemented in practice, as the computational complexity of the proposed algorithm is linear with the number of spot beams.

Storage Space Allocation of Inbound Container in Railway Container Terminal

Directory of Open Access Journals (Sweden)

Li Wang

2014-01-01

Full Text Available Efficient storage strategy of railway container terminals is important in balancing resource utilization, reducing waiting time, and improving handling efficiency. In this paper, we consider the formulation and solution algorithm for storage space allocation problem of inbound containers in railway container terminal. The problem is formulated as two-stage optimization models, whose objectives are balancing the workload of inbound containers and reducing the overlapping amounts. An algorithm implement process based on rolling horizon approach is designed to solve the proposed models. Computational experiments on an actual railway container terminal show that the proposed approach is effective to solve space allocation problem of inbound container and is significant for the operation and organization of railway container terminals.

Availability Allocation of Networked Systems Using Markov Model and Heuristics Algorithm

OpenAIRE

Li, Ruiying; Liu, Xiaoxi; Huang, Ning

2014-01-01

It is a common practice to allocate the system availability goal to reliability and maintainability goals of components in the early design phase. However, the networked system availability is difficult to be allocated due to its complex topology and multiple down states. To solve these problems, a practical availability allocation method is proposed. Network reliability algebraic methods are used to derive the availability expression of the networked topology on the system level, and Markov ...

Resource allocation in shared spectrum access communications for operators with diverse service requirements

Science.gov (United States)

Kibria, Mirza Golam; Villardi, Gabriel Porto; Ishizu, Kentaro; Kojima, Fumihide; Yano, Hiroyuki

2016-12-01

In this paper, we study inter-operator spectrum sharing and intra-operator resource allocation in shared spectrum access communication systems and propose efficient dynamic solutions to address both inter-operator and intra-operator resource allocation optimization problems. For inter-operator spectrum sharing, we present two competent approaches, namely the subcarrier gain-based sharing and fragmentation-based sharing, which carry out fair and flexible allocation of the available shareable spectrum among the operators subject to certain well-defined sharing rules, traffic demands, and channel propagation characteristics. The subcarrier gain-based spectrum sharing scheme has been found to be more efficient in terms of achieved throughput. However, the fragmentation-based sharing is more attractive in terms of computational complexity. For intra-operator resource allocation, we consider resource allocation problem with users' dissimilar service requirements, where the operator supports users with delay constraint and non-delay constraint service requirements, simultaneously. This optimization problem is a mixed-integer non-linear programming problem and non-convex, which is computationally very expensive, and the complexity grows exponentially with the number of integer variables. We propose less-complex and efficient suboptimal solution based on formulating exact linearization, linear approximation, and convexification techniques for the non-linear and/or non-convex objective functions and constraints. Extensive simulation performance analysis has been carried out that validates the efficiency of the proposed solution.

Multidemand Multisource Order Quantity Allocation with Multiple Transportation Alternatives

Directory of Open Access Journals (Sweden)

Jun Gang

2015-01-01

Full Text Available This paper focuses on a multidemand multisource order quantity allocation problem with multiple transportation alternatives. To solve this problem, a bilevel multiobjective programming model under a mixed uncertain environment is proposed. Two levels of decision makers are considered in the model. On the upper level, the purchaser aims to allocate order quantity to multiple suppliers for each demand node with the consideration of three objectives: total purchase cost minimization, total delay risk minimization, and total defect risk minimization. On the lower level, each supplier attempts to optimize the transportation alternatives with total transportation and penalty costs minimization as the objective. In contrast to prior studies, considering the information asymmetry in the bilevel decision, random and fuzzy random variables are used to model uncertain parameters of the construction company and the suppliers. To solve the bilevel model, a solution method based on Kuhn-Tucker conditions, sectional genetic algorithm, and fuzzy random simulation is proposed. Finally, the applicability of the proposed model and algorithm is evaluated through a practical case from a large scale construction project. The results show that the proposed model and algorithm are efficient in dealing with practical order quantity allocation problems.

Joint Power Allocation for Multicast Systems with Physical-Layer Network Coding

Directory of Open Access Journals (Sweden)

Zhu Wei-Ping

2010-01-01

Full Text Available This paper addresses the joint power allocation issue in physical-layer network coding (PLNC of multicast systems with two sources and two destinations communicating via a large number of distributed relays. By maximizing the achievable system rate, a constrained optimization problem is first formulated to jointly allocate powers for the source and relay terminals. Due to the nonconvex nature of the cost function, an iterative algorithm with guaranteed convergence is developed to solve the joint power allocation problem. As an alternative, an upper bound of the achievable rate is also derived to modify the original cost function in order to obtain a convex optimization solution. This approximation is shown to be asymptotically optimal in the sense of maximizing the achievable rate. It is confirmed through Monte Carlo simulations that the proposed joint power allocation schemes are superior to the existing schemes in terms of achievable rate and cumulative distribution function (CDF.

Zinc allocation and re-allocation in rice

Science.gov (United States)

Stomph, Tjeerd Jan; Jiang, Wen; Van Der Putten, Peter E. L.; Struik, Paul C.

2014-01-01

Aims: Agronomy and breeding actively search for options to enhance cereal grain Zn density. Quantifying internal (re-)allocation of Zn as affected by soil and crop management or genotype is crucial. We present experiments supporting the development of a conceptual model of whole plant Zn allocation and re-allocation in rice. Methods: Two solution culture experiments using 70Zn applications at different times during crop development and an experiment on within-grain distribution of Zn are reported. In addition, results from two earlier published experiments are re-analyzed and re-interpreted. Results: A budget analysis showed that plant zinc accumulation during grain filling was larger than zinc allocation to the grains. Isotope data showed that zinc taken up during grain filling was only partly transported directly to the grains and partly allocated to the leaves. Zinc taken up during grain filling and allocated to the leaves replaced zinc re-allocated from leaves to grains. Within the grains, no major transport barrier was observed between vascular tissue and endosperm. At low tissue Zn concentrations, rice plants maintained concentrations of about 20 mg Zn kg−1 dry matter in leaf blades and reproductive tissues, but let Zn concentrations in stems, sheath, and roots drop below this level. When plant zinc concentrations increased, Zn levels in leaf blades and reproductive tissues only showed a moderate increase while Zn levels in stems, roots, and sheaths increased much more and in that order. Conclusions: In rice, the major barrier to enhanced zinc allocation towards grains is between stem and reproductive tissues. Enhancing root to shoot transfer will not contribute proportionally to grain zinc enhancement. PMID:24478788

An improved risk-explicit interval linear programming model for pollution load allocation for watershed management.

Science.gov (United States)

Xia, Bisheng; Qian, Xin; Yao, Hong

2017-11-01

Although the risk-explicit interval linear programming (REILP) model has solved the problem of having interval solutions, it has an equity problem, which can lead to unbalanced allocation between different decision variables. Therefore, an improved REILP model is proposed. This model adds an equity objective function and three constraint conditions to overcome this equity problem. In this case, pollution reduction is in proportion to pollutant load, which supports balanced development between different regional economies. The model is used to solve the problem of pollution load allocation in a small transboundary watershed. Compared with the REILP original model result, our model achieves equity between the upstream and downstream pollutant loads; it also overcomes the problem of greatest pollution reduction, where sources are nearest to the control section. The model provides a better solution to the problem of pollution load allocation than previous versions.

Financial Resource Allocation in Higher Education

Science.gov (United States)

Ušpuriene, Ana; Sakalauskas, Leonidas; Dumskis, Valerijonas

2017-01-01

The paper considers a problem of financial resource allocation in a higher education institution. The basic financial management instruments and the multi-stage cost minimization model created are described involving financial instruments to constraints. Both societal and institutional factors that determine the costs of educating students are…

Optimal allocation and adaptive VAR control of PV-DG in distribution networks

International Nuclear Information System (INIS)

Fu, Xueqian; Chen, Haoyong; Cai, Runqing; Yang, Ping

2015-01-01

Highlights: • A methodology for optimal PV-DG allocation based on a combination of algorithms. • Dealing with the randomicity of solar power energy using CCSP. • Presenting a VAR control strategy to balance the technical demands. • Finding the Pareto solutions using MOPSO and SVM. • Evaluating the Pareto solutions using WRSR. - Abstract: The development of distributed generation (DG) has brought new challenges to power networks. One of them that catches extensive attention is the voltage regulation problem of distribution networks caused by DG. Optimal allocation of DG in distribution networks is another well-known problem being widely investigated. This paper proposes a new method for the optimal allocation of photovoltaic distributed generation (PV-DG) considering the non-dispatchable characteristics of PV units. An adaptive reactive power control model is introduced in PV-DG allocation as to balance the trade-off between the improvement of voltage quality and the minimization of power loss in a distribution network integrated with PV-DG units. The optimal allocation problem is formulated as a chance-constrained stochastic programming (CCSP) model for dealing with the randomness of solar power energy. A novel algorithm combining the multi-objective particle swarm optimization (MOPSO) with support vector machines (SVM) is proposed to find the Pareto front consisting of a set of possible solutions. The Pareto solutions are further evaluated using the weighted rank sum ratio (WRSR) method to help the decision-maker obtain the desired solution. Simulation results on a 33-bus radial distribution system show that the optimal allocation method can fully take into account the time-variant characteristics and probability distribution of PV-DG, and obtain the best allocation scheme

Allocation of Playing Time within Team Sports--A Problem for Discussion

Science.gov (United States)

Lorentzen, Torbjørn

2017-01-01

The background of the article is the recurrent discussion about allocation of playing time in team sports involving children and young athletes. The objective is to analyse "why" playing time is a topic for discussion among parents, coaches and athletes. The following question is addressed: Under which condition is it "fair" to…

Coordination Incentives, Performance Measurement and Resource Allocation in Public Sector Organizations

DEFF Research Database (Denmark)

Dietrichson, Jens

Why are coordination problems common when public sector organizations share responsibilities, and what can be done to mitigate such problems? This paper uses a multi-task principal-agent model to examine two related reasons: the incentives to coordinate resource allocation and the difficulties...... of measuring performance. The analysis shows that when targets are set individually for each organization, the resulting incentives normally induce inefficient resource allocations. If the principal impose shared targets, this may improve the incentives to coordinate but the success of this instrument depends...

Energy resource allocation using multi-objective goal programming: the case of Lebanon

International Nuclear Information System (INIS)

Mezher, T.; Chedid, R.; Zahabi, W.

1998-01-01

The traditional energy-resources allocation problem is concerned with the allocation of limited resources among the end-uses such that the overall return is maximized. In the past, several techniques have been used to deal with such a problem. In this paper, the energy allocation process is looked at from two points of view: economy and environment. The economic objectives include costs, efficiency, energy conservation, and employment generation. The environmental objectives consider environmental friendliness factors. The objective functions are first quantified and then transformed into mathematical language to obtain a multi-objective allocation model based upon pre-emptive goal programming techniques. The proposed method allows decision-makers to encourage or discourage specific energy resources for the various household end-uses. The case of Lebanon is examined to illustrate the usefulness of the proposed technique. (Copyright (c) 1998 Elsevier Science B.V., Amsterdam. All rights reserved.)

Resource Allocation Model for Modelling Abstract RTOS on Multiprocessor System-on-Chip

DEFF Research Database (Denmark)

Virk, Kashif Munir; Madsen, Jan

2003-01-01

Resource Allocation is an important problem in RTOS's, and has been an active area of research. Numerous approaches have been developed and many different techniques have been combined for a wide range of applications. In this paper, we address the problem of resource allocation in the context...... of modelling an abstract RTOS on multiprocessor SoC platforms. We discuss the implementation details of a simplified basic priority inheritance protocol for our abstract system model in SystemC....

Centralized Allocation in Multiple Markets

DEFF Research Database (Denmark)

Monte, Daniel; Tumennasan, Norovsambuu

The problem of allocating indivisible objects to different agents, where each indi vidual is assigned at most one object, has been widely studied. Pápai (2000) shows that the set of strategy-proof, nonbossy, Pareto optimal and reallocation-proof rules are hierarchical exchange rules | generalizat...... and nonbossy rules are sequential dictatorships, a special case of Pápai's hierarchical exchange rules....

Optimal allocation of sensors for state estimation of distributed parameter systems

International Nuclear Information System (INIS)

Sunahara, Yoshifumi; Ohsumi, Akira; Mogami, Yoshio.

1978-01-01

The purpose of this paper is to present a method for finding the optimal allocation of sensors for state estimation of linear distributed parameter systems. This method is based on the criterion that the error covariance associated with the state estimate becomes minimal with respect to the allocation of the sensors. A theorem is established, giving the sufficient condition for optimizing the allocation of sensors to make minimal the error covariance approximated by a modal expansion. The remainder of this paper is devoted to illustrate important phases of the general theory of the optimal measurement allocation problem. To do this, several examples are demonstrated, including extensive discussions on the mutual relation between the optimal allocation and the dynamics of sensors. (author)

Marine environmental radioactivity surveys at nuclear submarine berths in the UK, 1989

International Nuclear Information System (INIS)

Fuller, D.; Casey, E.

1990-12-01

This report presents the results of the marine environmental radioactivity monitoring surveys of intertidal and underwater areas around nuclear submarine berths in the UK, including the US Naval Base at Holy Loch, which were carried out by Defence Radiological Protection Service (DRPS) during 1989. Also included are results of smaller scale intertidal surveys carried out by local staff but co-ordinated by DRPS, and as an Appendix a report by the US Navy detailing the results of their environmental radioactivity monitoring programme at Holy Loch. Cobalt-60, the nuclide of major importance in naval discharges, was detected in a number of samples but in most cases was attributable to discharges by other operators. Concentrations in any case were found to be low, and at no survey location did the calculated annual radiation dose commitment to the most exposed members of the general public due to the presence of cobalt-60 exceed 1% of the ICRP principal dose limit for members of the public (1mSv). It is concluded that existing discharge arrangements are providing effective control over environmental levels of cobalt-60, and that there has been no radiological hazard to any member of the general public during 1989 from the operation of nuclear powered submarines. These findings have been confirmed by independent monitoring undertaken by the Ministry of Agriculture, Fisheries and Food Directorate of Fisheries Research. (author)

Marine environmental radioactivity surveys at nuclear submarine berths in the UK 1991

International Nuclear Information System (INIS)

1992-06-01

This report presents the results of the marine environmental radioactivity monitoring surveys of intertidal and underwater areas around nuclear submarine berths in the UK, including the US Naval Base at Holy Loch, which were carried out by DRPS during 1991. Also included are results of smaller scale intertidal surveys carried out by local staff but co-ordinated by DRPS and, as an Appendix, a report by the US Navy detailing the results of their environmental monitoring programme at Holy Loch. Cobalt-60, the nuclide of major importance in naval discharges, was detected in a number of samples but in many cases was attributable to discharges by other operators. Concentrations in any case were found to be low, and at no survey location did the calculated annual radiation dose commitment to the most exposed members of the general public due to the presence of cobalt-60 exceed 1% of the ICRP principal dose limit for members of the public (1000 μSv). These results are consistent with those obtained in the independent monitoring programme undertaken by the Ministry of Agriculture Fisheries and Food Directorate of Fisheries Research. It is concluded that existing discharge arrangements are providing effective control over environmental levels of cobalt-60, and that there has been no radiological hazard to any member of the general public during 1991 from the operation of nuclear powered submarines. (author)

Marine environmental radioactivity surveys at nuclear submarine berths in the UK, 1990

International Nuclear Information System (INIS)

Fuller, D.; Casey, E.

1992-02-01

This report presents the results of the marine environmental radioactivity monitoring surveys of intertidal and underwater areas around nuclear submarine berths in the UK, including the US Naval Base at Holy Loch, which were carried out by Defence Radiological Protection Service (DRPS) during 1990. Also included are results of smaller scale intertidal surveys carried out by local staff but coordinated by DRPS and, as an Appendix, a report by the US Navy detailing the results of their environmental monitoring programme at Holy Loch. Cobalt-60, the nuclide of major importance in naval discharges, was detected in a number of samples but in most cases was attributable to discharges by other operators. Concentrations in any case were found to be low, and at no survey location did the calculated annual radiation dose commitment to the most exposed members of the general public due to the presence of cobalt-60 exceed 1% of the ICRP principal dose limit for members of the public (1000 μSv). These results are consistent with those obtained in the independent monitoring programme undertaken by the Ministry of Agriculture Fisheries and Food Directorate of Fisheries Research. It is concluded that existing discharge arrangements are providing effective control over environmental levels of cobalt-60, and that there has been no radiological hazard to any member of the general public during 1990 from the operation of nuclear powered submarines. (author)

Power Allocation based on Certain Equivalent Margin Applicable to Wireless Communication Systems Limited by Interference

Directory of Open Access Journals (Sweden)

Tadeu Junior Gross

2015-10-01

Full Text Available This paper analyzes the method of power allocation for wireless communication networks, limited by multiple access interference under fading Rayleigh channels. The method takes into account the statistical variation of the desired and interfering signals power and optimally and dynamically allocates the power resources in the system. This allocation is made being taken into account the restrictions imposed by the outage probability for each receiver/transmitter pair. Based on the Perron-Frobenius eigenvalue and geometric programming (GP theories, some interesting results were found for the optimization problem analyzed. A GP is a special type of optimization problem that can be transformed in a non-linear convex optimization problem simply by the change of variables, and then to be globally solved. Also, an iterative method for fast convergence was shown to find the optimally power allocation seeking to minimize the outage probability in the communication.

Optimally Joint Subcarrier Matching and Power Allocation in OFDM Multihop System

Directory of Open Access Journals (Sweden)

Shuyuan Yang

2008-04-01

Full Text Available Orthogonal frequency division multiplexing (OFDM multihop system is a promising way to increase capacity and coverage. In this paper, we propose an optimally joint subcarrier matching and power allocation scheme to further maximize the total channel capacity with the constrained total system power. First, the problem is formulated as a mixed binary integer programming problem, which is prohibitive to find the global optimum in terms of complexity. Second, by making use of the equivalent channel power gain for any matched subcarrier pair, a low complexity scheme is proposed. The optimal subcarrier matching is to match subcarriers by the order of the channel power gains. The optimal power allocation among the matched subcarrier pairs is water-filling. An analytical argument is given to prove that the two steps achieve the optimally joint subcarrier matching and power allocation. The simulation results show that the proposed scheme achieves the largest total channel capacity as compared to the other schemes, where there is no subcarrier matching or no power allocation.

Optimally Joint Subcarrier Matching and Power Allocation in OFDM Multihop System

Directory of Open Access Journals (Sweden)

Wang Wenyi

2008-01-01

Full Text Available Orthogonal frequency division multiplexing (OFDM multihop system is a promising way to increase capacity and coverage. In this paper, we propose an optimally joint subcarrier matching and power allocation scheme to further maximize the total channel capacity with the constrained total system power. First, the problem is formulated as a mixed binary integer programming problem, which is prohibitive to find the global optimum in terms of complexity. Second, by making use of the equivalent channel power gain for any matched subcarrier pair, a low complexity scheme is proposed. The optimal subcarrier matching is to match subcarriers by the order of the channel power gains. The optimal power allocation among the matched subcarrier pairs is water-filling. An analytical argument is given to prove that the two steps achieve the optimally joint subcarrier matching and power allocation. The simulation results show that the proposed scheme achieves the largest total channel capacity as compared to the other schemes, where there is no subcarrier matching or no power allocation.

Availability Allocation of Networked Systems Using Markov Model and Heuristics Algorithm

Directory of Open Access Journals (Sweden)

Ruiying Li

2014-01-01

Full Text Available It is a common practice to allocate the system availability goal to reliability and maintainability goals of components in the early design phase. However, the networked system availability is difficult to be allocated due to its complex topology and multiple down states. To solve these problems, a practical availability allocation method is proposed. Network reliability algebraic methods are used to derive the availability expression of the networked topology on the system level, and Markov model is introduced to determine that on the component level. A heuristic algorithm is proposed to obtain the reliability and maintainability allocation values of components. The principles applied in the AGREE reliability allocation method, proposed by the Advisory Group on Reliability of Electronic Equipment, and failure rate-based maintainability allocation method persist in our allocation method. A series system is used to verify the new algorithm, and the result shows that the allocation based on the heuristic algorithm is quite accurate compared to the traditional one. Moreover, our case study of a signaling system number 7 shows that the proposed allocation method is quite efficient for networked systems.

Measuring health indicators and allocating health resources: a DEA-based approach.

Science.gov (United States)

Yang, Chih-Ching

2016-02-03

This paper suggests new empirical DEA models for the measurement of health indicators and the allocation of health resources. The proposed models were developed by first suggesting a population-based health indicator. By introducing the suggested indicator into DEA models, a new approach that solves the problem of health resource allocation has been developed. The proposed models are applied to an empirical study of Taiwan's health system. Empirical findings show that the suggested indicator can successfully accommodate the differences in health resource demands between populations, providing more reliable performance information than traditional indicators such as physician density. Using our models and a commonly used allocation mechanism, capitation, to allocate medical expenditures, it is found that the proposed model always obtains higher performance than those derived from capitation, and the superiority increases as allocated expenditures rise.

A Review of Function Allocation and En Route Separation Assurance

Science.gov (United States)

Lewis, Timothy A.; Aweiss, Arwa S.; Guerreiro, Nelson M.; Daiker, Ronald J.

2016-01-01

Today's air traffic control system has reached a limit to the number of aircraft that can be safely managed at the same time. This air traffic capacity bottleneck is a critical problem along the path to modernization for air transportation. The design of the next separation assurance system to address this problem is a cornerstone of air traffic management research today. This report reviews recent work by NASA and others in the areas of function allocation and en route separation assurance. This includes: separation assurance algorithms and technology prototypes; concepts of operations and designs for advanced separation assurance systems; and specific investigations into air-ground and human-automation function allocation.

Dynamic asset allocation for bank under stochastic interest rates.

OpenAIRE

Chakroun, Fatma; Abid, Fathi

2014-01-01

This paper considers the optimal asset allocation strategy for bank with stochastic interest rates when there are three types of asset: Bank account, loans and securities. The asset allocation problem is to maximize the expected utility from terminal wealth of a bank's shareholders over a finite time horizon. As a consequence, we apply a dynamic programming principle to solve the Hamilton-Jacobi-Bellman (HJB) equation explicitly in the case of the CRRA utility function. A case study is given ...

On approximately fair cost allocation in Euclidean TSP games

NARCIS (Netherlands)

Faigle, U.; Fekete, Sándor P.; Hochstättler, Winfried; Kern, Walter

1998-01-01

We consider the problem of allocating the cost of an optimal traveling salesman tour in a fair way among the nodes visited; in particular, we focus on the case where the distance matrix of the underlying TSP problem satisfies the triangle inequality. We thereby use the model of TSP games in the

Gestão de portos brasileiros e do BRICS: uma análise comparativa sobre seus problemas logísticos e a resolução por meio da tecnologia de informação

Directory of Open Access Journals (Sweden)

Priscilla Cristina Cabral Ribeiro

2017-01-01

Full Text Available Brazilian ports have many logistics problems caused by lack of investment and innovation, leading to bottlenecks in the movement of goods. The same occurs at the ports of BRICS member countries. In order to solve the bottlenecks, an option could be the use of information technology (IT, which acts as a facilitator for managing and operating ports. The purpose of this article is to analyze the main problems found at BRICS ports and propose solutions to them through the usage of IT. To do this, a bibliographic search was carried out in the Scopus and SciElo databases, as well as in institutional websites. For berth allocation problems, optimization solutions were more effective; for bottlenecks, simulation, optimization, and RFID technology were used; and for management problems, intelligent transportation systems (ITS and other IT solutions, such electronic data interchange (EDI, helped in the integration of logistic system actors, minimizing a majority of the problems.

Research advances on thereasonable water resources allocation in irrigation district

DEFF Research Database (Denmark)

Xuebin, Qi; Zhongdong, Huang; Dongmei, Qiao

2015-01-01

The rational allocation of water resources for irrigation is important to improve the efficiency in utilization of water resources and ensuring food security, but also effective control measures need to be in place for the sustainable utilization of water resources in an irrigation area. The prog......The rational allocation of water resources for irrigation is important to improve the efficiency in utilization of water resources and ensuring food security, but also effective control measures need to be in place for the sustainable utilization of water resources in an irrigation area...... mechanism of water resources is not perfect, the model for optimal water resources allocation is not practical, and the basic conditions for optimal allocation of water resources is relatively weak. In order to solve those problems in water resources allocation practice, six important as?pects must...... in irrigation districts, studying the water resources control technology in irrigation districts by hydrology ecological system, studying the technologies of real?time risk dispatching and intelligent management in irrigation districts, and finally studying the technology of cou?pling optimal allocation...

The Design and Implementation of a GUI-Based Control Allocation Toolbox in the MATLAB Environment

OpenAIRE

Glaze, Michelle L.

1998-01-01

Control Allocation addresses the problem of the management of multiple, redundant control effectors. Generally speaking, control allocation is any method that is used to determine how the controls of a system should be positioned to achieve some desired effect. An infinite number of allocation methods exist, from the straight-forward direct allocation technique, to the daisy chaining approach, to the computationally simple generalized inverse method. Because different methods have advantag...

Optimization of lift gas allocation in a gas lifted oil field as non-linear optimization problem

Directory of Open Access Journals (Sweden)

Roshan Sharma

2012-01-01

Full Text Available Proper allocation and distribution of lift gas is necessary for maximizing total oil production from a field with gas lifted oil wells. When the supply of the lift gas is limited, the total available gas should be optimally distributed among the oil wells of the field such that the total production of oil from the field is maximized. This paper describes a non-linear optimization problem with constraints associated with the optimal distribution of the lift gas. A non-linear objective function is developed using a simple dynamic model of the oil field where the decision variables represent the lift gas flow rate set points of each oil well of the field. The lift gas optimization problem is solved using the emph'fmincon' solver found in MATLAB. As an alternative and for verification, hill climbing method is utilized for solving the optimization problem. Using both of these methods, it has been shown that after optimization, the total oil production is increased by about 4. For multiple oil wells sharing lift gas from a common source, a cascade control strategy along with a nonlinear steady state optimizer behaves as a self-optimizing control structure when the total supply of lift gas is assumed to be the only input disturbance present in the process. Simulation results show that repeated optimization performed after the first time optimization under the presence of the input disturbance has no effect in the total oil production.

Design of SCADA water resource management control center by a bi-objective redundancy allocation problem and particle swarm optimization

International Nuclear Information System (INIS)

Dolatshahi-Zand, Ali; Khalili-Damghani, Kaveh

2015-01-01

SCADA is an essential system to control critical facilities in big cities. SCADA is utilized in several sectors such as water resource management, power plants, electricity distribution centers, traffic control centers, and gas deputy. The failure of SCADA results in crisis. Hence, the design of SCADA system in order to serve a high reliability considering limited budget and other constraints is essential. In this paper, a bi-objective redundancy allocation problem (RAP) is proposed to design Tehran's SCADA water resource management control center. Reliability maximization and cost minimization are concurrently considered. Since the proposed RAP is a non-linear multi-objective mathematical programming so the exact methods cannot efficiently handle it. A multi-objective particle swarm optimization (MOPSO) algorithm is designed to solve it. Several features such as dynamic parameter tuning, efficient constraint handling and Pareto gridding are inserted in proposed MOPSO. The results of proposed MOPSO are compared with an efficient ε-constraint method. Several non-dominated designs of SCADA system are generated using both methods. Comparison metrics based on accuracy and diversity of Pareto front are calculated for both methods. The proposed MOPSO algorithm reports better performance. Finally, in order to choose the practical design, the TOPSIS algorithm is used to prune the Pareto front. - Highlights: • Multi-objective redundancy allocation problem (MORAP) is proposed to design SCADA system. • Multi-objective particle swarm optimization (MOPSO) is proposed to solve MORAP. • Efficient epsilon-constraint method is adapted to solve MORAP. • Non-dominated solutions are generated on Pareto front of MORAP by both methods. • Several multi-objective metrics are calculated to compare the performance of methods

Optimal load allocation of complex ship power plants

International Nuclear Information System (INIS)

Baldi, Francesco; Ahlgren, Fredrik; Melino, Francesco; Gabrielii, Cecilia; Andersson, Karin

2016-01-01

Highlights: • The optimal operation of the prime movers of hybrid ship power plants is addressed. • Both mechanical, electric and thermal power demand are considered. • The problem is modelled as a mixed integer-nonlinear programming problem. • Up to 3% savings can be achieved with hybrid power plants. • Including the thermal power demand improves the solution by up to 4%. - Abstract: In a world with increased pressure on reducing fuel consumption and carbon dioxide emissions, the cruise industry is growing in size and impact. In this context, further effort is required for improving the energy efficiency of cruise ship energy systems. In this paper, we propose a generic method for modelling the power plant of an isolated system with mechanical, electric and thermal power demands and for the optimal load allocation of the different components that are able to fulfil the demand. The optimisation problem is presented in the form of a mixed integer linear programming (MINLP) problem, where the number of engines and/or boilers running is represented by the integer variables, while their respective load is represented by the non-integer variables. The individual components are modelled using a combination of first-principle models and polynomial regressions, thus making the system nonlinear. The proposed method is applied to the load-allocation problem of a cruise ship sailing in the Baltic Sea, and used to compare the existing power plant with a hybrid propulsion plant. The results show the benefits brought by using the proposing method, which allow estimating the performance of the hybrid system (for which the load allocation is a non-trivial problem) while also including the contribution of the heat demand. This allows showing that, based on a reference round voyage, up to 3% savings could be achieved by installing the proposed system, compared to the existing one, and that a NPV of 11 kUSD could be achieved already 5 years after the installation of the

Adapting water allocation management to drought scenarios

Directory of Open Access Journals (Sweden)

P. Giacomelli

2008-04-01

Full Text Available Climate change dynamics have significant consequences on water resources on a watershed scale. With water becoming scarcer and susceptible to variation, the planning and reallocation decisions in watershed management need to be reviewed. This research focuses on an in-depth understanding of the current allocation balance of water resources among competitors, placed along the course of the Adda River. In particular, during the summer period, the demand for water dramatically increases. This is due to the increase in irrigation activities in the lower part of the basin and to the highest peaks of tourist inflow, in the Como Lake and Valtellina areas. Moreover, during these months, the hydroelectric reservoirs in the upper part of the Adda River basin (the Valtellina retain most of the volume of water coming from the snow and glacier melt. The existing allocation problem among these different competing users is exacerbated by the decreasing water supplies. The summer of 2003 testified the rise in a number of allocation problems and situations of water scarcity that brought about environmental and economical consequences. The RICLIC project is committed to the understanding of water dynamics on a regional scale, to quantify the volumes involved and offer local communities an instrument to improve a sustainable water management system, within uncertain climate change scenarios.

Towards an understanding of the molecular regulation of carbon allocation in diatoms: the interaction of energy and carbon allocation.

Science.gov (United States)

Wagner, Heiko; Jakob, Torsten; Fanesi, Andrea; Wilhelm, Christian

2017-09-05

In microalgae, the photosynthesis-driven CO 2 assimilation delivers cell building blocks that are used in different biosynthetic pathways. Little is known about how the cell regulates the subsequent carbon allocation to, for example, cell growth or for storage. However, knowledge about these regulatory mechanisms is of high biotechnological and ecological importance. In diatoms, the situation becomes even more complex because, as a consequence of their secondary endosymbiotic origin, the compartmentation of the pathways for the primary metabolic routes is different from green algae. Therefore, the mechanisms to manipulate the carbon allocation pattern cannot be adopted from the green lineage. This review describes the general pathways of cellular energy distribution from light absorption towards the final allocation of carbon into macromolecules and summarizes the current knowledge of diatom-specific allocation patterns. We further describe the (limited) knowledge of regulatory mechanisms of carbon partitioning between lipids, carbohydrates and proteins in diatoms. We present solutions to overcome the problems that hinder the identification of regulatory elements of carbon metabolism.This article is part of the themed issue 'The peculiar carbon metabolism in diatoms'. © 2017 The Author(s).

Optimal allocation of resources for suppressing epidemic spreading on networks

Science.gov (United States)

Chen, Hanshuang; Li, Guofeng; Zhang, Haifeng; Hou, Zhonghuai

2017-07-01

Efficient allocation of limited medical resources is crucial for controlling epidemic spreading on networks. Based on the susceptible-infected-susceptible model, we solve the optimization problem of how best to allocate the limited resources so as to minimize prevalence, providing that the curing rate of each node is positively correlated to its medical resource. By quenched mean-field theory and heterogeneous mean-field (HMF) theory, we prove that an epidemic outbreak will be suppressed to the greatest extent if the curing rate of each node is directly proportional to its degree, under which the effective infection rate λ has a maximal threshold λcopt=1 / , where is the average degree of the underlying network. For a weak infection region (λ ≳λcopt ), we combine perturbation theory with the Lagrange multiplier method (LMM) to derive the analytical expression of optimal allocation of the curing rates and the corresponding minimized prevalence. For a general infection region (λ >λcopt ), the high-dimensional optimization problem is converted into numerically solving low-dimensional nonlinear equations by the HMF theory and LMM. Counterintuitively, in the strong infection region the low-degree nodes should be allocated more medical resources than the high-degree nodes to minimize prevalence. Finally, we use simulated annealing to validate the theoretical results.

Zinc allocation and re-allocation in rice

NARCIS (Netherlands)

Stomph, T.J.; Jiang, W.; Putten, van der P.E.L.; Struik, P.C.

2014-01-01

Aims: Agronomy and breeding actively search for options to enhance cereal grain Zn density. Quantifying internal (re-)allocation of Zn as affected by soil and crop management or genotype is crucial. We present experiments supporting the development of a conceptual model of whole plant Zn allocation

Energy-Efficient Power Allocation for Fixed-Gain Amplify-and-Forward Relay Networks with Partial Channel State Information

KAUST Repository

Zafar, Ammar

2012-06-01

In this report, energy-efficient transmission and power allocation for fixed-gain amplify-and-forward relay networks with partial channel state information (CSI) are studied. In the energy-efficiency problem, the total power consumed is minimized while keeping the signal-to-noise-ratio (SNR) above a certain threshold. In the dual problem of power allocation, the end-to-end SNR is maximized under individual and global power constraints. Closed-form expressions for the optimal source and relay powers and the Lagrangian multiplier are obtained. Numerical results show that the optimal power allocation with partial CSI provides comparable performance as optimal power allocation with full CSI at low SNR.

Energy-Efficient Power Allocation for Fixed-Gain Amplify-and-Forward Relay Networks with Partial Channel State Information

KAUST Repository

Zafar, Ammar

2012-09-16

In this letter, energy-efficient transmission and power allocation for fixed-gain amplify-and-forward relay networks with partial channel state information (CSI) are studied. In the energy-efficiency problem, the total power consumed is minimized while keeping the signal-to-noise-ratio (SNR) above a certain threshold. In the dual problem of power allocation, the end-to-end SNR is maximized under individual and global power constraints. Closed-form expressions for the optimal source and relay powers and the Lagrangian multiplier are obtained. Numerical results show that the optimal power allocation with partial CSI provides comparable performance as optimal power allocation with full CSI at low SNR. © 2012 IEEE.

Methodology for allocating nuclear power plant control functions to human or automatic control

International Nuclear Information System (INIS)

Pulliam, R.; Price, H.E.; Bongarra, J.; Sawyer, C.R.; Kisner, R.A.

1983-08-01

This report describes a general method for allocating control functions to man or machine during nuclear power plant (NPP) design, or for evaluating their allocation in an existing design. The research examined some important characeristics of the systems design process, and the results make it clear that allocation of control functions is an intractable problem, one which increases complexity of systems. The method is reported in terms of specific steps which should be taken during early stages of a new system design, and which will lead to an optimal allocation at the functional design level of detail

A Novel Sensor Selection and Power Allocation Algorithm for Multiple-Target Tracking in an LPI Radar Network

Directory of Open Access Journals (Sweden)

Ji She

2016-12-01

Full Text Available Radar networks are proven to have numerous advantages over traditional monostatic and bistatic radar. With recent developments, radar networks have become an attractive platform due to their low probability of intercept (LPI performance for target tracking. In this paper, a joint sensor selection and power allocation algorithm for multiple-target tracking in a radar network based on LPI is proposed. It is found that this algorithm can minimize the total transmitted power of a radar network on the basis of a predetermined mutual information (MI threshold between the target impulse response and the reflected signal. The MI is required by the radar network system to estimate target parameters, and it can be calculated predictively with the estimation of target state. The optimization problem of sensor selection and power allocation, which contains two variables, is non-convex and it can be solved by separating power allocation problem from sensor selection problem. To be specific, the optimization problem of power allocation can be solved by using the bisection method for each sensor selection scheme. Also, the optimization problem of sensor selection can be solved by a lower complexity algorithm based on the allocated powers. According to the simulation results, it can be found that the proposed algorithm can effectively reduce the total transmitted power of a radar network, which can be conducive to improving LPI performance.

Decision-theoretic methodology for reliability and risk allocation in nuclear power plants

International Nuclear Information System (INIS)

Cho, N.Z.; Papazoglou, I.A.; Bari, R.A.; El-Bassioni, A.

1985-01-01

This paper describes a methodology for allocating reliability and risk to various reactor systems, subsystems, components, operations, and structures in a consistent manner, based on a set of global safety criteria which are not rigid. The problem is formulated as a multiattribute decision analysis paradigm; the multiobjective optimization, which is performed on a PRA model and reliability cost functions, serves as the guiding principle for reliability and risk allocation. The concept of noninferiority is used in the multiobjective optimization problem. Finding the noninferior solution set is the main theme of the current approach. The assessment of the decision maker's preferences could then be performed more easily on the noninferior solution set. Some results of the methodology applications to a nontrivial risk model are provided and several outstanding issues such as generic allocation and preference assessment are discussed

A Thrust Allocation Method for Efficient Dynamic Positioning of a Semisubmersible Drilling Rig Based on the Hybrid Optimization Algorithm

Directory of Open Access Journals (Sweden)

Luman Zhao

2015-01-01

Full Text Available A thrust allocation method was proposed based on a hybrid optimization algorithm to efficiently and dynamically position a semisubmersible drilling rig. That is, the thrust allocation was optimized to produce the generalized forces and moment required while at the same time minimizing the total power consumption under the premise that forbidden zones should be taken into account. An optimization problem was mathematically formulated to provide the optimal thrust allocation by introducing the corresponding design variables, objective function, and constraints. A hybrid optimization algorithm consisting of a genetic algorithm and a sequential quadratic programming (SQP algorithm was selected and used to solve this problem. The proposed method was evaluated by applying it to a thrust allocation problem for a semisubmersible drilling rig. The results indicate that the proposed method can be used as part of a cost-effective strategy for thrust allocation of the rig.

Application of the NSGA-II algorithm to a multi-period inventory-redundancy allocation problem in a series-parallel system

International Nuclear Information System (INIS)

Alikar, Najmeh; Mousavi, Seyed Mohsen; Raja Ghazilla, Raja Ariffin; Tavana, Madjid; Olugu, Ezutah Udoncy

2017-01-01

In this paper, we formulate a mixed-integer binary non-linear programming model to study a series-parallel multi-component multi-periodic inventory-redundancy allocation problem (IRAP). This IRAP is a novel redundancy allocation problem (RAP) because components (products) are purchased under an all unit discount (AUD) policy and then installed on a series-parallel system. The total budget available for purchasing the components, the storage space, the vehicle capacities, and the total weight of the system are limited. Moreover, a penalty function is used to penalize infeasible solutions, generated randomly. The overall goal is to find the optimal number of the components purchased for each subsystem so that the total costs including ordering cost, holding costs, and purchasing cost are minimized while the system reliability is maximized, simultaneously. A non-dominated sorting genetic algorithm-II (NSGA-II), a multi-objective particle swarm optimization (MOPSO), and a multi-objective harmony search (MOHS) algorithm are applied to obtain the optimal Pareto solutions. While no benchmark is available in the literature, some numerical examples are generated randomly to evaluate the results of NSGA-II on the proposed IRAP. The results are in favor of NSGA-II. - Highlights: • An inventory control system employing an all-unit discount policy is considered in the proposed model. • The proposed model considers limited total budget, storage space, transportation capacity, and total weight. Moreover, a penalty function is used to penalize infeasible solutions. • The overall goal is to find the optimal number components purchased for each subsystem so that the total costs including ordering cost, holding cost and purchasing cost are minimized and the system reliability are maximized, simultaneously. • A NSGA-II algorithm is derived where a multi-objective particle swarm optimization and a multi-objective harmony search algorithm are used to evaluate the NSGA-II results.

Economics and the refinery's CO{sub 2} emissions allocation problem; Allocation des emissions de CO{sub 2} d'une raffinerie: solutions suggerees par la theorie economique

Energy Technology Data Exchange (ETDEWEB)

Pierru, A. [Institut Francais du Petrole (IFP), IFP School, 92 - Rueil-Malmaison (France)

2007-07-01

The establishment of a market for CO{sub 2} emission rights in Europe leads oil-refining companies to add a cost associated with carbon emissions to the objective function of linear programming models used to manage refineries. These models may be used to compute the marginal contribution of each finished product to the CO{sub 2} emissions of the refinery. Babusiaux (Oil. Gas Sci. Technol., 58, 2003, 685-692) has shown that, under some conditions, this marginal contribution is a relevant means of allocating the carbon emissions of the refinery. Thus, it can be used in a well-to-wheel Life Cycle Assessment. In fact, this result holds if the demand equations are the only binding constraints with a non-zero right-hand side coefficient. This is not the case for short-run models with fixed capacity. Then, allocating CO{sub 2} emissions on a marginal basis tends to over-value (or undervalue) the total volume of emissions. In order to extend the existing methodology, we discuss two distinct solutions to this problem, inspired by economic theory: adapting either the Aumann-Shapley cost sharing method (Values of non-atomic games, 1974, Princeton University Press) or the Ramsey pricing formula (Econ. J., 37, 1927, 47-61; J. Econ. Theory, 3, 1971, 219-240). We compare these two solutions, with a strong argument in favour of Ramsey prices, based on the determination of the optimal environmental tax rate to which imported finished products should be subject. (author)

Optimal water resource allocation modelling in the Lowveld of Zimbabwe

Directory of Open Access Journals (Sweden)

D. Mhiribidi

2018-05-01

Full Text Available The management and allocation of water from multi-reservoir systems is complex and thus requires dynamic modelling systems to achieve optimality. A multi-reservoir system in the Southern Lowveld of Zimbabwe is used for irrigation of sugarcane estates that produce sugar for both local and export consumption. The system is burdened with water allocation problems, made worse by decommissioning of dams. Thus the aim of this research was to develop an operating policy model for the Lowveld multi-reservoir system.The Mann Kendall Trend and Wilcoxon Signed-Rank tests were used to assess the variability of historic monthly rainfall and dam inflows for the period 1899–2015. The WEAP model was set up to evaluate the water allocation system of the catchment and come-up with a reference scenario for the 2015/2016 hydrologic year. Stochastic Dynamic Programming approach was used for optimisation of the multi-reservoirs releases.Results showed no significant trend in the rainfall but a significantly decreasing trend in inflows (p < 0.05. The water allocation model (WEAP showed significant deficits ( ∼  40 % in irrigation water allocation in the reference scenario. The optimal rule curves for all the twelve months for each reservoir were obtained and considered to be a proper guideline for solving multi- reservoir management problems within the catchment. The rule curves are effective tools in guiding decision makers in the release of water without emptying the reservoirs but at the same time satisfying the demands based on the inflow, initial storage and end of month storage.

Momentum and mean-reversion in strategic asset allocation

NARCIS (Netherlands)

Koijen, R.S.J.; Rodriguez, J.C.; Sbuelz, A.

2009-01-01

We study a dynamic asset allocation problem in which stock returns exhibit short-run momentum and long-run mean reversion. We develop a tractable continuous-time model that captures these two predictability features and derive the optimal investment strategy in closed form. The model predicts

Multi-objective reliability redundancy allocation in an interval environment using particle swarm optimization

International Nuclear Information System (INIS)

Zhang, Enze; Chen, Qingwei

2016-01-01

Most of the existing works addressing reliability redundancy allocation problems are based on the assumption of fixed reliabilities of components. In real-life situations, however, the reliabilities of individual components may be imprecise, most often given as intervals, under different operating or environmental conditions. This paper deals with reliability redundancy allocation problems modeled in an interval environment. An interval multi-objective optimization problem is formulated from the original crisp one, where system reliability and cost are simultaneously considered. To render the multi-objective particle swarm optimization (MOPSO) algorithm capable of dealing with interval multi-objective optimization problems, a dominance relation for interval-valued functions is defined with the help of our newly proposed order relations of interval-valued numbers. Then, the crowding distance is extended to the multi-objective interval-valued case. Finally, the effectiveness of the proposed approach has been demonstrated through two numerical examples and a case study of supervisory control and data acquisition (SCADA) system in water resource management. - Highlights: • We model the reliability redundancy allocation problem in an interval environment. • We apply the particle swarm optimization directly on the interval values. • A dominance relation for interval-valued multi-objective functions is defined. • The crowding distance metric is extended to handle imprecise objective functions.

Optimum design for pipe-support allocation against seismic loading

International Nuclear Information System (INIS)

Hara, Fumio; Iwasaki, Akira

1996-01-01

This paper deals with the optimum design methodology of a piping system subjected to a seismic design loading to reduce its dynamic response by selecting the location of pipe supports and whereby reducing the number of pipe supports to be used. The author employs the Genetic Algorithm for obtaining a reasonably optimum solution of the pipe support location, support capacity and number of supports. The design condition specified by the support location, support capacity and the number of supports to be used is encored by an integer number string for each of the support allocation candidates and they prepare many strings for expressing various kinds of pipe-support allocation state. Corresponding to each string, the authors evaluate the seismic response of the piping system to the design seismic excitation and apply the Genetic Algorithm to select the next generation candidates of support allocation to improve the seismic design performance specified by a weighted linear combination of seismic response magnitude, support capacity and the number of supports needed. Continuing this selection process, they find a reasonably optimum solution to the seismic design problem. They examine the feasibility of this optimum design method by investigating the optimum solution for 5, 7 and 10 degree-of-freedom models of piping system, and find that this method can offer one a theoretically feasible solution to the problem. They will be, thus, liberated from the severe uncertainty of damping value when the pipe support guaranties the design capacity of damping. Finally, they discuss the usefulness of the Genetic Algorithm for the seismic design problem of piping systems and some sensitive points when it will be applied to actual design problems

Nigerian agricultural sector and budgetary allocation, 1990-2008 ...

African Journals Online (AJOL)

The government budget is a financial statement of the government's proposed expenditure and expected revenue during a particular period (usually a year). By manipulating the size and structure of the government expenditure (allocation) and revenue, government can solve a number of macro-economic problems such as ...

The development of social-realistic «tropes» in the screenwriting of the early 1960s: based on Gennady Shpalikov’s screenplay «Berth»

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Artemyeva E.A.

2017-06-01

Full Text Available the paper focuses on the development of the social-realistic tradition in the culture of the early 1960s. Special attention is paid to the first full-length feature Gennady Shpalikov’s screenplay «Berth», which is an example of the development and the change of social-realistic «tropes» in the screenwriting of «Ottepel / the Thaw»: «a positive hero», «big family» and «war». The author concludes that these fundamental «tropes» define all Shpalikov’s work, the screenwriting and the poetry.

Allocation and sequencing in 1-out-of-N heterogeneous cold-standby systems: Multi-objective harmony search with dynamic parameters tuning

International Nuclear Information System (INIS)

Valaei, M.R.; Behnamian, J.

2017-01-01

A redundancy allocation is a famous problem in reliability sciences. A lot of researcher investigated about this problem, but a few of them focus on heterogeneous 1-out-of-N: G cold-standby redundancy in each subsystem. This paper considers a redundancy allocation problem (RAP) and standby element sequencing problem (SESP) for 1-out-of-N: G heterogeneous cold-standby system, simultaneously. Moreover, here, maximizing reliability of cold-standby allocation and minimizing cost of buying and time-independent elements are considered as two conflict objectives. This problem is NP-Hard and consequently, devizing a metaheuristic to solve this problem, especially for large-sized instances, is highly desirable. In this paper, we propose a multi-objective harmony search. Based on Taguchi experimental design, we, also, present a new parameters tuning method to improve the proposed algorithm. - Graphical abstract: Example of solution encoding. - Highlights: • This paper considers a redundancy allocation and standby element sequencing problem. • To solve this problem, a multi-objective harmony search algorithm is proposed. • Dynamic parameters tuning method is applied to improved the algorithm. • With this method, sensitivity of the algorithm to initial parameters is reduced.

Allocation and management issues in multiple-transaction open access transmission networks

Science.gov (United States)

Tao, Shu

This thesis focuses on some key issues related to allocation and management by the independent grid operator (IGO) of unbundled services in multiple-transaction open access transmission networks. The three unbundled services addressed in the thesis are transmission real power losses, reactive power support requirements from generation sources, and transmission congestion management. We develop the general framework that explicitly represents multiple transactions undertaken simultaneously in the transmission grid. This framework serves as the basis for formulating various problems treated in the thesis. We use this comprehensive framework to develop a physical-flow-based mechanism to allocate the total transmission losses to each transaction using the system. An important property of the allocation scheme is its capability to effectively deal with counter flows that result in the presence of specific transactions. Using the loss allocation results as the basis, we construct the equivalent loss compensation concept and apply it to develop flexible and effective procedures for compensating losses in multiple-transaction networks. We present a new physical-flow-based mechanism for allocating the reactive power support requirements provided by generators in multiple-transaction networks. The allocatable reactive support requirements are formulated as the sum of two specific components---the voltage magnitude variation component and the voltage angle variation component. The formulation utilizes the multiple-transaction framework and makes use of certain simplifying approximations. The formulation leads to a natural allocation as a function of the amount of each transaction. The physical interpretation of each allocation as a sensitivity of the reactive output of a generator is discussed. We propose a congestion management allocation scheme for multiple-transaction networks. The proposed scheme determines the allocation of congestion among the transactions on a physical

An improved model for the oPtImal Measurement Probes Allocation tool

International Nuclear Information System (INIS)

Sterle, C.; Neto, A.C.; De Tommasi, G.

2015-01-01

Highlights: • The problem of optimally allocating the probes of a diagnostic system is tackled. • The problem is decomposed in two consecutive optimization problems. • Two original ILP models are proposed and sequentially solved to optimality. • The proposed ILP models improve and extend the previous work present in literature. • Real size instances have been optimally solved with very low computation time. - Abstract: The oPtImal Measurement Probes Allocation (PIMPA) tool has been recently proposed in [1] to maximize the reliability of a tokamak diagnostic system against the failure of one or more of the processing nodes. PIMPA is based on the solution of integer linear programming (ILP) problems, and it minimizes the effect of the failure of a data acquisition component. The first formulation of the PIMPA model did not support the concept of individual slots. This work presents an improved ILP model that addresses the above mentioned problem, by taking into account all the individual probes.

An improved model for the oPtImal Measurement Probes Allocation tool

Energy Technology Data Exchange (ETDEWEB)

Sterle, C., E-mail: claudio.sterle@unina.it [Consorzio CREATE/Dipartimento di Ingegneria Elettrica e delle Tecnologie dell’Informazione, Università degli Studi di Napoli Federico II, Via Claudio 21, 80125 Napoli (Italy); Neto, A.C. [Fusion for Energy, 08019 Barcelona (Spain); De Tommasi, G. [Consorzio CREATE/Dipartimento di Ingegneria Elettrica e delle Tecnologie dell’Informazione, Università degli Studi di Napoli Federico II, Via Claudio 21, 80125 Napoli (Italy)

2015-10-15

Highlights: • The problem of optimally allocating the probes of a diagnostic system is tackled. • The problem is decomposed in two consecutive optimization problems. • Two original ILP models are proposed and sequentially solved to optimality. • The proposed ILP models improve and extend the previous work present in literature. • Real size instances have been optimally solved with very low computation time. - Abstract: The oPtImal Measurement Probes Allocation (PIMPA) tool has been recently proposed in [1] to maximize the reliability of a tokamak diagnostic system against the failure of one or more of the processing nodes. PIMPA is based on the solution of integer linear programming (ILP) problems, and it minimizes the effect of the failure of a data acquisition component. The first formulation of the PIMPA model did not support the concept of individual slots. This work presents an improved ILP model that addresses the above mentioned problem, by taking into account all the individual probes.

Resource allocation for wildland fire suppression planning using a stochastic program

Science.gov (United States)

Alex Taylor Masarie

2011-01-01

Resource allocation for wildland fire suppression problems, referred to here as Fire-S problems, have been studied for over a century. Not only have the many variants of the base Fire-S problem made it such a durable one to study, but advances in suppression technology and our ever-expanding knowledge of and experience with wildland fire behavior have required almost...

A Stochastic Flows Approach for Asset Allocation with Hidden Economic Environment

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Tak Kuen Siu

2015-01-01

Full Text Available An optimal asset allocation problem for a quite general class of utility functions is discussed in a simple two-state Markovian regime-switching model, where the appreciation rate of a risky share changes over time according to the state of a hidden economy. As usual, standard filtering theory is used to transform a financial model with hidden information into one with complete information, where a martingale approach is applied to discuss the optimal asset allocation problem. Using a martingale representation coupled with stochastic flows of diffeomorphisms for the filtering equation, the integrand in the martingale representation is identified which gives rise to an optimal portfolio strategy under some differentiability conditions.

Optimization of Power Allocation for Multiusers in Multi-Spot-Beam Satellite Communication Systems

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Heng Wang

2014-01-01

Full Text Available In recent years, multi-spot-beam satellite communication systems have played a key role in global seamless communication. However, satellite power resources are scarce and expensive, due to the limitations of satellite platform. Therefore, this paper proposes optimizing the power allocation of each user in order to improve the power utilization efficiency. Initially the capacity allocated to each user is calculated according to the satellite link budget equations, which can be achieved in the practical satellite communication systems. The problem of power allocation is then formulated as a convex optimization, taking account of a trade-off between the maximization of the total system capacity and the fairness of power allocation amongst the users. Finally, an iterative algorithm based on the duality theory is proposed to obtain the optimal solution to the optimization. Compared with the traditional uniform resource allocation or proportional resource allocation algorithms, the proposed optimal power allocation algorithm improves the fairness of power allocation amongst the users. Moreover, the computational complexity of the proposed algorithm is linear with both the numbers of the spot beams and users. As a result, the proposed power allocation algorithm is easy to be implemented in practice.

A Dynamic Pricing Reverse Auction-Based Resource Allocation Mechanism in Cloud Workflow Systems

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Xuejun Li

2016-01-01

Full Text Available Market-oriented reverse auction is an efficient and cost-effective method for resource allocation in cloud workflow systems since it can dynamically allocate resources depending on the supply-demand relationship of the cloud market. However, during the auction the price of cloud resource is usually fixed, and the current resource allocation mechanisms cannot adapt to the changeable market properly which results in the low efficiency of resource utilization. To address such a problem, a dynamic pricing reverse auction-based resource allocation mechanism is proposed. During the auction, resource providers can change prices according to the trading situation so that our novel mechanism can increase the chances of making a deal and improve efficiency of resource utilization. In addition, resource providers can improve their competitiveness in the market by lowering prices, and thus users can obtain cheaper resources in shorter time which would decrease monetary cost and completion time for workflow execution. Experiments with different situations and problem sizes are conducted for dynamic pricing-based allocation mechanism (DPAM on resource utilization and the measurement of Time⁎Cost (TC. The results show that our DPAM can outperform its representative in resource utilization, monetary cost, and completion time and also obtain the optimal price reduction rates.

Estimation of Distribution Algorithm for Resource Allocation in Green Cooperative Cognitive Radio Sensor Networks

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Alagan Anpalagan

2013-04-01

Full Text Available Due to the rapid increase in the usage and demand of wireless sensor networks (WSN, the limited frequency spectrum available for WSN applications will be extremely crowded in the near future. More sensor devices also mean more recharging/replacement of batteries, which will cause significant impact on the global carbon footprint. In this paper, we propose a relay-assisted cognitive radio sensor network (CRSN that allocates communication resources in an environmentally friendly manner. We use shared band amplify and forward relaying for cooperative communication in the proposed CRSN. We present a multi-objective optimization architecture for resource allocation in a green cooperative cognitive radio sensor network (GC-CRSN. The proposed multi-objective framework jointly performs relay assignment and power allocation in GC-CRSN, while optimizing two conflicting objectives. The first objective is to maximize the total throughput, and the second objective is to minimize the total transmission power of CRSN. The proposed relay assignment and power allocation problem is a non-convex mixed-integer non-linear optimization problem (NC-MINLP, which is generally non-deterministic polynomial-time (NP-hard. We introduce a hybrid heuristic algorithm for this problem. The hybrid heuristic includes an estimation-of-distribution algorithm (EDA for performing power allocation and iterative greedy schemes for constraint satisfaction and relay assignment. We analyze the throughput and power consumption tradeoff in GC-CRSN. A detailed analysis of the performance of the proposed algorithm is presented with the simulation results.

Optimal Computing Budget Allocation for Particle Swarm Optimization in Stochastic Optimization.

Science.gov (United States)

Zhang, Si; Xu, Jie; Lee, Loo Hay; Chew, Ek Peng; Wong, Wai Peng; Chen, Chun-Hung

2017-04-01

Particle Swarm Optimization (PSO) is a popular metaheuristic for deterministic optimization. Originated in the interpretations of the movement of individuals in a bird flock or fish school, PSO introduces the concept of personal best and global best to simulate the pattern of searching for food by flocking and successfully translate the natural phenomena to the optimization of complex functions. Many real-life applications of PSO cope with stochastic problems. To solve a stochastic problem using PSO, a straightforward approach is to equally allocate computational effort among all particles and obtain the same number of samples of fitness values. This is not an efficient use of computational budget and leaves considerable room for improvement. This paper proposes a seamless integration of the concept of optimal computing budget allocation (OCBA) into PSO to improve the computational efficiency of PSO for stochastic optimization problems. We derive an asymptotically optimal allocation rule to intelligently determine the number of samples for all particles such that the PSO algorithm can efficiently select the personal best and global best when there is stochastic estimation noise in fitness values. We also propose an easy-to-implement sequential procedure. Numerical tests show that our new approach can obtain much better results using the same amount of computational effort.

An Enhanced OFDM Resource Allocation Algorithm in C-RAN Based 5G Public Safety Network

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Lei Feng

2016-01-01

Full Text Available Public Safety Network (PSN is the network for critical communication when disaster occurs. As a key technology in 5G, Cloud-Radio Access Network (C-RAN can play an important role in PSN instead of LTE-based RAN. This paper firstly introduces C-RAN based PSN architecture and models the OFDM resource allocation problem in C-RAN based PSN as an integer quadratic programming, which allows the trade-off between expected bitrates and allocating fairness of PSN Service User (PSU. However, C-RAN based PSN needs to improve the efficiency of allocating algorithm because of a mass of PSU-RRH associations when disaster occurs. To deal with it, the resources allocating problem with integer variables is relaxed into one with continuous variables in the first step and an algorithm based on Generalized Bender’s Decomposition (GBD is proposed to solve it. Then we use Feasible Pump (FP method to get a feasible integer solution on the original OFDM resources allocation problem. The final experiments show the total throughput achieved by C-RAN based PSN is at most higher by 19.17% than the LTE-based one. And the average computational time of the proposed GBD and FP algorithm is at most lower than Barrier by 51.5% and GBD with no relaxation by 30.1%, respectively.

Combined Rate and Power Allocation with Link Scheduling in Wireless Data Packet Relay Networks with Fading Channels

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Subhrakanti Dey

2007-08-01

Full Text Available We consider a joint rate and power control problem in a wireless data traffic relay network with fading channels. The optimization problem is formulated in terms of power and rate selection, and link transmission scheduling. The objective is to seek high aggregate utility of the relay node when taking into account buffer load management and power constraints. The optimal solution for a single transmitting source is computed by a two-layer dynamic programming algorithm which leads to optimal power, rate, and transmission time allocation at the wireless links. We further consider an optimal power allocation problem for multiple transmitting sources in the same framework. Performances of the resource allocation algorithms including the effect of buffer load control are illustrated via extensive simulation studies.

Generation and exploration of aggregation abstractions for scheduling and resource allocation

Science.gov (United States)

Lowry, Michael R.; Linden, Theodore A.

1993-01-01

This paper presents research on the abstraction of computational theories for scheduling and resource allocation. The paper describes both theory and methods for the automated generation of aggregation abstractions and approximations in which detailed resource allocation constraints are replaced by constraints between aggregate demand and capacity. The interaction of aggregation abstraction generation with the more thoroughly investigated abstractions of weakening operator preconditions is briefly discussed. The purpose of generating abstract theories for aggregated demand and resources includes: answering queries about aggregate properties, such as gross feasibility; reducing computational costs by using the solution of aggregate problems to guide the solution of detailed problems; facilitating reformulating theories to approximate problems for which there are efficient problem-solving methods; and reducing computational costs of scheduling by providing more opportunities for variable and value-ordering heuristics to be effective. Experiments are being developed to characterize the properties of aggregations that make them cost effective. Both abstract and concrete theories are represented in a variant of first-order predicate calculus, which is a parameterized multi-sorted logic that facilitates specification of large problems. A particular problem is conceptually represented as a set of ground sentences that is consistent with a quantified theory.

Comprehensive reliability allocation method for CNC lathes based on cubic transformed functions of failure mode and effects analysis

Science.gov (United States)

Yang, Zhou; Zhu, Yunpeng; Ren, Hongrui; Zhang, Yimin

2015-03-01

Reliability allocation of computerized numerical controlled(CNC) lathes is very important in industry. Traditional allocation methods only focus on high-failure rate components rather than moderate failure rate components, which is not applicable in some conditions. Aiming at solving the problem of CNC lathes reliability allocating, a comprehensive reliability allocation method based on cubic transformed functions of failure modes and effects analysis(FMEA) is presented. Firstly, conventional reliability allocation methods are introduced. Then the limitations of direct combination of comprehensive allocation method with the exponential transformed FMEA method are investigated. Subsequently, a cubic transformed function is established in order to overcome these limitations. Properties of the new transformed functions are discussed by considering the failure severity and the failure occurrence. Designers can choose appropriate transform amplitudes according to their requirements. Finally, a CNC lathe and a spindle system are used as an example to verify the new allocation method. Seven criteria are considered to compare the results of the new method with traditional methods. The allocation results indicate that the new method is more flexible than traditional methods. By employing the new cubic transformed function, the method covers a wider range of problems in CNC reliability allocation without losing the advantages of traditional methods.

Resource Allocation for the Multiband Relay Channel: A Building Block for Hybrid Wireless Networks

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Kyounghwan Lee

2010-01-01

Full Text Available We investigate optimal resource allocation for the multiband relay channel. We find the optimal power and bandwidth allocation strategies that maximize the bounds on the capacity, by solving the corresponding max-min optimization problem. We provide sufficient conditions under which the associated max-min problem is equivalent to a supporting plane problem, which renders the solution for an arbitrary number of bands tractable. In addition, the sufficient conditions derived are general enough so that a class of utility functions can be accommodated with this formulation. As an example, we concentrate on the case where the source has two bands and the relay has a single band available and find the optimal resource allocation. We observe that joint power and bandwidth optimization always yields higher achievable rates than power optimization alone, establishing the merit of bandwidth sharing. Motivated by our analytical results, we examine a simple scenario where new channels become available for a transmitter to communicate; that is, new source to relay bands are added to a frequency division relay network. Given the channel conditions of the network, we establish the guidelines on how to allocate resources in order to achieve higher rates, depending on the relative quality of the available links.

Concurrent airline fleet allocation and aircraft design with profit modeling for multiple airlines

Science.gov (United States)

Govindaraju, Parithi

A "System of Systems" (SoS) approach is particularly beneficial in analyzing complex large scale systems comprised of numerous independent systems -- each capable of independent operations in their own right -- that when brought in conjunction offer capabilities and performance beyond the constituents of the individual systems. The variable resource allocation problem is a type of SoS problem, which includes the allocation of "yet-to-be-designed" systems in addition to existing resources and systems. The methodology presented here expands upon earlier work that demonstrated a decomposition approach that sought to simultaneously design a new aircraft and allocate this new aircraft along with existing aircraft in an effort to meet passenger demand at minimum fleet level operating cost for a single airline. The result of this describes important characteristics of the new aircraft. The ticket price model developed and implemented here enables analysis of the system using profit maximization studies instead of cost minimization. A multiobjective problem formulation has been implemented to determine characteristics of a new aircraft that maximizes the profit of multiple airlines to recognize the fact that aircraft manufacturers sell their aircraft to multiple customers and seldom design aircraft customized to a single airline's operations. The route network characteristics of two simple airlines serve as the example problem for the initial studies. The resulting problem formulation is a mixed-integer nonlinear programming problem, which is typically difficult to solve. A sequential decomposition strategy is applied as a solution methodology by segregating the allocation (integer programming) and aircraft design (non-linear programming) subspaces. After solving a simple problem considering two airlines, the decomposition approach is then applied to two larger airline route networks representing actual airline operations in the year 2005. The decomposition strategy serves

Resource Allocation for Sustainable Urban Transit from a Transport Diversity Perspective

Directory of Open Access Journals (Sweden)

Cheng-Min Feng

2009-11-01

Full Text Available Different transport stakeholders have different needs for transport infrastructure and services. Meeting the needs of all stakeholders implies a trade-off of benefits and costs between supply and demand and creates transport diversity issues. However, the literature has largely ignored these issues. Transport diversity can assess the level to which important needs are satisfied equitably, and monitor whether transportation systems are moving towards sustainability by confirming the targets and basic level of quality of life. Based on the concept of transport diversity, this study utilizes fuzzy multi-objective programming to solve non-linear multi-objective problems involving urban public transit systems to determine the impact of resource allocation on needs satisfaction in relation to stakeholder behaviors. The proposed approach avoids problems of inefficient and inequitable resource allocation. A real-life case is presented to demonstrate the feasibility of applying the proposed methodology. Furthermore, empirical outcomes show that recent investments allocated to public transit systems considered equitable stakeholder satisfaction for both mass rapid transit (MRT and bus, and also promoted transport diversity in the Taipei metropolitan area.

An Optimal Joint User Association and Power Allocation Algorithm for Secrecy Information Transmission in Heterogeneous Networks

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Rong Chai

2017-01-01

Full Text Available In recent years, heterogeneous radio access technologies have experienced rapid development and gradually achieved effective coordination and integration, resulting in heterogeneous networks (HetNets. In this paper, we consider the downlink secure transmission of HetNets where the information transmission from base stations (BSs to legitimate users is subject to the interception of eavesdroppers. In particular, we stress the problem of joint user association and power allocation of the BSs. To achieve data transmission in a secure and energy efficient manner, we introduce the concept of secrecy energy efficiency which is defined as the ratio of the secrecy transmission rate and power consumption of the BSs and formulate the problem of joint user association and power allocation as an optimization problem which maximizes the joint secrecy energy efficiency of all the BSs under the power constraint of the BSs and the minimum data rate constraint of user equipment (UE. By equivalently transforming the optimization problem into two subproblems, that is, power allocation subproblem and user association subproblem of the BSs, and applying iterative method and Kuhn-Munkres (K-M algorithm to solve the two subproblems, respectively, the optimal user association and power allocation strategies can be obtained. Numerical results demonstrate that the proposed algorithm outperforms previously proposed algorithms.

Distributed Multi-Cell Resource Allocation with Price Based ICI Coordination in Downlink OFDMA Networks

Science.gov (United States)

Lv, Gangming; Zhu, Shihua; Hui, Hui

Multi-cell resource allocation under minimum rate request for each user in OFDMA networks is addressed in this paper. Based on Lagrange dual decomposition theory, the joint multi-cell resource allocation problem is decomposed and modeled as a limited-cooperative game, and a distributed multi-cell resource allocation algorithm is thus proposed. Analysis and simulation results show that, compared with non-cooperative iterative water-filling algorithm, the proposed algorithm can remarkably reduce the ICI level and improve overall system performances.

Optimal resource allocation solutions for heterogeneous cognitive radio networks

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Babatunde Awoyemi

2017-05-01

Full Text Available Cognitive radio networks (CRN are currently gaining immense recognition as the most-likely next-generation wireless communication paradigm, because of their enticing promise of mitigating the spectrum scarcity and/or underutilisation challenge. Indisputably, for this promise to ever materialise, CRN must of necessity devise appropriate mechanisms to judiciously allocate their rather scarce or limited resources (spectrum and others among their numerous users. ‘Resource allocation (RA in CRN', which essentially describes mechanisms that can effectively and optimally carry out such allocation, so as to achieve the utmost for the network, has therefore recently become an important research focus. However, in most research works on RA in CRN, a highly significant factor that describes a more realistic and practical consideration of CRN has been ignored (or only partially explored, i.e., the aspect of the heterogeneity of CRN. To address this important aspect, in this paper, RA models that incorporate the most essential concepts of heterogeneity, as applicable to CRN, are developed and the imports of such inclusion in the overall networking are investigated. Furthermore, to fully explore the relevance and implications of the various heterogeneous classifications to the RA formulations, weights are attached to the different classes and their effects on the network performance are studied. In solving the developed complex RA problems for heterogeneous CRN, a solution approach that examines and exploits the structure of the problem in achieving a less-complex reformulation, is extensively employed. This approach, as the results presented show, makes it possible to obtain optimal solutions to the rather difficult RA problems of heterogeneous CRN.

Ant Colony Optimization Algorithm for Centralized Dynamic Channel Allocation in Multi-Cell OFDMA Systems

Science.gov (United States)

Kim, Hyo-Su; Kim, Dong-Hoi

The dynamic channel allocation (DCA) scheme in multi-cell systems causes serious inter-cell interference (ICI) problem to some existing calls when channels for new calls are allocated. Such a problem can be addressed by advanced centralized DCA design that is able to minimize ICI. Thus, in this paper, a centralized DCA is developed for the downlink of multi-cell orthogonal frequency division multiple access (OFDMA) systems with full spectral reuse. However, in practice, as the search space of channel assignment for centralized DCA scheme in multi-cell systems grows exponentially with the increase of the number of required calls, channels, and cells, it becomes an NP-hard problem and is currently too complicated to find an optimum channel allocation. In this paper, we propose an ant colony optimization (ACO) based DCA scheme using a low-complexity ACO algorithm which is a kind of heuristic algorithm in order to solve the aforementioned problem. Simulation results demonstrate significant performance improvements compared to the existing schemes in terms of the grade of service (GoS) performance and the forced termination probability of existing calls without degrading the system performance of the average throughput.

Allocation and Location of Transport Logistics Centres

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D. Mocková

2010-01-01

Full Text Available The facility allocation problem sets out to determine the optimal number of facilities to be opened. Based on multiple criteria evaluation, the optimal location of the facilities is usually solved subsequently. Several considerations, e.g. technical parameters, costs and finance must be taken into account. Economic analysis is carried out on the basis of the specific instance of the problem.Let us assume that the number of potentially located facilities is known. Then the problem of the optimal location of a given number of facilities in a network is referred to as the facility location problem. The solution to the problem is a set of facilities optimally located in an area such that this area is fully covered by the required services that the facilities provide. An example of a real-life problem of this type is the location of logistics centers. 

An Optimal Online Resource Allocation Algorithm for Energy Harvesting Body Area Networks

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Guangyuan Wu

2018-01-01

Full Text Available In Body Area Networks (BANs, how to achieve energy management to extend the lifetime of the body area networks system is one of the most critical problems. In this paper, we design a body area network system powered by renewable energy, in which the sensors carried by patient with energy harvesting module can transmit data to a personal device. We do not require any a priori knowledge of the stochastic nature of energy harvesting and energy consumption. We formulate a user utility optimization problem. We use Lyapunov Optimization techniques to decompose the problem into three sub-problems, i.e., battery management, collecting rate control and transmission power allocation. We propose an online resource allocation algorithm to achieve two major goals: (1 balancing sensors’ energy harvesting and energy consumption while stabilizing the BANs system; and (2 maximizing the user utility. Performance analysis addresses required battery capacity, bounded data queue length and optimality of the proposed algorithm. Simulation results verify the optimization of algorithm.

Fair Resource Allocation to Health Research: Priority Topics for Bioethics Scholarship.

Science.gov (United States)

Pratt, Bridget; Hyder, Adnan A

2017-07-01

This article draws attention to the limited amount of scholarship on what constitutes fairness and equity in resource allocation to health research by individual funders. It identifies three key decisions of ethical significance about resource allocation that research funders make regularly and calls for prioritizing scholarship on those topics - namely, how health resources should be fairly apportioned amongst public health and health care delivery versus health research, how health research resources should be fairly allocated between health problems experienced domestically versus other health problems typically experienced by disadvantaged populations outside the funder's country, and how domestic and non-domestic health research funding should be further apportioned to different areas, e.g. types of research and recipients. These three topics should be priorities for bioethics research because their outcomes have a substantial bearing on the achievement of health justice. The proposed agenda aims to move discussion on the ethics of health research funding beyond its current focus on the mismatch between worldwide basic and clinical research investment and the global burden of disease. Individual funders' decision-making on whether and to what extent to allocate resources to non-domestic health research, health systems research, research on the social determinants of health, capacity development, and recipients in certain countries should also be the focus of ethical scrutiny. © 2017 John Wiley & Sons Ltd.

Adolescence, Attention Allocation, and Driving Safety

OpenAIRE

Romer, Daniel; Lee, Yi-Ching; McDonald, Catherine C.; Winston, Flaura K.

2014-01-01

Motor vehicle crashes are the leading source of morbidity and mortality in adolescents in the United States and the developed world. Inadequate allocation of attention to the driving task and to driving hazards are important sources of adolescent crashes. We review major explanations for these attention failures with particular focus on the roles that brain immaturity and lack of driving experience play in causing attention problems. The review suggests that the potential for overcoming inexp...

A heuristic and hybrid method for the tank allocation problem in maritime bulk shipping

DEFF Research Database (Denmark)

Vilhelmsen, Charlotte; Larsen, Jesper; Lusby, Richard Martin

2016-01-01

In bulk shipping, ships often have multiple tanks and carry multiple inhomogeneous products at a time. When operating such ships it is therefore a major challenge to decide how to best allocate cargoes to available tanks while taking into account tank capacity, safety restrictions, ship stability...... finding a feasible solution. We have developed a heuristic that can efficiently find feasible cargo allocations. Computational results show that it can solve 99 % of the considered instances within 0.4 s and all of them if allowed longer time. We have also modified an optimality based method from...... the literature. The heuristic is much faster than this modified method on the vast majority of considered instances. However, the heuristic struggles on two instances which are relatively quickly solved by the modified optimality based method. These two methods therefore complement each other nicely and so, we...

A Heuristic and Hybrid Method for the Tank Allocation Problem in Maritime Bulk Shipping

DEFF Research Database (Denmark)

Vilhelmsen, Charlotte; Larsen, Jesper; Lusby, Richard Martin

In bulk shipping, ships often have multiple tanks and carry multiple inhomogeneous products at a time. When operating such ships it is therefore a major challenge to decide how to best allocate cargoes to available tanks while taking into account tank capacity, safety restrictions, ship stability...... finding a feasible solution. We have developed a heuristic that can efficiently find feasible cargo allocations. Computational results show that it can solve 99% of the considered instances within 0.4 seconds and all of them if allowed longer time. We have also modified an optimality based method from...... the literature. The heuristic is much faster than this modified method on the vast majority of considered instances. However, the heuristic struggles on two instances which are relatively quickly solved by the modified optimality based method. These two methods therefore complement each other nicely and so, we...

Method of reliability allocation based on fault tree analysis and fuzzy math in nuclear power plants

International Nuclear Information System (INIS)

Chen Zhaobing; Deng Jian; Cao Xuewu

2005-01-01

Reliability allocation is a kind of a difficult multi-objective optimization problem. It can not only be applied to determine the reliability characteristic of reactor systems, subsystem and main components but also be performed to improve the design, operation and maintenance of nuclear plants. The fuzzy math known as one of the powerful tools for fuzzy optimization and the fault analysis deemed to be one of the effective methods of reliability analysis can be applied to the reliability allocation model so as to work out the problems of fuzzy characteristic of some factors and subsystem's choice respectively in this paper. Thus we develop a failure rate allocation model on the basis of the fault tree analysis and fuzzy math. For the choice of the reliability constraint factors, we choose the six important ones according to practical need for conducting the reliability allocation. The subsystem selected by the top-level fault tree analysis is to avoid allocating reliability for all the equipment and components including the unnecessary parts. During the reliability process, some factors can be calculated or measured quantitatively while others only can be assessed qualitatively by the expert rating method. So we adopt fuzzy decision and dualistic contrast to realize the reliability allocation with the help of fault tree analysis. Finally the example of the emergency diesel generator's reliability allocation is used to illustrate reliability allocation model and improve this model simple and applicable. (authors)

Optimal Rate Allocation in Cluster-Tree WSNs

Directory of Open Access Journals (Sweden)

Jose Lopez Vicario

2011-03-01

Full Text Available In this paper, we propose a solution to the problem of guaranteed time slot allocation in cluster-tree WSNs. Our design uses the so-called Network Utility Maximization (NUM approach as far as we aim to provide a fair distribution of the available resources. From the point of view of implementation, we extend here the authors’ proposed Coupled-Decompositions Method (CDM in order to compute the NUM problem inside the cluster tree topology and we prove the optimality of this new extended version of the method. As a result, we obtain a distributed solution that reduces the total amount of signalling information in the network up to a factor of 500 with respect to the classical techniques, that is, primal and dual decomposition. This is possible because the CDM finds the optimal solution with a small number of iterations. Furthermore, when we compare our solution to the standard-proposed First Come First Serve (FCFS policy, we realize that FCFS becomes pretty unfair as the traffic load in the network increases and thus, a fair allocation of resources can be considered whenever the price to pay in terms of signalling and computational complexity is controlled.

Solving the redundancy allocation problem with multiple strategy choices using a new simplified particle swarm optimization

International Nuclear Information System (INIS)

Kong, Xiangyong; Gao, Liqun; Ouyang, Haibin; Li, Steven

2015-01-01

In most research on redundancy allocation problem (RAP), the redundancy strategy for each subsystem is assumed to be predetermined and fixed. This paper focuses on a specific RAP with multiple strategy choices (RAP-MSC), in which both active redundancy and cold standby redundancy can be selected as an additional decision variable for individual subsystems. To do so, the component type, redundancy strategy and redundancy level for each subsystem should be chosen subject to the system constraints appropriately such that the system reliability is maximized. Meanwhile, imperfect switching for cold standby redundancy is considered and a k-Erlang distribution is introduced to model the time-to-failure component as well. Given the importance and complexity of RAP-MSC, we propose a new efficient simplified version of particle swarm optimization (SPSO) to solve such NP-hard problems. In this method, a new position updating scheme without velocity is presented with stochastic disturbance and a low probability. Moreover, it is compared with several well-known PSO variants and other state-of-the-art approaches in the literature to evaluate its performance. The experiment results demonstrate the superiority of SPSO as an alternative for solving the RAP-MSC. - Highlights: • A more realistic RAP form with multiple strategy choices is focused. • Redundancy strategies are to be selected rather than fixed in general RAP. • A new simplified particle swarm optimization is proposed. • Higher reliabilities are achieved than the state-of-the-art approaches.

Relay Selection and Resource Allocation in One-Way and Two-Way Cognitive Relay Networks

KAUST Repository

Alsharoa, Ahmad M.

2013-01-01

In this work, the problem of relay selection and resource power allocation in one- way and two-way cognitive relay networks using half duplex channels with different relaying protocols is investigated. Optimization problems for both single

Marginal Contribution-Based Distributed Subchannel Allocation in Small Cell Networks.

Science.gov (United States)

Shah, Shashi; Kittipiyakul, Somsak; Lim, Yuto; Tan, Yasuo

2018-05-10

The paper presents a game theoretic solution for distributed subchannel allocation problem in small cell networks (SCNs) analyzed under the physical interference model. The objective is to find a distributed solution that maximizes the welfare of the SCNs, defined as the total system capacity. Although the problem can be addressed through best-response (BR) dynamics, the existence of a steady-state solution, i.e., a pure strategy Nash equilibrium (NE), cannot be guaranteed. Potential games (PGs) ensure convergence to a pure strategy NE when players rationally play according to some specified learning rules. However, such a performance guarantee comes at the expense of complete knowledge of the SCNs. To overcome such requirements, properties of PGs are exploited for scalable implementations, where we utilize the concept of marginal contribution (MC) as a tool to design learning rules of players’ utility and propose the marginal contribution-based best-response (MCBR) algorithm of low computational complexity for the distributed subchannel allocation problem. Finally, we validate and evaluate the proposed scheme through simulations for various performance metrics.

Marginal Contribution-Based Distributed Subchannel Allocation in Small Cell Networks

Directory of Open Access Journals (Sweden)

Shashi Shah

2018-05-01

Full Text Available The paper presents a game theoretic solution for distributed subchannel allocation problem in small cell networks (SCNs analyzed under the physical interference model. The objective is to find a distributed solution that maximizes the welfare of the SCNs, defined as the total system capacity. Although the problem can be addressed through best-response (BR dynamics, the existence of a steady-state solution, i.e., a pure strategy Nash equilibrium (NE, cannot be guaranteed. Potential games (PGs ensure convergence to a pure strategy NE when players rationally play according to some specified learning rules. However, such a performance guarantee comes at the expense of complete knowledge of the SCNs. To overcome such requirements, properties of PGs are exploited for scalable implementations, where we utilize the concept of marginal contribution (MC as a tool to design learning rules of players’ utility and propose the marginal contribution-based best-response (MCBR algorithm of low computational complexity for the distributed subchannel allocation problem. Finally, we validate and evaluate the proposed scheme through simulations for various performance metrics.

Chunk-Based Energy Efficient Resource Allocation in OFDMA Systems

Directory of Open Access Journals (Sweden)

Yong Li

2013-01-01

Full Text Available Energy efficiency (EE capacity analysis of the chunk-based resource allocation is presented by considering the minimum spectrum efficiency (SE constraint in downlink multiuser orthogonal frequency division multiplexing (OFDM systems. Considering the minimum SE requirement, an optimization problem to maximize EE with limited transmit power is formulated over frequency selective channels. Based on this model, a low-complexity energy efficient resource allocation is proposed. The effects of system parameters, such as the average channel gain-to-noise ratio (CNR and the number of subcarriers per chunk, are evaluated. Numerical results demonstrate the effectiveness of the proposed scheme for balancing the EE and SE.

A Heuristic and Hybrid Method for the Tank Allocation Problem in Maritime Bulk Shipping

DEFF Research Database (Denmark)

Vilhelmsen, Charlotte; Larsen, Jesper; Lusby, Richard Martin

Many bulk ships have multiple tanks and can thereby carry multiple inhomogeneous products at a time. A major challenge when operating such ships is how to best allocate cargoes to available tanks while taking tank capacity, safety restrictions, ship stability and strength as well as other...... ship route. We have developed a randomised heuristic for eciently nding feasible allocations and computational results show that it can solve 99% of the considered instances within 0.5 seconds and all of them if allowed longer time. The heuristic is designed to work as an ecient subproblem solver...... and in such a setting with running times below e.g. 5 seconds, the heuristic clearly outperforms an earlier method by consistently solving more instances and eectively cutting 84% of the average running time. Furthermore, we have combined our heuristic with a modied version of the earlier method to derive a hybrid...

Residency Allocation Database

Data.gov (United States)

Department of Veterans Affairs — The Residency Allocation Database is used to determine allocation of funds for residency programs offered by Veterans Affairs Medical Centers (VAMCs). Information...

Cluster Formation and Joint Power-Bandwidth Allocation for Imperfect NOMA in DL-HetNets

KAUST Repository

Celik, Abdulkadir; Al-Qahtani, Fawaz; Radaydeh, Redha; Alouini, Mohamed-Slim

2017-01-01

and estimation errors. Then, a generic cluster formation (CF) and Power-Bandwidth Allocation (PBA) is formulated as a mixed-integer non-linear programming (MINLP) problem for downlink (DL) heterogeneous networks (HetNets). After dividing the MINLP problem

Self-Coexistence among IEEE 802.22 Networks: Distributed Allocation of Power and Channel.

Science.gov (United States)

Sakin, Sayef Azad; Razzaque, Md Abdur; Hassan, Mohammad Mehedi; Alamri, Atif; Tran, Nguyen H; Fortino, Giancarlo

2017-12-07

Ensuring self-coexistence among IEEE 802.22 networks is a challenging problem owing to opportunistic access of incumbent-free radio resources by users in co-located networks. In this study, we propose a fully-distributed non-cooperative approach to ensure self-coexistence in downlink channels of IEEE 802.22 networks. We formulate the self-coexistence problem as a mixed-integer non-linear optimization problem for maximizing the network data rate, which is an NP-hard one. This work explores a sub-optimal solution by dividing the optimization problem into downlink channel allocation and power assignment sub-problems. Considering fairness, quality of service and minimum interference for customer-premises-equipment, we also develop a greedy algorithm for channel allocation and a non-cooperative game-theoretic framework for near-optimal power allocation. The base stations of networks are treated as players in a game, where they try to increase spectrum utilization by controlling power and reaching a Nash equilibrium point. We further develop a utility function for the game to increase the data rate by minimizing the transmission power and, subsequently, the interference from neighboring networks. A theoretical proof of the uniqueness and existence of the Nash equilibrium has been presented. Performance improvements in terms of data-rate with a degree of fairness compared to a cooperative branch-and-bound-based algorithm and a non-cooperative greedy approach have been shown through simulation studies.

Self-Coexistence among IEEE 802.22 Networks: Distributed Allocation of Power and Channel

Directory of Open Access Journals (Sweden)

Sayef Azad Sakin

2017-12-01

Full Text Available Ensuring self-coexistence among IEEE 802.22 networks is a challenging problem owing to opportunistic access of incumbent-free radio resources by users in co-located networks. In this study, we propose a fully-distributed non-cooperative approach to ensure self-coexistence in downlink channels of IEEE 802.22 networks. We formulate the self-coexistence problem as a mixed-integer non-linear optimization problem for maximizing the network data rate, which is an NP-hard one. This work explores a sub-optimal solution by dividing the optimization problem into downlink channel allocation and power assignment sub-problems. Considering fairness, quality of service and minimum interference for customer-premises-equipment, we also develop a greedy algorithm for channel allocation and a non-cooperative game-theoretic framework for near-optimal power allocation. The base stations of networks are treated as players in a game, where they try to increase spectrum utilization by controlling power and reaching a Nash equilibrium point. We further develop a utility function for the game to increase the data rate by minimizing the transmission power and, subsequently, the interference from neighboring networks. A theoretical proof of the uniqueness and existence of the Nash equilibrium has been presented. Performance improvements in terms of data-rate with a degree of fairness compared to a cooperative branch-and-bound-based algorithm and a non-cooperative greedy approach have been shown through simulation studies.

Reliability-oriented multi-resource allocation in a stochastic-flow network

International Nuclear Information System (INIS)

Hsieh, C.-C.; Lin, M.-H.

2003-01-01

A stochastic-flow network consists of a set of nodes, including source nodes which supply various resources and sink nodes at which resource demands take place, and a collection of arcs whose capacities have multiple operational states. The network reliability of such a stochastic-flow network is the probability that resources can be successfully transmitted from source nodes through multi-capacitated arcs to sink nodes. Although the evaluation schemes of network reliability in stochastic-flow networks have been extensively studied in the literature, how to allocate various resources at source nodes in a reliable means remains unanswered. In this study, a resource allocation problem in a stochastic-flow network is formulated that aims to determine the optimal resource allocation policy at source nodes subject to given resource demands at sink nodes such that the network reliability of the stochastic-flow network is maximized, and an algorithm for computing the optimal resource allocation is proposed that incorporates the principle of minimal path vectors. A numerical example is given to illustrate the proposed algorithm

The vehicle routing game: An application of cost allocation in a gas and oil company

Energy Technology Data Exchange (ETDEWEB)

Engevall, Stefan; Goethe-Lundgren, Maud; Vaerbrand, Peter

2000-12-01

In this article we study a cost allocation problem that arises in a distribution planning situation at the Logistics department at Norsk Hydro Olje AB. The routes from one depot during one day are considered, for which the total distribution cost is to be divided among the customers that are visited. This cost allocation problem is formulated as a vehicle routing game, allowing the use of vehicles with different capacities. Cost allocation methods based on different concepts from cooperative game theory, such as the core and the nucleolus, are discussed. A procedure that can be used to investigate whether the core is empty or not is presented, as well as a procedure to compute the nucleolus. Computational results for the Norsk Hydro case are also presented and discussed.

Interactive Land-Use Optimization Using Laguerre Voronoi Diagram with Dynamic Generating Point Allocation

Science.gov (United States)

Chaidee, S.; Pakawanwong, P.; Suppakitpaisarn, V.; Teerasawat, P.

2017-09-01

In this work, we devise an efficient method for the land-use optimization problem based on Laguerre Voronoi diagram. Previous Voronoi diagram-based methods are more efficient and more suitable for interactive design than discrete optimization-based method, but, in many cases, their outputs do not satisfy area constraints. To cope with the problem, we propose a force-directed graph drawing algorithm, which automatically allocates generating points of Voronoi diagram to appropriate positions. Then, we construct a Laguerre Voronoi diagram based on these generating points, use linear programs to adjust each cell, and reconstruct the diagram based on the adjustment. We adopt the proposed method to the practical case study of Chiang Mai University's allocated land for a mixed-use complex. For this case study, compared to other Voronoi diagram-based method, we decrease the land allocation error by 62.557 %. Although our computation time is larger than the previous Voronoi-diagram-based method, it is still suitable for interactive design.

Draft regulatory analysis: notice of proposed rulemaking motor gasoline allocation revisions

Energy Technology Data Exchange (ETDEWEB)

None

1980-06-01

The Draft Regulatory Analysis is prepared for those proposed regulations which either may have a major impact on the general economy, individual industries, or geographic regions and levels of government, or may be significant in that they affect important DOE policy concerns and are the object of public interest. The problems and proposed solutions for the Notice of Proposed Rulemaking and Public Hearings on the Motor Gasoline Allocation Program are examined. The ERA's mandate for this program is set out in the Emergency Petroleum Allocation Act of 1973. Under this Act, the President is empowered to enforce, at his discretion, price and allocation controls on petroleum and petroleum products, including gasoline, through September 30, 1981. The Act sets the following allocation goals: protect public health; maintain public services and agricultural operations; foster competition in the petroleum industry; distribute petroleum among industry sectors and US regions equitably; and minimize economic disruption and unnecessary interference wth market mechanisms.

An Ameliorative Whale Optimization Algorithm for Multi-Objective Optimal Allocation of Water Resources in Handan, China

Directory of Open Access Journals (Sweden)

Zhihong Yan

2018-01-01

Full Text Available With the deepening discrepancy between water supply and demand caused by water shortages, alleviating water shortages by optimizing water resource allocation has received extensive attention. How to allocate water resources optimally, rapidly, and effectively has become a challenging problem. Thus, this study employs a meta-heuristic swarm-based algorithm, the whale optimization algorithm (WOA. To overcome drawbacks like relatively low convergence precision and convergence rates, when applying the WOA algorithm to complex optimization problems, logistic mapping is used to initialize swarm location, and inertia weighting is employed to improve the algorithm. The resulting ameliorative whale optimization algorithm (AWOA shows substantially enhanced convergence rates and precision than the WOA and particle swarm optimization algorithms, demonstrating relatively high reliability and applicability. A water resource allocation optimization model with optimal economic efficiency and least total water shortage volume is established for Handan, China, and solved by the AWOA. The allocation results better reflect actual water usage in Handan. In 2030, the p = 50% total water shortage is forecast as 404.34 × 106 m3 or 14.8%. The shortage is mainly in the primary agricultural sector. The allocation results provide a reference for regional water resources management.

Near-optimal power allocation with PSO algorithm for MIMO cognitive networks using multiple AF two-way relays

KAUST Repository

Alsharoa, Ahmad M.

2014-06-01

In this paper, the problem of power allocation for a multiple-input multiple-output two-way system is investigated in underlay Cognitive Radio (CR) set-up. In the CR underlay mode, secondary users are allowed to exploit the spectrum allocated to primary users in an opportunistic manner by respecting a tolerated temperature limit. The secondary networks employ an amplify-and-forward two-way relaying technique in order to maximize the sum rate under power budget and interference constraints. In this context, we formulate an optimization problem that is solved in two steps. First, we derive a closed-form expression of the optimal power allocated to terminals. Then, we employ a strong optimization tool based on particle swarm optimization algorithm to find the power allocated to secondary relays. Simulation results demonstrate the efficiency of the proposed solution and analyze the impact of some system parameters on the achieved performance. © 2014 IEEE.

Allocation of losses in distribution system with dispersed generation of electricity

International Nuclear Information System (INIS)

Atanasovski, Metodija B.

2005-01-01

The problem of allocation of losses in distribution systems with dispersed generation (DG) of electricity is considered in this work. Definition of category DG, overview of technologies which belongs to this category and main features of each technology are given. Modeling of DG in steady state analysis of distribution networks is completely elaborated. Requirements for ideal allocation of losses are summarized. Methods from the literature, for allocation of losses in distribution systems with DG, are elaborated, as: classical distribution pricing method, substitution method, marginal loss coefficients method and nodal factors pricing method. In this work a new method for allocation of losses in distribution systems with DG is also presented. The new method is based on branches and resolves the problems of implementation of branch based methods for transmission networks to distribution networks. The method establishes direct relationship between losses in each branch of the network and injected active and reactive power in the nodes on which path to the root node the branch is placed. Reactive power is considered in the loss allocation process in this method and allocation of crossed terms of active and reactive power is performed using quadratic allocation of crossed terms. DG in this method is treated as negative power injection. It is assumed that the network is radial and the power flow in each branch of the, distribution network is constant and equal to the sum of injected active and reactive power in each node on which path to the root node, the branch is placed. The network is considered loss less. The new proposed method is applied and tested on real distribution network which is a part of Distribution company-Bitola. One distribution feeder of power station 110/10 kV/kV Bitola 4 is considered. Different types of consumers and two small hydro power plants in property of JP Strezevo as typical representatives of DG are connected to the feeder. Results

Multiarea Transmission Cost Allocation in Large Power Systems Using the Nodal Pricing Control Approach

Directory of Open Access Journals (Sweden)

M. Ghayeni

2010-12-01

Full Text Available This paper proposes an algorithm for transmission cost allocation (TCA in a large power system based on nodal pricing approach using the multi-area scheme. The nodal pricing approach is introduced to allocate the transmission costs by the control of nodal prices in a single area network. As the number of equations is dependent on the number of buses and generators, this method will be very time consuming for large power systems. To solve this problem, the present paper proposes a new algorithm based on multi-area approach for regulating the nodal prices, so that the simulation time is greatly reduced and therefore the TCA problem with nodal pricing approach will be applicable for large power systems. In addition, in this method the transmission costs are allocated to users more equitable. Since the higher transmission costs in an area having a higher reliability are paid only by users of that area in contrast with the single area method, in which these costs are allocated to all users regardless of their locations. The proposed method is implemented on the IEEE 118 bus test system which comprises three areas. Results show that with application of multi-area approach, the simulation time is greatly reduced and the transmission costs are also allocated to users with less variation in new nodal prices with respect to the single area approach.

Energy Efficient Power Allocation in Multi-tier 5G Networks Using Enhanced Online Learning

KAUST Repository

Alqerm, Ismail

2017-07-25

The multi-tier heterogeneous structure of 5G with dense small cells deployment, relays, and device-to-device (D2D) communications operating in an underlay fashion is envisioned as a potential solution to satisfy the future demand for cellular services. However, efficient power allocation among dense secondary transmitters that maintains quality of service (QoS) for macro (primary) cell users and secondary cell users is a critical challenge for operating such radio. In this paper, we focus on the power allocation problem in the multi-tier 5G network structure using a non-cooperative methodology with energy efficiency consideration. Therefore, we propose a distributive intuition-based online learning scheme for power allocation in the downlink of the 5G systems, where each transmitter surmises other transmitters power allocation strategies without information exchange. The proposed learning model exploits a brief state representation to account for the problem of dimensionality in online learning and expedite the convergence. The convergence of the proposed scheme is proved and numerical results demonstrate its capability to achieve fast convergence with QoS guarantee and significant improvement in system energy efficiency.

Unfair allocation of gains under equal price in cooperative purchasing

NARCIS (Netherlands)

Schotanus, Fredo; Calvi, R.; Merminod, N.

2005-01-01

Cooperative purchasing is becoming more and more common practice. However, many cooperative initiatives end prematurely or do not flourish. Important reasons indi-cated for these problems are directly or indirectly related to the unfair allocation of gains. The purpose of this paper is to analyse

Application research of power allocation based on Buck circuit in DC microgrid

OpenAIRE

Wang Zihao; Zhou Mingyu

2017-01-01

In a traditional DC microgrid, the power sharing control strategy has been always used in the distributed power converters, resulting in not making outer power allocation arbitrarily. In order to solve the power output allocation problem of wind power in DC microgrid, the intelligent Buck circuit based on PI algorithm and the load current feed-forward method was used to realize the arbitrary regulation of the output power of the wind power in the DC microgrid system. Compared with traditional...

Characterization of the loss allocation techniques for radial systems with distributed generation

International Nuclear Information System (INIS)

Carpaneto, Enrico; Chicco, Gianfranco; Sumaili Akilimali, Jean

2008-01-01

In the restructured electricity industry, meaningful loss allocation methods are required in order to send correct signals to the market taking into account the location and characteristics of loads and generations, including the local sources forming the distributed generation (DG). This paper addresses the issues related to loss allocation in radial distribution systems with DG, with a three-fold focus. First, the key differences in the formulation of the loss allocation problem for radial distribution systems with respect to transmission systems are discussed, specifying the modeling and computational issues concerning the treatment of the slack node in radial distribution systems. Then, the characteristics of derivative-based and circuit-based loss allocation techniques are presented and compared, illustrating the arrangements used for adapting the various techniques to be applied to radial distribution systems with DG. Finally, the effects of introducing voltage-controllable local generation on the calculation of the loss allocation coefficients are discussed, proposing the adoption of a ''reduced'' representation of the system capable of taking into proper account the characteristics of the nodes containing voltage-controllable DG units. Numerical results are provided to show the time evolution of the loss allocation coefficients for distribution systems with variable load and local generation patterns. (author)

Berthe Morisot, catalogue de l'exposition au Palais des Beaux-Arts de Lille et à la Fondation Pierre Gianadda à Martigny, éd. Fondation Pierre Gianadda, 2002, 461 p.

OpenAIRE

Bonnet, Marie-Jo

2004-01-01

L'exposition Berthe Morisot organisée conjointement par le Palais des Beaux-Arts de Lille et la fondation Pierre Gianadda, à Martigny, ainsi que son catalogue peuvent être regardés comme un véritable événement. D'abord, saluons la fondation suisse qui fait un travail de fond remarquable depuis de nombreuses années en exposant (avec catalogue) des artistes françaises comme Camille Claudel, Suzanne Valadon, Marie Laurencin, en collaboration avec des musées de province. Notons ensuite que...

Many-objective robust decision making for water allocation under climate change.

Science.gov (United States)

Yan, Dan; Ludwig, Fulco; Huang, He Qing; Werners, Saskia E

2017-12-31

Water allocation is facing profound challenges due to climate change uncertainties. To identify adaptive water allocation strategies that are robust to climate change uncertainties, a model framework combining many-objective robust decision making and biophysical modeling is developed for large rivers. The framework was applied to the Pearl River basin (PRB), China where sufficient flow to the delta is required to reduce saltwater intrusion in the dry season. Before identifying and assessing robust water allocation plans for the future, the performance of ten state-of-the-art MOEAs (multi-objective evolutionary algorithms) is evaluated for the water allocation problem in the PRB. The Borg multi-objective evolutionary algorithm (Borg MOEA), which is a self-adaptive optimization algorithm, has the best performance during the historical periods. Therefore it is selected to generate new water allocation plans for the future (2079-2099). This study shows that robust decision making using carefully selected MOEAs can help limit saltwater intrusion in the Pearl River Delta. However, the framework could perform poorly due to larger than expected climate change impacts on water availability. Results also show that subjective design choices from the researchers and/or water managers could potentially affect the ability of the model framework, and cause the most robust water allocation plans to fail under future climate change. Developing robust allocation plans in a river basin suffering from increasing water shortage requires the researchers and water managers to well characterize future climate change of the study regions and vulnerabilities of their tools. Copyright © 2017 Elsevier B.V. All rights reserved.

Stochastic Averaging for Constrained Optimization With Application to Online Resource Allocation

Science.gov (United States)

Chen, Tianyi; Mokhtari, Aryan; Wang, Xin; Ribeiro, Alejandro; Giannakis, Georgios B.

2017-06-01

Existing approaches to resource allocation for nowadays stochastic networks are challenged to meet fast convergence and tolerable delay requirements. The present paper leverages online learning advances to facilitate stochastic resource allocation tasks. By recognizing the central role of Lagrange multipliers, the underlying constrained optimization problem is formulated as a machine learning task involving both training and operational modes, with the goal of learning the sought multipliers in a fast and efficient manner. To this end, an order-optimal offline learning approach is developed first for batch training, and it is then generalized to the online setting with a procedure termed learn-and-adapt. The novel resource allocation protocol permeates benefits of stochastic approximation and statistical learning to obtain low-complexity online updates with learning errors close to the statistical accuracy limits, while still preserving adaptation performance, which in the stochastic network optimization context guarantees queue stability. Analysis and simulated tests demonstrate that the proposed data-driven approach improves the delay and convergence performance of existing resource allocation schemes.

Irrigation water allocation optimization using multi-objective evolutionary algorithm (MOEA) - a review

Science.gov (United States)

Fanuel, Ibrahim Mwita; Mushi, Allen; Kajunguri, Damian

2018-03-01

This paper analyzes more than 40 papers with a restricted area of application of Multi-Objective Genetic Algorithm, Non-Dominated Sorting Genetic Algorithm-II and Multi-Objective Differential Evolution (MODE) to solve the multi-objective problem in agricultural water management. The paper focused on different application aspects which include water allocation, irrigation planning, crop pattern and allocation of available land. The performance and results of these techniques are discussed. The review finds that there is a potential to use MODE to analyzed the multi-objective problem, the application is more significance due to its advantage of being simple and powerful technique than any Evolutionary Algorithm. The paper concludes with the hopeful new trend of research that demand effective use of MODE; inclusion of benefits derived from farm byproducts and production costs into the model.

Effect of optimum stratification on sampling with varying probabilities under proportional allocation

Directory of Open Access Journals (Sweden)

Syed Ejaz Husain Rizvi

2007-10-01

Full Text Available The problem of optimum stratification on an auxiliary variable when the units from different strata are selected with probability proportional to the value of auxiliary variable (PPSWR was considered by Singh (1975 for univariate case. In this paper we have extended the same problem, for proportional allocation, when two variates are under study. A cum. 3 R3(x rule for obtaining approximately optimum strata boundaries has been provided. It has been shown theoretically as well as empirically that the use of stratification has inverse effect on the relative efficiency of PPSWR as compared to unstratified PPSWR method when proportional method of allocation is envisaged. Further comparison showed that with increase in number of strata the stratified simple random sampling is equally efficient as PPSWR.

Cost allocation with limited information

DEFF Research Database (Denmark)

Hougaard, Jens Leth; Tind, Jørgen

This article investigates progressive development of Aumann-Shapley cost allocation in a multilevel organizational or production structure. In particular, we study a linear parametric programming setup utilizing the Dantzig-Wolfe decomposition procedure. Typically cost allocation takes place after...... all activities have been performed, for example by finishing all outputs. Here the allocation is made progressively with suggestions for activities. I other words cost allocation is performed in parallel for example with a production planning process. This development does not require detailed...... information about some technical constraints in order to make the cost allocation....

The Multi-unit Assignment Problem: Theory and Evidence from Course Allocation at Harvard

OpenAIRE

Budish, Eric; Cantillon, Estelle

2010-01-01

This paper uses data consisting of students' strategically reported preferences and their underlying true preferences to study the course allocation mechanism used at Harvard Business School. We show that the mechanism is manipulable in theory, manipulated in practice, and that these manipulations cause meaningful welfare losses. However, we also find that ex-ante welfare is higher than under the strategyproof and ex-post efficient alternative, the Random Serial Dictatorship. We trace the poo...

Energy-Efficient Resource and Power Allocation for Underlay Multicast Device-to-Device Transmission

Directory of Open Access Journals (Sweden)

Fan Jiang

2017-11-01

Full Text Available In this paper, we present an energy-efficient resource allocation and power control scheme for D2D (Device-to-Device multicasting transmission. The objective is to maximize the overall energy-efficiency of D2D multicast clusters through effective resource allocation and power control schemes, while considering the quality of service (QoS requirements of both cellular users (CUs and D2D clusters. We first build the optimization model and a heuristic resource and power allocation algorithm is then proposed to solve the energy-efficiency problem with less computational complexity. Numerical results indicate that the proposed algorithm outperforms existing schemes in terms of throughput per energy consumption.

Profit Allocation of Hybrid Power System Planning in Energy Internet: A Cooperative Game Study

Directory of Open Access Journals (Sweden)

Jicheng Liu

2018-02-01

Full Text Available The rapid development of Energy Internet (EI has prompted numbers of generators to participate, leading to a hybrid power system. Hence, how to plan the hybrid power system and allocate its profit becomes necessary. In this paper, the cooperative game theory is introduced to discuss this problem. We first design the basic structure of EI, and point out the object of this study—coal power plant-wind farm-photovoltaic power station-energy storage provider (CWPE alliance. Subsequently, average allocation strategy (AAS, capacity-based allocation strategy (CAS and Shapley value allocation strategy (SAS are proposed, and then the modified disruption propensity (MDP index is constructed to judge the advantages and disadvantages of the three schemes. Thirdly, taking a certain area of A Province as an example, the profits of CWPE under three strategies are calculated respectively. Finally, by analyzing individual rationality and collective rationality of cooperative game and the MDP index of the three profit allocation schemes, we find that SAS is the most stable.

Practical Approaches to Adaptive Resource Allocation in OFDM Systems

Directory of Open Access Journals (Sweden)

N. Y. Ermolova

2007-11-01

Full Text Available Whenever a communication system operates in a time-frequency dispersive radio channel, the link adaptation provides a benefit in terms of any system performance metric by employing time, frequency, and, in case of multiple users, multiuser diversities. With respect to an orthogonal frequency division multiplexing (OFDM system, link adaptation includes bit, power, and subcarrier allocations. While the well-known water-filling principle provides the optimal solution for both margin-maximization and rate-maximization problems, implementation complexity often makes difficult its application in practical systems. This paper presents a few suboptimal (low-complexity adaptive loading algorithms for both single- and multiuser OFDM systems. We show that the single-user system performance can be improved by suitable power loading and an algorithm based on the incomplete channel state information is derived. At the same time, the power loading in a multiuser system only slightly affects performance while the initial subcarrier allocation has a rather big impact. A number of subcarrier allocation algorithms are discussed and the best one is derived on the basis of the order statistics theory.

Dose-optimal vaccine allocation over multiple populations

OpenAIRE

Duijzer, Evelot; Jaarsveld, Willem; Wallinga, Jacco; Dekker, Rommert

2015-01-01

textabstractFor a large number of infectious diseases, vaccination is the most effective way to prevent an epidemic. However, the vaccine stockpile is hardly ever sufficient to treat the entire population, which brings about the challenge of vaccine allocation. To aid decision makers facing this challenge, we provide insights into the structure of this problem. We first investigate the dependence of health benefit on the fraction of people that receive vaccination, where we define health bene...

An application of data mining classification and bi-level programming for optimal credit allocation

Directory of Open Access Journals (Sweden)

Seyed Mahdi Sadatrasou

2015-01-01

Full Text Available This paper investigates credit allocation policy making and its effect on economic development using bi-level programming. There are two challenging problems in bi-level credit allocation; at the first level government/public related institutes must allocate the credit strategically concerning sustainable development to regions and industrial sectors. At the second level, there are agent banks, which should allocate the credit tactically to individual applicants based on their own profitability and risk using their credit scoring models. There is a conflict of interest between these two stakeholders but the cooperation is inevitable. In this paper, a new bi-level programming formulation of the leader-follower game in association with sustainable development theory in the first level and data mining classifier at the second level is used to mathematically model the problem. The model is applied to a national development fund (NDF as a government related organization and one of its agent banks. A new algorithm called Bi-level Genetic fuzzy apriori Algorithm (BGFAA is introduced to solve the bilateral model. Experimental results are presented and compared with a unilateral policy making scenario by the leader. Findings show that although the objective functions of the leader are worse in the bilateral scenario but agent banks collaboration is attracted and guaranteed.

Graph theoretical stable allocation as a tool for reproduction of control by human operators

Science.gov (United States)

van Nooijen, Ronald; Ertsen, Maurits; Kolechkina, Alla

2016-04-01

During the design of central control algorithms for existing water resource systems under manual control it is important to consider the interaction with parts of the system that remain under manual control and to compare the proposed new system with the existing manual methods. In graph theory the "stable allocation" problem has good solution algorithms and allows for formulation of flow distribution problems in terms of priorities. As a test case for the use of this approach we used the algorithm to derive water allocation rules for the Gezira Scheme, an irrigation system located between the Blue and White Niles south of Khartoum. In 1925, Gezira started with 300,000 acres; currently it covers close to two million acres.

A case study of supply chain simulation for determining the best stock allocation

OpenAIRE

Puryani; Astanti Yuli Dwi; Fitriani Gity Nur

2018-01-01

You Dare is a Small and Medium Enterprise (SME) engaged in fashion, namely the sale of shoes. The problems that occurred in Dare are their limit on the amount of the shoes supply from suppliers and the inventory allocation policies are unplanned, so the profit is not maximized. This study simulates inventory allocation policy that Dare applies to see the impact on profits of Dare then proceed with the design of new system scenarios. The new scenario aims to implement policies more appropriate...

A Mixed Integer Efficient Global Optimization Framework: Applied to the Simultaneous Aircraft Design, Airline Allocation and Revenue Management Problem

Science.gov (United States)

Roy, Satadru

problem consisting of 94 decision variables including 33 integer and 61 continuous type variables. This application problem is a representation of an interacting group of systems and provides key challenges to the optimization framework to solve the MINLP problem, as reflected by the presence of a moderate number of integer and continuous type design variables and expensive analysis tool. The result indicates simultaneously solving the subspaces could lead to significant improvement in the fleet-level objective of the airline when compared to the previously developed sequential subspace decomposition approach. In developing the approach to solve the MINLP/MDNLP challenge problem, several test problems provided the ability to explore performance of the framework. While solving these test problems, the framework showed that it could solve other MDNLP problems including categorically discrete variables, indicating that the framework could have broader application than the new aircraft design-fleet allocation-revenue management problem.

Tendances Carbone no. 79 'Free allocations under Phase 3 benchmarks: early evidence of what has changed'

International Nuclear Information System (INIS)

Sartor, Oliver

2013-01-01

Among the publications of CDC Climat Research, 'Tendances Carbone' bulletin specifically studies the developments of the European market for CO 2 allowances. This issue addresses the following points: One of the most controversial changes to the EU ETS in Phase 3 (2013-2020) has been the introduction of emissions-performance benchmarks for determining free allocations to non-electricity producers. Phases 1 and 2 used National Allocation Plans (NAPs). For practical reasons NAPs were drawn up by each Member State, but this led to problems, including over-generous allowance allocation, insufficiently harmonised allocations across countries and distorted incentives to reduce emissions. Benchmarking tries to fix things by allocating the equivalent of 100% of allowances needed if every installation used the best available technology. But this is not universally popular and industries say that they might lose international competitiveness. So a new study by CDC Climat and the Climate Economics Chair examined the data from the preliminary Phase 3 free allocations of 20 EU Member States and asked: how much are free allocations actually going to change with benchmarking?

Bayesian Modelling, Monte Carlo Sampling and Capital Allocation of Insurance Risks

Directory of Open Access Journals (Sweden)

Gareth W. Peters

2017-09-01

Full Text Available The main objective of this work is to develop a detailed step-by-step guide to the development and application of a new class of efficient Monte Carlo methods to solve practically important problems faced by insurers under the new solvency regulations. In particular, a novel Monte Carlo method to calculate capital allocations for a general insurance company is developed, with a focus on coherent capital allocation that is compliant with the Swiss Solvency Test. The data used is based on the balance sheet of a representative stylized company. For each line of business in that company, allocations are calculated for the one-year risk with dependencies based on correlations given by the Swiss Solvency Test. Two different approaches for dealing with parameter uncertainty are discussed and simulation algorithms based on (pseudo-marginal Sequential Monte Carlo algorithms are described and their efficiency is analysed.

Allocating service parts in two-echelon networks at a utility company

NARCIS (Netherlands)

van den Berg, D.; van der Heijden, Matthijs C.; Schuur, Peter

2014-01-01

We study a multi-item, two-echelon, continuous-review inventory problem at a Dutch utility company, Liander. We develop a model that optimizes the quantities of service parts and their allocation in the two-echelon network under an aggregate waiting time restriction. Specific aspects that we address

Time allocation between feeding and incubation in uniparental arctic-breeding shorebirds: energy reserves provide leeway in a tight schedule

NARCIS (Netherlands)

Tulp, I.Y.M.; Schekkerman, H.

2006-01-01

Birds with uniparental incubation may face a time allocation problem between incubation and feeding. Eggs need regular warming to hatch successfully, but the parent must leave the nest to feed and safeguard its own survival. Time allocation during incubation is likely to depend on factors

Addressing congestion on single allocation hub-and-spoke networks

Directory of Open Access Journals (Sweden)

Ricardo Saraiva de Camargo

2012-12-01

Full Text Available When considering hub-and-spoke networks with single allocation, the absence of alternative routes makes this kind of systems specially vulnerable to congestion effects. In order to improve the design of such networks, congestion costs must be addressed. This article deploys two different techniques for addressing congestion on single allocation hub-and-spoke networks: the Generalized Benders Decomposition and the Outer Approximation method. Both methods are able to solve large scale instances. Computational experiments show how the adoption of advanced solution strategies, such as Pareto-optimal cut generation on the Master Problem branch-and-bound tree, may be decisive. They also demonstrate that the solution effort is not only associated with the size of the instances, but also with their combination of the installation and congestion costs.

Location-Based Resource Allocation for OFDMA Cognitive Radio Systems

KAUST Repository

Ghorbel, Mahdi

2011-05-01

Cognitive radio is one of the hot topics for emerging and future wireless communication. It has been proposed as a suitable solution for the spectrum scarcity caused by the increase in frequency demand. The concept is based on allowing unlicensed users, called cognitive or secondary users, to share the unoccupied frequency bands with their owners, called the primary users, under constraints on the interference they cause to them. In order to estimate this interference, the cognitive system usually uses the channel state information to the primary user, which is often impractical to obtain. However, we propose to use location information, which is easier to obtain, to estimate this interference. The purpose of this work is to propose a subchannel and power allocation method which maximizes the secondary users\\' total capacity under the constraints of limited budget power and total interference to the primary under certain threshold. We model the problem as a constrained optimization problem for both downlink and uplink cases. Then, we propose low-complexity resource allocation schemes based on the waterfilling algorithm. The simulation results show the efficiency of the proposed method with comparison to the exhaustive search algorithm.

Offspring Size and Reproductive Allocation in Harvester Ants.

Science.gov (United States)

Wiernasz, Diane C; Cole, Blaine J

2018-01-01

A fundamental decision that an organism must make is how to allocate resources to offspring, with respect to both size and number. The two major theoretical approaches to this problem, optimal offspring size and optimistic brood size models, make different predictions that may be reconciled by including how offspring fitness is related to size. We extended the reasoning of Trivers and Willard (1973) to derive a general model of how parents should allocate additional resources with respect to the number of males and females produced, and among individuals of each sex, based on the fitness payoffs of each. We then predicted how harvester ant colonies should invest additional resources and tested three hypotheses derived from our model, using data from 3 years of food supplementation bracketed by 6 years without food addition. All major results were predicted by our model: food supplementation increased the number of reproductives produced. Male, but not female, size increased with food addition; the greatest increases in male size occurred in colonies that made small females. We discuss how use of a fitness landscape improves quantitative predictions about allocation decisions. When parents can invest differentially in offspring of different types, the best strategy will depend on parental state as well as the effect of investment on offspring fitness.

Modeling and simulation of dynamic ant colony's labor division for task allocation of UAV swarm

Science.gov (United States)

Wu, Husheng; Li, Hao; Xiao, Renbin; Liu, Jie

2018-02-01

The problem of unmanned aerial vehicle (UAV) task allocation not only has the intrinsic attribute of complexity, such as highly nonlinear, dynamic, highly adversarial and multi-modal, but also has a better practicability in various multi-agent systems, which makes it more and more attractive recently. In this paper, based on the classic fixed response threshold model (FRTM), under the idea of "problem centered + evolutionary solution" and by a bottom-up way, the new dynamic environmental stimulus, response threshold and transition probability are designed, and a dynamic ant colony's labor division (DACLD) model is proposed. DACLD allows a swarm of agents with a relatively low-level of intelligence to perform complex tasks, and has the characteristic of distributed framework, multi-tasks with execution order, multi-state, adaptive response threshold and multi-individual response. With the proposed model, numerical simulations are performed to illustrate the effectiveness of the distributed task allocation scheme in two situations of UAV swarm combat (dynamic task allocation with a certain number of enemy targets and task re-allocation due to unexpected threats). Results show that our model can get both the heterogeneous UAVs' real-time positions and states at the same time, and has high degree of self-organization, flexibility and real-time response to dynamic environments.

Allocation of Energy Consumption among Provinces in China: A Weighted ZSG-DEA Model

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Siqin Xiong

2017-11-01

Full Text Available To realize the sustainable development of energy, the Chinese government has formulated a series of national goals of total energy control and energy structure optimization. Under the national constraints, how to efficiently allocate the constrained total amount of energy consumption to each province is a fundamental problem to be solved. Based on a data envelopment analysis (DEA model and a zero-sum game theory (ZSG, this paper constructs a weighted zero-sum game data envelopment analysis (ZSG-DEA model to allocate the energy consumption quota. Additionally, this paper compares the results with the current administrative targets, to examine the efficiency and feasibility of each allocation mechanism. Finally, this paper employs the proposed model to determine the optimal energy structure for each province in China. The results indicate that by 2020, the national goal of energy structure adjustment will be realized, and energy structure will be diversified in most regions, whereas the coal-dominated status in primary energy consumption will not change. Additionally, the weighted ZSG-DEA model focuses on allocation efficiency while the government considers more regional economic disparity. Therefore, this study suggests a mixture of the two allocation mechanisms in accordance with specific conditions.

Peer-Allocated Instant Response (PAIR): Computional allocation of peer tutors in learning communities

NARCIS (Netherlands)

Westera, Wim

2009-01-01

Westera, W. (2007). Peer-Allocated Instant Response (PAIR): Computational allocation of peer tutors in learning communities. Journal of Artificial Societies and Social Simulation, http://jasss.soc.surrey.ac.uk/10/2/5.html

Energy Efficient Resource Allocation for Cognitive Radios: A Generalized Sensing Analysis

KAUST Repository

Alabbasi, AbdulRahman; Rezki, Zouheir; Shihada, Basem

2014-01-01

In this paper, two resource allocation schemes for energy efficient cognitive radio systems are proposed. Our design considers resource allocation approaches that adopt spectrum sharing combined with soft-sensing information, adaptive sensing thresholds, and adaptive power to achieve an energy efficient system. An energy per good-bit metric is considered as an energy efficient objective function. A multi-carrier system, such as, orthogonal frequency division multiplexing, is considered in the framework. The proposed resource allocation schemes, using different approaches, are designated as sub-optimal and optimal. The sub-optimal approach is attained by optimizing over a channel inversion power policy. The optimal approach utilizes the calculus of variation theory to optimize a problem of instantaneous objective function subject to average and instantaneous constraints with respect to functional optimization variables. In addition to the analytical results, selected numerical results are provided to quantify the impact of soft-sensing information and the optimal adaptive sensing threshold on the system performance.

Energy Efficient Resource Allocation for Cognitive Radios: A Generalized Sensing Analysis

KAUST Repository

Alabbasi, Abdulrahman

2014-12-31

In this paper, two resource allocation schemes for energy efficient cognitive radio systems are proposed. Our design considers resource allocation approaches that adopt spectrum sharing combined with soft-sensing information, adaptive sensing thresholds, and adaptive power to achieve an energy efficient system. An energy per good-bit metric is considered as an energy efficient objective function. A multi-carrier system, such as, orthogonal frequency division multiplexing, is considered in the framework. The proposed resource allocation schemes, using different approaches, are designated as sub-optimal and optimal. The sub-optimal approach is attained by optimizing over a channel inversion power policy. The optimal approach utilizes the calculus of variation theory to optimize a problem of instantaneous objective function subject to average and instantaneous constraints with respect to functional optimization variables. In addition to the analytical results, selected numerical results are provided to quantify the impact of soft-sensing information and the optimal adaptive sensing threshold on the system performance.

How much water flows? Examining water allocations using a mobile decision lab

Science.gov (United States)

Strickert, G. E.; Gober, P.; Bradford, L. E.; Phillips, P.; Ross, J.

2016-12-01

Management of freshwater resources is a complex and multifaceted issues. Big challenges like scarcity, conflicts over water use and access, and ecosystem degradation are widespread around the world. These issues reflects ineffective past practices and signals the need for a fundamental change. Previous actions to mitigate these problems have been incremental rather than innovative, in part because of inherent conservatism in the water management community and an inability to experiment with water allocations in a safe environment. The influence of transboundary water policies was tested using a mobile decision lab which examined three theory areas: limited territorial sovereignty, absolute territorial sovereignty, and shared risk. The experiment allowed people engaged in the water sector to allocate incoming flows to different sectors: agriculture, municipal, industrial and environmental flows in two flow scenarios; slight shortage and extreme water shortage, and to pass on the remaining water to downstream regions. Mandatory sharing 50% of the natural flows between provinces (i.e. limited territorial sovereignty) achieved the most equitable allocation based on water units and points across the three regions. When there were no allocation rules (i.e. absolute territorial sovereignty) the downstream region received significantly less water (e.g. 8-11%. p affect on the amount of water flowing through the region. It is also notable that most participants sought a trade-off of water allocations, minimizing the allocations to agriculture and industry and prioritizing the municipal sector particularity under the severe drought scenario.

A note on resource allocation scheduling with group technology and learning effects on a single machine

Science.gov (United States)

Lu, Yuan-Yuan; Wang, Ji-Bo; Ji, Ping; He, Hongyu

2017-09-01

In this article, single-machine group scheduling with learning effects and convex resource allocation is studied. The goal is to find the optimal job schedule, the optimal group schedule, and resource allocations of jobs and groups. For the problem of minimizing the makespan subject to limited resource availability, it is proved that the problem can be solved in polynomial time under the condition that the setup times of groups are independent. For the general setup times of groups, a heuristic algorithm and a branch-and-bound algorithm are proposed, respectively. Computational experiments show that the performance of the heuristic algorithm is fairly accurate in obtaining near-optimal solutions.

Statistical mechanics of competitive resource allocation using agent-based models

Science.gov (United States)

Chakraborti, Anirban; Challet, Damien; Chatterjee, Arnab; Marsili, Matteo; Zhang, Yi-Cheng; Chakrabarti, Bikas K.

2015-01-01

Demand outstrips available resources in most situations, which gives rise to competition, interaction and learning. In this article, we review a broad spectrum of multi-agent models of competition (El Farol Bar problem, Minority Game, Kolkata Paise Restaurant problem, Stable marriage problem, Parking space problem and others) and the methods used to understand them analytically. We emphasize the power of concepts and tools from statistical mechanics to understand and explain fully collective phenomena such as phase transitions and long memory, and the mapping between agent heterogeneity and physical disorder. As these methods can be applied to any large-scale model of competitive resource allocation made up of heterogeneous adaptive agent with non-linear interaction, they provide a prospective unifying paradigm for many scientific disciplines.

A linear bi-level multi-objective program for optimal allocation of water resources.

Directory of Open Access Journals (Sweden)

Ijaz Ahmad

Full Text Available This paper presents a simple bi-level multi-objective linear program (BLMOLP with a hierarchical structure consisting of reservoir managers and several water use sectors under a multi-objective framework for the optimal allocation of limited water resources. Being the upper level decision makers (i.e., leader in the hierarchy, the reservoir managers control the water allocation system and tend to create a balance among the competing water users thereby maximizing the total benefits to the society. On the other hand, the competing water use sectors, being the lower level decision makers (i.e., followers in the hierarchy, aim only to maximize individual sectoral benefits. This multi-objective bi-level optimization problem can be solved using the simultaneous compromise constraint (SICCON technique which creates a compromise between upper and lower level decision makers (DMs, and transforms the multi-objective function into a single decision-making problem. The bi-level model developed in this study has been applied to the Swat River basin in Pakistan for the optimal allocation of water resources among competing water demand sectors and different scenarios have been developed. The application of the model in this study shows that the SICCON is a simple, applicable and feasible approach to solve the BLMOLP problem. Finally, the comparisons of the model results show that the optimization model is practical and efficient when it is applied to different conditions with priorities assigned to various water users.

Development of a new loss allocation method for a hybrid electricity market using graph theory

International Nuclear Information System (INIS)

Lim, Valerie S.C.; McDonald, John D.F.; Saha, Tapan K.

2009-01-01

This paper introduces a new method for allocating losses in a power system using a loop-based representation of system behaviour. Using the new method, network behaviour is formulated as a series of presumed power transfers directly between market participants. In contrast to many existing loss allocation methods, this makes it easier to justify the resulting loss distribution. In addition to circumventing the problems of non-unique loss allocations, a formalised process of loop identification, using graph theory concepts, is introduced. The proposed method is applied to both the IEEE 14-bus system and a modified CIGRE Nordic 32-bus system. The results provide a demonstration of the capability of the proposed method to allocate losses in the hybrid market, and demonstrate the approach's capacity to link the technical performance of the network to market instruments. (author)

Cost allocation review : staff discussion paper

International Nuclear Information System (INIS)

2005-09-01

This report addressed the need for updated cost allocation studies filed by local electricity distribution companies because they ensure that distribution rates for each customer class remain just and reasonable. According to the 2001 Electricity Distribution Rate Handbook, the Ontario Energy Board requires new cost allocation studies before implementing any future incentive regulation plans. A review of cost allocations allows the Board to consider the need for adjustments to the current share of distribution costs paid by different classes of ratepayers. This report included 14 sections to facilitate consultations with stakeholders on financial information requirements for cost allocation; directly assignable costs; functionalization; categorization; allocation methods; allocation of other costs; load data requirements; cost allocation implementation issues; addition of new rate class and rate design for scattered unmetered loads; addition of new rate class for larger users; rates to charge embedded distributors; treatment of the rate sub-classification identified as time-of-use; and, rate design implementation issues. 1 fig., 7 appendices

Research on multirobot pursuit task allocation algorithm based on emotional cooperation factor.

Science.gov (United States)

Fang, Baofu; Chen, Lu; Wang, Hao; Dai, Shuanglu; Zhong, Qiubo

2014-01-01

Multirobot task allocation is a hot issue in the field of robot research. A new emotional model is used with the self-interested robot, which gives a new way to measure self-interested robots' individual cooperative willingness in the problem of multirobot task allocation. Emotional cooperation factor is introduced into self-interested robot; it is updated based on emotional attenuation and external stimuli. Then a multirobot pursuit task allocation algorithm is proposed, which is based on emotional cooperation factor. Combined with the two-step auction algorithm recruiting team leaders and team collaborators, set up pursuit teams, and finally use certain strategies to complete the pursuit task. In order to verify the effectiveness of this algorithm, some comparing experiments have been done with the instantaneous greedy optimal auction algorithm; the results of experiments show that the total pursuit time and total team revenue can be optimized by using this algorithm.

Resource Allocation for Multicell Device-to-Device Communications in Cellular Network: A Game Theoretic Approach

Directory of Open Access Journals (Sweden)

Jun Huang

2015-08-01

Full Text Available Device-to-Device (D2D communication has recently emerged as a promising technology to improve the capacity and coverage of cellular systems. To successfully implement D2D communications underlaying a cellular network, resource allocation for D2D links plays a critical role. While most of prior resource allocation mechanisms for D2D communications have focused on interference within a single-cell system, this paper investigates the resource allocation problem for a multicell cellular network in which a D2D link reuses available spectrum resources of multiple cells. A repeated game theoretic approach is proposed to address the problem. In this game, the base stations (BSs act as players that compete for resource supply of D2D, and the utility of each player is formulated as revenue collected from both cellular and D2D users using resources. Extensive simulations are conducted to verify the proposed approach and the results show that it can considerably enhance the system performance in terms of sum rate and sum rate gain.

Tradable permit allocations and sequential choice

Energy Technology Data Exchange (ETDEWEB)

MacKenzie, Ian A. [Centre for Economic Research, ETH Zuerich, Zurichbergstrasse 18, 8092 Zuerich (Switzerland)

2011-01-15

This paper investigates initial allocation choices in an international tradable pollution permit market. For two sovereign governments, we compare allocation choices that are either simultaneously or sequentially announced. We show sequential allocation announcements result in higher (lower) aggregate emissions when announcements are strategic substitutes (complements). Whether allocation announcements are strategic substitutes or complements depends on the relationship between the follower's damage function and governments' abatement costs. When the marginal damage function is relatively steep (flat), allocation announcements are strategic substitutes (complements). For quadratic abatement costs and damages, sequential announcements provide a higher level of aggregate emissions. (author)

Bandwidth and power allocation for two-way relaying in overlay cognitive radio systems

KAUST Repository

Alsharoa, Ahmad M.; Ghazzai, Hakim; Yaacoub, Elias E.; Alouini, Mohamed-Slim

2014-01-01

In this paper, the problem of both bandwidth and power allocation for two-way multiple relay systems in overlay cognitive radio (CR) setup is investigated. In the CR overlay mode, primary users (PUs) cooperate with cognitive users (CUs) for mutual

Adaptive Cross-Layer Distributed Energy-Efficient Resource Allocation Algorithms for Wireless Data Networks

Directory of Open Access Journals (Sweden)

Daniela Saturnino

2008-10-01

Full Text Available The issue of adaptive and distributed cross-layer resource allocation for energy efficiency in uplink code-division multiple-access (CDMA wireless data networks is addressed. The resource allocation problems are formulated as noncooperative games wherein each terminal seeks to maximize its own energy efficiency, namely, the number of reliably transmitted information symbols per unit of energy used for transmission. The focus of this paper is on the issue of adaptive and distributed implementation of policies arising from this approach, that is, it is assumed that only readily available measurements, such as the received data, are available at the receiver in order to play the considered games. Both single-cell and multicell networks are considered. Stochastic implementations of noncooperative games for power allocation, spreading code allocation, and choice of the uplink (linear receiver are thus proposed, and analytical results describing the convergence properties of selected stochastic algorithms are also given. Extensive simulation results show that, in many instances of practical interest, the proposed stochastic algorithms approach with satisfactory accuracy the performance of nonadaptive games, whose implementation requires much more prior information.

Power allocation strategies to minimize energy consumption in wireless body area networks.

Science.gov (United States)

Kailas, Aravind

2011-01-01

The wide scale deployment of wireless body area networks (WBANs) hinges on designing energy efficient communication protocols to support the reliable communication as well as to prolong the network lifetime. Cooperative communications, a relatively new idea in wireless communications, offers the benefits of multi-antenna systems, thereby improving the link reliability and boosting energy efficiency. In this short paper, the advantages of resorting to cooperative communications for WBANs in terms of minimized energy consumption are investigated. Adopting an energy model that encompasses energy consumptions in the transmitter and receiver circuits, and transmitting energy per bit, it is seen that cooperative transmission can improve energy efficiency of the wireless network. In particular, the problem of optimal power allocation is studied with the constraint of targeted outage probability. Two strategies of power allocation are considered: power allocation with and without posture state information. Using analysis and simulation-based results, two key points are demonstrated: (i) allocating power to the on-body sensors making use of the posture information can reduce the total energy consumption of the WBAN; and (ii) when the channel condition is good, it is better to recruit less relays for cooperation to enhance energy efficiency.

A decentralized multidistrict optimization framework for system-wide pavement maintenance resource allocation

Directory of Open Access Journals (Sweden)

J. Farhan

2016-05-01

Full Text Available Historically, pavement maintenance funds have been allocated based on a centralized programme development process. Such practice, though seemingly convenient, does not lead to optimal allocation of funds since districts generally have different priorities based on the state of development and condition of their respective road networks. This paper proposes a decentralized two-phased optimization framework for pavement maintenance fund allocation considering multiple objectives and cross-district trade-off at the network level. In the proposed two-phased analysis approach, Phase-I focuses on establishing the needs and funds requirements of individual districts given multiple performance targets or objectives, while a system-wide fund appropriation strategy is selected, in Phase-II, given budget and equity constraints across competing districts. The proposed approach is illustrated using a numerical example problem for appropriating funds to three districts. The results indicated that the proposed approach is not only able to evaluate the extent to which various performance targets are achieved at the central and district level, but also maintains equity in distribution of financial resources across districts. Keywords: Pavement maintenance programming, Multiobjective, Multidistrict, Optimized resource allocation, Genetic algorithm, Dynamic programming

Directed graph based carbon flow tracing for demand side carbon obligation allocation

DEFF Research Database (Denmark)

Sun, Tao; Feng, Donghan; Ding, Teng

2016-01-01

In order to achieve carbon emission abatement, some researchers and policy makers have cast their focus on demand side carbon abatement potentials. This paper addresses the problem of carbon flow calculation in power systems and carbon obligation allocation at demand side. A directed graph based...... method for tracing carbon flow is proposed. In a lossy network, matrices such as carbon losses, net carbon intensity (NCI) and footprint carbon intensity (FCI) are obtained with the proposed method and used to allocate carbon obligation at demand side. Case studies based on realistic distribution...... and transmission systems are provided to demonstrate the effectiveness of the proposed method....

Three Years of Experience of Wet Gas Allocation on Canyon Express

Energy Technology Data Exchange (ETDEWEB)

Singh, Aditya; Hall, James; Letton, Winsor

2005-07-01

In September 2002, production was begun from the three fields that together form the Canyon Express System- King's Peak, Aconcagua, and Camden Hills. The 9 wells from these fields are connected to a pair of 12-inch flow lines carrying the commingled wet gas a distance of approximately 92 kilometers back to the Canyon Station platform for processing. At the 21st NSFMW in October 2003, an initial report was given on the status of Wet Gas Allocation for the Canyon Express project. As discussed in that paper, dual-differential, subsea wet gas meters were chosen for the task of allocating gas and liquids back to individual wells. However, since the gas from all three fields was very dry (Lockhart-Martinelli parameter less than 0.01) and because the operating pressures were quite high (250 bar), application of the dual-differential function of the meters yielded errors in both liquid and gas flow rates. Furthermore, as these problems were being uncovered, scale was beginning to collect inside some of the meters. Taken together, these problems produced system imbalances as great as 20%. To address the problems, one of the individual flow metering elements within each wet gas meter was chosen as the allocation meter, operating as a single-phase gas meter. After three years of operation of the Canyon Express Project, considerable experience has been accumulated. Since at the time it held the record for deep water hydrocarbon production, application of the technologies discussed here were challenging and required considerable flexibility. It is believed that the Canyon Express experiences will benefit future deep water flow metering projects. The knowledge acquired thus far is surveyed and summarized. The emphasis is on the technical aspects. (tk)

Multimedia transmission in MC-CDMA using adaptive subcarrier power allocation and CFO compensation

Science.gov (United States)

Chitra, S.; Kumaratharan, N.

2018-02-01

Multicarrier code division multiple access (MC-CDMA) system is one of the most effective techniques in fourth-generation (4G) wireless technology, due to its high data rate, high spectral efficiency and resistance to multipath fading. However, MC-CDMA systems are greatly deteriorated by carrier frequency offset (CFO) which is due to Doppler shift and oscillator instabilities. It leads to loss of orthogonality among the subcarriers and causes intercarrier interference (ICI). Water filling algorithm (WFA) is an efficient resource allocation algorithm to solve the power utilisation problems among the subcarriers in time-dispersive channels. The conventional WFA fails to consider the effect of CFO. To perform subcarrier power allocation with reduced CFO and to improve the capacity of MC-CDMA system, residual CFO compensated adaptive subcarrier power allocation algorithm is proposed in this paper. The proposed technique allocates power only to subcarriers with high channel to noise power ratio. The performance of the proposed method is evaluated using random binary data and image as source inputs. Simulation results depict that the bit error rate performance and ICI reduction capability of the proposed modified WFA offered superior performance in both power allocation and image compression for high-quality multimedia transmission in the presence of CFO and imperfect channel state information conditions.

Management of electricity network cross border capacity: allocation procedures between France and Belgium

International Nuclear Information System (INIS)

Raytchev, D.

2003-01-01

This paper tries to identify a method of allocation of the Interconnector capacity for the transport of electricity which complies best with the (conflicting) interests of users, system operators and regulators in the context of a common European market of electricity. The first part combines a historical approach with a comparative study of existing allocation procedures to show that the new joint mechanism of auctioning and market splitting, applied to the whole northern zone of UCTE is vastly superior to the existing allocation arrangement on the Franco-Belgian border. The second part discusses some problems related to the implementation of the new allocation mechanism. Here we examine some difficulties concerning ca achy auctioning (like auction methods and organisation, profit distribution and derivative markets) as well as the market splitting method (neutrality, markets without power exchanges, etc). The main obstacle facing the new method remains however the lack of willingness to address the urgent issue of reforming the present allocation procedures- a remnant from the period of centrally planned electricity systems where neighbouring monopoly companies negotiated agreements of mutual assistance. These agreements are currently kept in place by tacit inaction despite their heterogeneity and arbitrariness which slow down the emergence of a real competition capable of contesting the positions of historic operators. (authors)

Performance Analysis and Optimal Allocation of Layered Defense M/M/N Queueing Systems

Directory of Open Access Journals (Sweden)

Longyue Li

2016-01-01

Full Text Available One important mission of strategic defense is to develop an integrated layered Ballistic Missile Defense System (BMDS. Motivated by the queueing theory, we presented a work for the representation, modeling, performance simulation, and channels optimal allocation of the layered BMDS M/M/N queueing systems. Firstly, in order to simulate the process of defense and to study the Defense Effectiveness (DE, we modeled and simulated the M/M/N queueing system of layered BMDS. Specifically, we proposed the M/M/N/N and M/M/N/C queueing model for short defense depth and long defense depth, respectively; single target channel and multiple target channels were distinguished in each model. Secondly, we considered the problem of assigning limited target channels to incoming targets, we illustrated how to allocate channels for achieving the best DE, and we also proposed a novel and robust search algorithm for obtaining the minimum channel requirements across a set of neighborhoods. Simultaneously, we presented examples of optimal allocation problems under different constraints. Thirdly, several simulation examples verified the effectiveness of the proposed queueing models. This work may help to understand the rules of queueing process and to provide optimal configuration suggestions for defense decision-making.

A new proposal for greenhouse gas emissions responsibility allocation: best available technologies approach.

Science.gov (United States)

Berzosa, Álvaro; Barandica, Jesús M; Fernández-Sánchez, Gonzalo

2014-01-01

In recent years, several methodologies have been developed for the quantification of greenhouse gas (GHG) emissions. However, determining who is responsible for these emissions is also quite challenging. The most common approach is to assign emissions to the producer (based on the Kyoto Protocol), but proposals also exist for its allocation to the consumer (based on an ecological footprint perspective) and for a hybrid approach called shared responsibility. In this study, the existing proposals and standards regarding the allocation of GHG emissions responsibilities are analyzed, focusing on their main advantages and problems. A new model of shared responsibility that overcomes some of the existing problems is also proposed. This model is based on applying the best available technologies (BATs). This new approach allocates the responsibility between the producers and the final consumers based on the real capacity of each agent to reduce emissions. The proposed approach is demonstrated using a simple case study of a 4-step life cycle of ammonia nitrate (AN) fertilizer production. The proposed model has the characteristics that the standards and publications for assignment of GHG emissions responsibilities demand. This study presents a new way to assign responsibilities that pushes all the actors in the production chain, including consumers, to reduce pollution. © 2013 SETAC.

Energy Efficient Power Allocation in Multi-tier 5G Networks Using Enhanced Online Learning

KAUST Repository

Alqerm, Ismail; Shihada, Basem

2017-01-01

of the 5G systems, where each transmitter surmises other transmitters power allocation strategies without information exchange. The proposed learning model exploits a brief state representation to account for the problem of dimensionality in online learning

Modeling a four-layer location-routing problem

Directory of Open Access Journals (Sweden)

Mohsen Hamidi

2012-01-01

Full Text Available Distribution is an indispensable component of logistics and supply chain management. Location-Routing Problem (LRP is an NP-hard problem that simultaneously takes into consideration location, allocation, and vehicle routing decisions to design an optimal distribution network. Multi-layer and multi-product LRP is even more complex as it deals with the decisions at multiple layers of a distribution network where multiple products are transported within and between layers of the network. This paper focuses on modeling a complicated four-layer and multi-product LRP which has not been tackled yet. The distribution network consists of plants, central depots, regional depots, and customers. In this study, the structure, assumptions, and limitations of the distribution network are defined and the mathematical optimization programming model that can be used to obtain the optimal solution is developed. Presented by a mixed-integer programming model, the LRP considers the location problem at two layers, the allocation problem at three layers, the vehicle routing problem at three layers, and a transshipment problem. The mathematical model locates central and regional depots, allocates customers to plants, central depots, and regional depots, constructs tours from each plant or open depot to customers, and constructs transshipment paths from plants to depots and from depots to other depots. Considering realistic assumptions and limitations such as producing multiple products, limited production capacity, limited depot and vehicle capacity, and limited traveling distances enables the user to capture the real world situations.

Discovering Bayesian Market Views for Intelligent Asset Allocation

OpenAIRE

Xing, Frank Z.; Cambria, Erik; Malandri, Lorenzo; Vercellis, Carlo

2018-01-01

Along with the advance of opinion mining techniques, public mood has been found to be a key element for stock market prediction. However, in what manner the market participants are affected by public mood has been rarely discussed. As a result, there has been little progress in leveraging public mood for the asset allocation problem, as the application is preferred in a trusted and interpretable way. In order to address the issue of incorporating public mood analyzed from social media, we pro...

IPO Allocations: Discriminatory or Discretionary?

OpenAIRE

William Wilhelm; Alexander Ljungqvist

2001-01-01

We estimate the structural links between IPO allocations, pre-market information production, and initial underpricing returns, within the context of theories of bookbuilding. Using a sample of both US and international IPOs we find evidence of the following: ? IPO allocation policies favour institutional investors, both in the US and worldwide. ? Increasing institutional allocations results in offer prices that deviate more from the indicative price range established prior to bankers’ efforts...

Effect of optimum stratification on sampling with varying probabilities under proportional allocation

OpenAIRE

Syed Ejaz Husain Rizvi; Jaj P. Gupta; Manoj Bhargava

2007-01-01

The problem of optimum stratification on an auxiliary variable when the units from different strata are selected with probability proportional to the value of auxiliary variable (PPSWR) was considered by Singh (1975) for univariate case. In this paper we have extended the same problem, for proportional allocation, when two variates are under study. A cum. 3 R3(x) rule for obtaining approximately optimum strata boundaries has been provided. It has been shown theoretically as well as empiricall...

Optimal Allocation of Renewable Energy Sources for Energy Loss Minimization

Directory of Open Access Journals (Sweden)

Vaiju Kalkhambkar

2017-03-01

Full Text Available Optimal allocation of renewable distributed generation (RDG, i.e., solar and the wind in a distribution system becomes challenging due to intermittent generation and uncertainty of loads. This paper proposes an optimal allocation methodology for single and hybrid RDGs for energy loss minimization. The deterministic generation-load model integrated with optimal power flow provides optimal solutions for single and hybrid RDG. Considering the complexity of the proposed nonlinear, constrained optimization problem, it is solved by a robust and high performance meta-heuristic, Symbiotic Organisms Search (SOS algorithm. Results obtained from SOS algorithm offer optimal solutions than Genetic Algorithm (GA, Particle Swarm Optimization (PSO and Firefly Algorithm (FFA. Economic analysis is carried out to quantify the economic benefits of energy loss minimization over the life span of RDGs.

Location of Urban Logistic Terminals as Hub Location Problem

Directory of Open Access Journals (Sweden)

Jasmina Pašagić Škrinjar

2012-09-01

Full Text Available In this paper the problems of locating urban logistic terminals are studied as hub location problems that due to a large number of potential nodes in big cities belong to hard non-polynomial problems, the so-called NP-problems. The hub location problems have found wide application in physical planning of transport and telecommunication systems, especially systems of fast delivery, networks of logistic and distribution centres and cargo traffic terminals of the big cities, etc. The paper defines single and multiple allocations and studies the numerical examples. The capacitated single allocation hub location problems have been studied, with the provision of a mathematical model of selecting the location for the hubs on the network. The paper also presents the differences in the possibilities of implementing the exact and heuristic methods to solve the actual location problems of big dimensions i.e. hub problems of the big cities.

A generalized fuzzy credibility-constrained linear fractional programming approach for optimal irrigation water allocation under uncertainty

Science.gov (United States)

Zhang, Chenglong; Guo, Ping

2017-10-01

The vague and fuzzy parametric information is a challenging issue in irrigation water management problems. In response to this problem, a generalized fuzzy credibility-constrained linear fractional programming (GFCCFP) model is developed for optimal irrigation water allocation under uncertainty. The model can be derived from integrating generalized fuzzy credibility-constrained programming (GFCCP) into a linear fractional programming (LFP) optimization framework. Therefore, it can solve ratio optimization problems associated with fuzzy parameters, and examine the variation of results under different credibility levels and weight coefficients of possibility and necessary. It has advantages in: (1) balancing the economic and resources objectives directly; (2) analyzing system efficiency; (3) generating more flexible decision solutions by giving different credibility levels and weight coefficients of possibility and (4) supporting in-depth analysis of the interrelationships among system efficiency, credibility level and weight coefficient. The model is applied to a case study of irrigation water allocation in the middle reaches of Heihe River Basin, northwest China. Therefore, optimal irrigation water allocation solutions from the GFCCFP model can be obtained. Moreover, factorial analysis on the two parameters (i.e. λ and γ) indicates that the weight coefficient is a main factor compared with credibility level for system efficiency. These results can be effective for support reasonable irrigation water resources management and agricultural production.

Intelligent tactical asset allocation support system

NARCIS (Netherlands)

Hiemstra, Y.

1995-01-01

This paper presents an advanced support system for Tactical Asset Allocation. Asset allocation explains over 90% of portfolio performance (Brinson, Hood and Beebower, 1988). Tactical asset allocation adjusts a strategic portfolio on the basis of short term market outlooks. The system includes

How should INGOs allocate resources?

Directory of Open Access Journals (Sweden)

Scott Wisor

2012-02-01

Full Text Available International Non-governmental Organizations (INGOs face difficult choices when choosing to allocate resources. Given that the resources made available to INGOs fall far short of what is needed to reduce massive human rights deficits, any chosen scheme of resource allocation requires failing to reach other individuals in great need. Facing these moral opportunity costs, what moral reasons should guide INGO resource allocation? Two reasons that clearly matter, and are recognized by philosophers and development practitioners, are the consequences (or benefit or harm reduction of any given resource allocation and the need (or priority of individual beneficiaries. If accepted, these reasons should lead INGOs to allocate resources to a limited number of countries where the most prioritarian weighted harm reduction will be achieved. I make three critiques against this view. First, on grounds the consequentialist accepts, I argue that INGOs ought to maintain a reasonably wide distribution of resources. Second, I argue that even if one is a consequentialist, consequentialism ought not act as an action guiding principle for INGOs. Third, I argue that additional moral reasons should influence decision making about INGO resource allocation. Namely, INGO decision making should attend to relational reasons, desert, respect for agency, concern for equity, and the importance of expressing a view of moral wrongs.

Vehicle Sliding Mode Control with Adaptive Upper Bounds: Static versus Dynamic Allocation to Saturated Tire Forces

Directory of Open Access Journals (Sweden)

Ali Tavasoli

2012-01-01

Full Text Available Nonlinear vehicle control allocation is achieved through distributing the task of vehicle control among individual tire forces, which are constrained to nonlinear saturation conditions. A high-level sliding mode control with adaptive upper bounds is considered to assess the body yaw moment and lateral force for the vehicle motion. The proposed controller only requires the online adaptation of control gains without acquiring the knowledge of upper bounds on system uncertainties. Static and dynamic control allocation approaches have been formulated to distribute high-level control objectives among the system inputs. For static control allocation, the interior-point method is applied to solve the formulated nonlinear optimization problem. Based on the dynamic control allocation method, a dynamic update law is derived to allocate vehicle control to tire forces. The allocated tire forces are fed into a low-level control module, where the applied torque and active steering angle at each wheel are determined through a slip-ratio controller and an inverse tire model. Computer simulations are used to prove the significant effects of the proposed control allocation methods on improving the stability and handling performance. The advantages and limitations of each method have been discussed, and conclusions have been derived.

Regional allocation of CO2 emissions allowance over provinces in China by 2020

International Nuclear Information System (INIS)

Wang, Ke; Zhang, Xian; Wei, Yi-Ming; Yu, Shiwei

2013-01-01

The mitigation efforts of China are increasingly important for meeting global climate target since the rapid economic growth of China has led to an increasing share in the world's total CO 2 emissions. This paper sets out to explore the approach for realizing China's national mitigation targets submitted to the UNFCCC as part of the Copenhagen Accord; that is, to reduce the intensity of CO 2 emissions per unit of GDP by 40–45% by 2020, as well as reducing the energy intensity and increasing the share of non-fossil fuel consumption, through regional allocation of emission allowance over China's provinces. Since the realization of China's mitigation target essentially represents a total amount emission allowance allocation problem, an improved zero sum gains data envelopment analysis optimization model, which could deal with the constant total amount resources allocation, is proposed in this study. By utilizing this model and based on several scenarios of China's economic growth, CO 2 emissions, and energy consumption, a new efficient emission allowance allocation scheme on provincial level for China by 2020 is proposed. The allocation results indicate that different provinces have to shoulder different mitigation burdens in terms of emission intensity reduction, energy intensity reduction, and share of non-fossil fuels increase. - Highlights: ► We explore the approach to realize national CO 2 emissions reduction target of China by 2020. ► The CO 2 emissions allowance is allocated over China's 30 administrative regions. ► Several scenarios of China's regional economy, emission, energy consumption are given. ► The zero sum gains data envelopment analysis model is applied in emission allowance allocation. ► An efficient emission allowance allocation scheme on provincial level is proposed

A practical approach for solving multi-objective reliability redundancy allocation problems using extended bare-bones particle swarm optimization

International Nuclear Information System (INIS)

Zhang, Enze; Wu, Yifei; Chen, Qingwei

2014-01-01

This paper proposes a practical approach, combining bare-bones particle swarm optimization and sensitivity-based clustering for solving multi-objective reliability redundancy allocation problems (RAPs). A two-stage process is performed to identify promising solutions. Specifically, a new bare-bones multi-objective particle swarm optimization algorithm (BBMOPSO) is developed and applied in the first stage to identify a Pareto-optimal set. This algorithm mainly differs from other multi-objective particle swarm optimization algorithms in the parameter-free particle updating strategy, which is especially suitable for handling the complexity and nonlinearity of RAPs. Moreover, by utilizing an approach based on the adaptive grid to update the global particle leaders, a mutation operator to improve the exploration ability and an effective constraint handling strategy, the integrated BBMOPSO algorithm can generate excellent approximation of the true Pareto-optimal front for RAPs. This is followed by a data clustering technique based on difference sensitivity in the second stage to prune the obtained Pareto-optimal set and obtain a small, workable sized set of promising solutions for system implementation. Two illustrative examples are presented to show the feasibility and effectiveness of the proposed approach

Research on Multirobot Pursuit Task Allocation Algorithm Based on Emotional Cooperation Factor

Directory of Open Access Journals (Sweden)

Baofu Fang

2014-01-01

Full Text Available Multirobot task allocation is a hot issue in the field of robot research. A new emotional model is used with the self-interested robot, which gives a new way to measure self-interested robots’ individual cooperative willingness in the problem of multirobot task allocation. Emotional cooperation factor is introduced into self-interested robot; it is updated based on emotional attenuation and external stimuli. Then a multirobot pursuit task allocation algorithm is proposed, which is based on emotional cooperation factor. Combined with the two-step auction algorithm recruiting team leaders and team collaborators, set up pursuit teams, and finally use certain strategies to complete the pursuit task. In order to verify the effectiveness of this algorithm, some comparing experiments have been done with the instantaneous greedy optimal auction algorithm; the results of experiments show that the total pursuit time and total team revenue can be optimized by using this algorithm.

Allocation of Tutors and Study Centers in Distance Learning Using Geospatial Technologies

Directory of Open Access Journals (Sweden)

Shahid Nawaz Khan

2018-05-01

Full Text Available Allama Iqbal Open University (AIOU is Pakistan’s largest distance learning institute, providing education to 1.4 million students. This is a fairly large setup across a country where students are highly geographically distributed. Currently, the system works using a manual approach, which is not efficient. Allocation of tutors and study centers to students plays a key role in creating a better learning environment for distance learning. Assigning tutors and study centers to distance learning students is a challenging task when there is a huge geographic spread. Using geospatial technologies in open and distance learning can fix allocation problems. This research analyzes real data from the twin cities Islamabad and Rawalpindi. The results show that geospatial technologies can be used for efficient and proper resource utilization and allocation, which in turn can save time and money. The overall idea fits into an improved distance learning framework and related analytics.

NOTES ON OPTIMAL ALLOCATION FOR FIXED SIZE CONFIDENCE REGIONS OF THE DIFFERENCE OF TWO MULTINORMAL MEANS

OpenAIRE

Hyakutake, Hiroto; Kawasaki, Hidefumi

2004-01-01

We consider the problem of constructing a fixed-size confidence region of the difference of two multinormal means when the covariance matrices have intraclass correlation structure. When the covariance matrices are known, we derive an optimal allocation. A two-stage procedure is given for the problem with unknown covariance matrices.

Asset Allocation of Mutual Fund Investors

OpenAIRE

Dengpan Luo

2003-01-01

This paper studies mutual fund investors' asset allocation decisions using monthly flow data of U.S mutual fund industry from 1984 to 1998. We find that mutual fund investors change their asset allocations between stocks and bonds in reaction to business conditions tracked by changes in expected stock market returns. They tend to allocate less into stock funds during the trough of a business cycle when expected stock market returns are higher and to allocate more into stock funds during the p...

40 CFR 60.4142 - Hg allowance allocations.

Science.gov (United States)

2010-07-01

... 40 Protection of Environment 6 2010-07-01 2010-07-01 false Hg allowance allocations. 60.4142... Coal-Fired Electric Steam Generating Units Hg Allowance Allocations § 60.4142 Hg allowance allocations. (a)(1) The baseline heat input (in MMBtu) used with respect to Hg allowance allocations under...

A Spatial Queuing-Based Algorithm for Multi-Robot Task Allocation

Directory of Open Access Journals (Sweden)

William Lenagh

2015-08-01

Full Text Available Multi-robot task allocation (MRTA is an important area of research in autonomous multi-robot systems. The main problem in MRTA is to allocate a set of tasks to a set of robots so that the tasks can be completed by the robots while ensuring that a certain metric, such as the time required to complete all tasks, or the distance traveled, or the energy expended by the robots is reduced. We consider a scenario where tasks can appear dynamically and a task needs to be performed by multiple robots to be completed. We propose a new algorithm called SQ-MRTA (Spatial Queueing-MRTA that uses a spatial queue-based model to allocate tasks between robots in a distributed manner. We have implemented the SQ-MRTA algorithm on accurately simulated models of Corobot robots within the Webots simulator for different numbers of robots and tasks and compared its performance with other state-of-the-art MRTA algorithms. Our results show that the SQ-MRTA algorithm is able to scale up with the number of tasks and robots in the environment, and it either outperforms or performs comparably with respect to other distributed MRTA algorithms.

18 CFR 367.28 - Methods of allocation.

Science.gov (United States)

2010-04-01

... 18 Conservation of Power and Water Resources 1 2010-04-01 2010-04-01 false Methods of allocation... Instructions § 367.28 Methods of allocation. Indirect costs and compensation for use of capital must be... allocation. Both direct and allocated indirect costs on projects must be assigned among those companies in...

Importance measures and resource allocation

International Nuclear Information System (INIS)

Guey, C.N.; Morgan, T.; Hughes, E.A.

1987-01-01

This paper discusses various importance measures and their practical relevance to allocating resources. The characteristics of importance measures are illustrated through simple examples. Important factors associated with effectively allocating resources to improve plant system performance or to prevent system degradation are discussed. It is concluded that importance measures are only indicative of and not equal to the risk significance of a component, system, or event. A decision framework is suggested to provide a comprehensive basis for resource allocation

Control system of the inspection robots group applying auctions and multi-criteria analysis for task allocation

Science.gov (United States)

Panfil, Wawrzyniec; Moczulski, Wojciech

2017-10-01

In the paper presented is a control system of a mobile robots group intended for carrying out inspection missions. The main research problem was to define such a control system in order to facilitate a cooperation of the robots resulting in realization of the committed inspection tasks. Many of the well-known control systems use auctions for tasks allocation, where a subject of an auction is a task to be allocated. It seems that in the case of missions characterized by much larger number of tasks than number of robots it will be better if robots (instead of tasks) are subjects of auctions. The second identified problem concerns the one-sided robot-to-task fitness evaluation. Simultaneous assessment of the robot-to-task fitness and task attractiveness for robot should affect positively for the overall effectiveness of the multi-robot system performance. The elaborated system allows to assign tasks to robots using various methods for evaluation of fitness between robots and tasks, and using some tasks allocation methods. There is proposed the method for multi-criteria analysis, which is composed of two assessments, i.e. robot's concurrency position for task among other robots and task's attractiveness for robot among other tasks. Furthermore, there are proposed methods for tasks allocation applying the mentioned multi-criteria analysis method. The verification of both the elaborated system and the proposed tasks' allocation methods was carried out with the help of simulated experiments. The object under test was a group of inspection mobile robots being a virtual counterpart of the real mobile-robot group.

Single Allocation Hub-and-spoke Networks Design Based on Ant Colony Optimization Algorithm

Directory of Open Access Journals (Sweden)

Yang Pingle

2014-10-01

Full Text Available Capacitated single allocation hub-and-spoke networks can be abstracted as a mixed integer linear programming model equation with three variables. Introducing an improved ant colony algorithm, which has six local search operators. Meanwhile, introducing the "Solution Pair" concept to decompose and optimize the composition of the problem, the problem can become more specific and effectively meet the premise and advantages of using ant colony algorithm. Finally, location simulation experiment is made according to Australia Post data to demonstrate this algorithm has good efficiency and stability for solving this problem.

Management of electricity network cross border capacity: allocation procedures between France and Belgium; Gestion des capacites d'echange d'electricite: methodes d'allocation entre la France et la Belgique

Energy Technology Data Exchange (ETDEWEB)

Raytchev, D. [Bordeaux-4 Univ. Montesquieu, LAREefi, 33 (France)

2003-11-01

This paper tries to identify a method of allocation of the Interconnector capacity for the transport of electricity which complies best with the (conflicting) interests of users, system operators and regulators in the context of a common European market of electricity. The first part combines a historical approach with a comparative study of existing allocation procedures to show that the new joint mechanism of auctioning and market splitting, applied to the whole northern zone of UCTE is vastly superior to the existing allocation arrangement on the Franco-Belgian border. The second part discusses some problems related to the implementation of the new allocation mechanism. Here we examine some difficulties concerning ca achy auctioning (like auction methods and organisation, profit distribution and derivative markets) as well as the market splitting method (neutrality, markets without power exchanges, etc). The main obstacle facing the new method remains however the lack of willingness to address the urgent issue of reforming the present allocation procedures- a remnant from the period of centrally planned electricity systems where neighbouring monopoly companies negotiated agreements of mutual assistance. These agreements are currently kept in place by tacit inaction despite their heterogeneity and arbitrariness which slow down the emergence of a real competition capable of contesting the positions of historic operators. (authors)

Demographic and regional economic modeling using stochastic allocation in the City of Johannesburg

CSIR Research Space (South Africa)

Lamprecht, TJ

2005-11-01

Full Text Available submittal. Venter, Lamprecht, Badenhorst 10 o Dedensification occurring as a result of government actions to alleviate overpopulation problems in certain areas (a not uncommon issue in developing countries) is captured by specifying a residential... a common understanding of problems and of “the way the world works”. ILLUSTRATIVE APPLICATION: CITY OF JOHANNESBURG The allocation model’s application to the City of Johannesburg provides an illustration of its capabilities. Base year (2001...

A proposal toward a possibilistic multi-robot task allocation

Energy Technology Data Exchange (ETDEWEB)

Guerrero, J.

2017-07-01

One of the main problems to solve in multi-agent (or multi-robot) systems is to select the best robot or group of robots to carry out a specific task. This problem, referenced as Multi-Agent (robot) task allocation (MRTA), is still an open issue in real environments. Swarm intelligence methods provide very simple solutions for the MRTA problem. One of the most widely used swarm methods are the so-called Response Threshold algorithms, where the behavior of the systems is modeled as a Markov chain and the robots in each time step select the next task to execute according to a transition probability function. Among other factors, this probability depends on a stimulus (for example the distance between the robot and the task). This classical probabilistic approach presents a lot of disadvantages:the transition function must meet constraints of a probabilistic distribution, the system only convergences to a stationary asymptotically, and so on. In order to overcome these problems, a new theoretical framework based on fuzzy (possibilistic) Markov chains was proposed [2]. As was proved, the possibilistic Markov chains outperform the classical probabilistic when a Max-Min algebra is considered for matrix composition. For example, fuzzy Markov chains convergence to a stable state in a finite number of steps 10 times faster than its probability counter part. Moreover, they improve the predictions of the system under imprecise information. Firstly, this paper will review relevant work in MRTA, from theoretical and experimental point of view. Then it will be summarized the aforementioned recent advances given toward a new possibilistic swarm multi-robot task allocation framework. It will be seen how the possibilistic Markov chains behave when other algebras are considered for matrix composition [1] and how the possibility transition function impacts on the system's performance [3]. Finally, it will be proposed new future works in this field. (Author)

A proposal toward a possibilistic multi-robot task allocation

International Nuclear Information System (INIS)

Guerrero, J.

2017-01-01

One of the main problems to solve in multi-agent (or multi-robot) systems is to select the best robot or group of robots to carry out a specific task. This problem, referenced as Multi-Agent (robot) task allocation (MRTA), is still an open issue in real environments. Swarm intelligence methods provide very simple solutions for the MRTA problem. One of the most widely used swarm methods are the so-called Response Threshold algorithms, where the behavior of the systems is modeled as a Markov chain and the robots in each time step select the next task to execute according to a transition probability function. Among other factors, this probability depends on a stimulus (for example the distance between the robot and the task). This classical probabilistic approach presents a lot of disadvantages:the transition function must meet constraints of a probabilistic distribution, the system only convergences to a stationary asymptotically, and so on. In order to overcome these problems, a new theoretical framework based on fuzzy (possibilistic) Markov chains was proposed [2]. As was proved, the possibilistic Markov chains outperform the classical probabilistic when a Max-Min algebra is considered for matrix composition. For example, fuzzy Markov chains convergence to a stable state in a finite number of steps 10 times faster than its probability counter part. Moreover, they improve the predictions of the system under imprecise information. Firstly, this paper will review relevant work in MRTA, from theoretical and experimental point of view. Then it will be summarized the aforementioned recent advances given toward a new possibilistic swarm multi-robot task allocation framework. It will be seen how the possibilistic Markov chains behave when other algebras are considered for matrix composition [1] and how the possibility transition function impacts on the system's performance [3]. Finally, it will be proposed new future works in this field. (Author)

A Knowledge-Informed and Pareto-Based Artificial Bee Colony Optimization Algorithm for Multi-Objective Land-Use Allocation

Directory of Open Access Journals (Sweden)

Lina Yang

2018-02-01

Full Text Available Land-use allocation is of great significance in urban development. This type of allocation is usually considered to be a complex multi-objective spatial optimization problem, whose optimized result is a set of Pareto-optimal solutions (Pareto front reflecting different tradeoffs in several objectives. However, obtaining a Pareto front is a challenging task, and the Pareto front obtained by state-of-the-art algorithms is still not sufficient. To achieve better Pareto solutions, taking the grid-representative land-use allocation problem with two objectives as an example, an artificial bee colony optimization algorithm for multi-objective land-use allocation (ABC-MOLA is proposed. In this algorithm, the traditional ABC’s search direction guiding scheme and solution maintaining process are modified. In addition, a knowledge-informed neighborhood search strategy, which utilizes the auxiliary knowledge of natural geography and spatial structures to facilitate the neighborhood spatial search around each solution, is developed to further improve the Pareto front’s quality. A series of comparison experiments (a simulated experiment with small data volume and a real-world data experiment for a large area shows that all the Pareto fronts obtained by ABC-MOLA totally dominate the Pareto fronts by other algorithms, which demonstrates ABC-MOLA’s effectiveness in achieving Pareto fronts of high quality.

Joint slot allocation and dynamic pricing of container sea–rail multimodal transportation

Directory of Open Access Journals (Sweden)

Di Liu

2015-06-01

Full Text Available The container sea–rail multimodal transport system faces complex challenges with demand uncertainties for joint slot allocation and dynamic pricing. The challenge is formulated as a two-stage optimal model based on revenue management (RM as actual slots sale of multi-node container sea–rail multimodal transport usually includes contract sale to large shippers and free sale to scattered shippers. First stage in the model utilizes an origin-destination control approach, formulated as a stochastic integer programming equation, to settle long-term slot allocation in the contract market and empty container allocation. Second stage in the model is formulated as a stochastic nonlinear programming equation to solve a multiproduct joint dynamic pricing and inventory control problem for price settling and slot allocation in each period of free market. Considering the random nature of demand, the methods of chance constrained programming and robust optimization are utilized to transform stochastic models into deterministic models. A numerical experiment is presented to verify the availability of models and solving methods. Results of considering uncertain/certain demand are compared, which show that the two-stage optimal strategy integrating slot allocation with dynamic pricing considering random demand is revealed to increase the revenue for multimodal transport operators (MTO while concurrently satisfying shippers' demand. Research resulting from this paper will contribute to the theory and practice of container sea–rail multimodal transport revenue management and provide a scientific decision-making tool for MTO.

Joint Bandwidth and Power Allocation for MIMO Two-Way Relays-Assisted Overlay Cognitive Radio Systems

KAUST Repository

Alsharoa, Ahmad; Ghazzai, Hakim; Yaacoub, Elias; Alouini, Mohamed-Slim; Kamal, Ahmed

2015-01-01

This paper studies the achievable cognitive sum rate of an overlay cognitive radio (CR) system assisted with multiple antennas two-way relays in which primary users (PUs) cooperate with cognitive users (CUs) for mutual benefits. In this context, the problem of both bandwidth and power allocation is investigated. We propose that the CUs are allowed to allocate a part of the PUs spectrum to perform their cognitive transmission. In return, acting as amplify-and-forward two-way relays, they are exploited to support PUs to reach their target data rates over the remaining bandwidth. Power expressions for optimal transmit power allocated per PU and CU antenna are derived under primary quality-of-service constraint in addition to bandwidth and power budget constraints. More specifically, CUs act as relays for the PUs transmission and gain some spectrum as long as they respect these constraints. After deriving the optimal transmit powers, we employ a strong optimization tool based on swarm intelligence to optimize the full and complex relay amplification gain matrices in addition to the bandwidths released to primary and cognitive transmission. Furthermore, three different utility functions are considered in our optimization problems depending on the level of fairness among CUs.

Joint Bandwidth and Power Allocation for MIMO Two-Way Relays-Assisted Overlay Cognitive Radio Systems

KAUST Repository

Alsharoa, Ahmad

2015-10-08

This paper studies the achievable cognitive sum rate of an overlay cognitive radio (CR) system assisted with multiple antennas two-way relays in which primary users (PUs) cooperate with cognitive users (CUs) for mutual benefits. In this context, the problem of both bandwidth and power allocation is investigated. We propose that the CUs are allowed to allocate a part of the PUs spectrum to perform their cognitive transmission. In return, acting as amplify-and-forward two-way relays, they are exploited to support PUs to reach their target data rates over the remaining bandwidth. Power expressions for optimal transmit power allocated per PU and CU antenna are derived under primary quality-of-service constraint in addition to bandwidth and power budget constraints. More specifically, CUs act as relays for the PUs transmission and gain some spectrum as long as they respect these constraints. After deriving the optimal transmit powers, we employ a strong optimization tool based on swarm intelligence to optimize the full and complex relay amplification gain matrices in addition to the bandwidths released to primary and cognitive transmission. Furthermore, three different utility functions are considered in our optimization problems depending on the level of fairness among CUs.

Allocating multiple units

DEFF Research Database (Denmark)

Tranæs, Torben; Krishna, Kala

2002-01-01

This paper studies the allocation and rent distribution in multi-unit, combinatorial-bid auctions under complete information. We focus on the natural multi-unit analogue of the first-price auction, where buyers bid total payments, pay their bids, and where the seller allocates goods to maximize his...... auction, which is the multi unit analogue of a second-price auction. Furthermore, we characterize these equilibria when valuations take a number of different forms: diminishing marginal valuations, increasing average valuations, and marginal valuations with single turning points...

ESG Allocations

Data.gov (United States)

Department of Housing and Urban Development — This report displays the Emergency Solutions Grants (ESG), formerly Emergency Shelter Grants, allocation by jurisdiction. The website allows users to look at...

Life-cycle asset allocation with focus on retirement savings

OpenAIRE

Konicz, Agnieszka Karolina

2013-01-01

We consider optimal asset allocation of a pension saver with uncertain lifetime. The objective is to maximize the expected utility of the retirement savings. The model accounts for characteristics of a pension saver given by her mortality risk, risk attitude, type of retirement contract, trading costs, taxes, and uncertain labor income. The problem is solved using a combination of a multi-stage stochastic linear programming (SLP) model and stochastic optimal control, such that the practical a...

The Impact of Short-Sale Constraints on Asset Allocation Strategies via the Backward Markov Chain Approximation Method

OpenAIRE

Carl Chiarella; Chih-Ying Hsiao

2005-01-01

This paper considers an asset allocation strategy over a finite period under investment uncertainty and short-sale constraints as a continuous time stochastic control problem. Investment uncertainty is characterised by a stochastic interest rate and inflation risk. If there are no short-sale constraints, the optimal asset allocation strategy can be solved analytically. We consider several kinds of short-sale constraints and employ the backward Markov chain approximation method to explore the ...

Efficient Allocation of Resources for Defense of Spatially Distributed Networks Using Agent-Based Simulation.

Science.gov (United States)

Kroshl, William M; Sarkani, Shahram; Mazzuchi, Thomas A

2015-09-01

This article presents ongoing research that focuses on efficient allocation of defense resources to minimize the damage inflicted on a spatially distributed physical network such as a pipeline, water system, or power distribution system from an attack by an active adversary, recognizing the fundamental difference between preparing for natural disasters such as hurricanes, earthquakes, or even accidental systems failures and the problem of allocating resources to defend against an opponent who is aware of, and anticipating, the defender's efforts to mitigate the threat. Our approach is to utilize a combination of integer programming and agent-based modeling to allocate the defensive resources. We conceptualize the problem as a Stackelberg "leader follower" game where the defender first places his assets to defend key areas of the network, and the attacker then seeks to inflict the maximum damage possible within the constraints of resources and network structure. The criticality of arcs in the network is estimated by a deterministic network interdiction formulation, which then informs an evolutionary agent-based simulation. The evolutionary agent-based simulation is used to determine the allocation of resources for attackers and defenders that results in evolutionary stable strategies, where actions by either side alone cannot increase its share of victories. We demonstrate these techniques on an example network, comparing the evolutionary agent-based results to a more traditional, probabilistic risk analysis (PRA) approach. Our results show that the agent-based approach results in a greater percentage of defender victories than does the PRA-based approach. © 2015 Society for Risk Analysis.

Relay selection and resource allocation for two-way DF-AF cognitive radio networks

KAUST Repository

Alsharoa, Ahmad M.; Bader, Faouzi; Alouini, Mohamed-Slim

2013-01-01

In this letter, the problem of relay selection and optimal resource allocation for two-way relaying cognitive radio networks using half duplex amplify-and-forward and decode-and-forward protocols is investigated. The primary and secondary users are assumed to access the spectrum simultaneously, in a way that the interference introduced to the primary users should be below a certain tolerated limit. Dual decomposition and subgradient methods are used to find the optimal power allocation. A suboptimal approach based on a genetic algorithm is also presented. Simulation results show that the proposed suboptimal algorithm offers a performance close to the optimal performance with a considerable complexity saving. © 2013 IEEE.

Relay selection and resource allocation for two-way DF-AF cognitive radio networks

KAUST Repository

Alsharoa, Ahmad M.

2013-08-01

In this letter, the problem of relay selection and optimal resource allocation for two-way relaying cognitive radio networks using half duplex amplify-and-forward and decode-and-forward protocols is investigated. The primary and secondary users are assumed to access the spectrum simultaneously, in a way that the interference introduced to the primary users should be below a certain tolerated limit. Dual decomposition and subgradient methods are used to find the optimal power allocation. A suboptimal approach based on a genetic algorithm is also presented. Simulation results show that the proposed suboptimal algorithm offers a performance close to the optimal performance with a considerable complexity saving. © 2013 IEEE.

Environmental risk allocation in the asset rationalization process

International Nuclear Information System (INIS)

Kruhlak, R.M.; Miller, S.R.

1999-01-01

Public concern regarding the state of the environment has resulted in improved enforcement of existing laws related to protection of the environment. This has had an impact on oil and gas transactions. One of the factors which affects the nature of oil and gas acquisitions and dispositions is the risk associated with environmental conditions. For example, the purchaser of an oil or gas asset may acquire threats of prosecution under existing legislation, or may acquire significant costs associated with remediation or clean-up. Vendors may also be affected by environmental risks resulting from divestiture. Risks include increased liability, continuing liability, and a growing uncertainty over the potential extent and nature of environmental problems. These problems mean that lawyers must find adequate methods of allocating risk. The best approach is to place more emphasis on rigorous due diligence, disclosure and contractual accommodation of identifiable environmental problems at the time of the acquisition or disposition. 2 figs

Fuzzy Simulation-Optimization Model for Waste Load Allocation

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Motahhare Saadatpour

2006-01-01

Full Text Available This paper present simulation-optimization models for waste load allocation from multiple point sources which include uncertainty due to vagueness of the parameters and goals. This model employs fuzzy sets with appropriate membership functions to deal with uncertainties due to vagueness. The fuzzy waste load allocation model (FWLAM incorporate QUAL2E as a water quality simulation model and Genetic Algorithm (GA as an optimization tool to find the optimal combination of the fraction removal level to the dischargers and pollution control agency (PCA. Penalty functions are employed to control the violations in the system.  The results demonstrate that the goal of PCA to achieve the best water quality and the goal of the dischargers to use the full assimilative capacity of the river have not been satisfied completely and a compromise solution between these goals is provided. This fuzzy optimization model with genetic algorithm has been used for a hypothetical problem. Results demonstrate a very suitable convergence of proposed optimization algorithm to the global optima.

Portfolio Allocation Subject to Credit Risk

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Rogerio de Deus Oliveira

2003-12-01

Full Text Available Credit Risk is an important dimension to be considered in the risk management procedures of financial institutions. Is a particularly useful in emerging markets where default rates on bank loan products are usually high. It is usually calculated through highly costly Monte Carlo simulations which consider different stochastic factors driving the uncertainly associated to the borrowers liabilities. In this paper, under some restrictions, we drive closed form formulas for the probability distributions of default rates of bank loans products involving a big number of clients. This allows us to quickly obtain the credit risk of such products. Moreover, using these probability distributions, we solve the problem of optimal portfolio allocation under default risk.

Scheduling language and algorithm development study. Volume 1, phase 2: Design considerations for a scheduling and resource allocation system

Science.gov (United States)

Morrell, R. A.; Odoherty, R. J.; Ramsey, H. R.; Reynolds, C. C.; Willoughby, J. K.; Working, R. D.

1975-01-01

Data and analyses related to a variety of algorithms for solving typical large-scale scheduling and resource allocation problems are presented. The capabilities and deficiencies of various alternative problem solving strategies are discussed from the viewpoint of computer system design.

THE EFFECTIVENESS OF BUDGET ALLOCATION IN PUBLIC PROCUREMENT

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Irina Yu. Fedorova

2015-01-01

Full Text Available This article deals with the problem of budget allocation in the state order inRussia. Assesses the effectiveness of the financial mechanism of the public procurement business entities, purchasing activities are regulated by Federal Law №44-FZ and №223-FZ. The dynamics of financing the procurement process and reveal its features by using the most common methods of procurement through competitive bidding and without bidding. Identifies the causes of inefficient spending budget as a result of the non-competitive procurement methods by certain categories of business entities. 

A cooperative online learning scheme for resource allocation in 5G systems

KAUST Repository

Alqerm, Ismail; Shihada, Basem

2016-01-01

The demand on mobile Internet related services has increased the need for higher bandwidth in cellular networks. The 5G technology is envisioned as a solution to satisfy this demand as it provides high data rates and scalable bandwidth. The multi-tier heterogeneous structure of 5G with dense base station deployment, relays, and device-to-device (D2D) communications intends to serve users with different QoS requirements. However, the multi-tier structure causes severe interference among the multi-tier users which further complicates the resource allocation problem. In this paper, we propose a cooperative scheme to tackle the interference problem, including both cross-tier interference that affects macro users from other tiers and co-tier interference, which is among users belong to the same tier. The scheme employs an online learning algorithm for efficient spectrum allocation with power and modulation adaptation capability. Our evaluation results show that our online scheme outperforms others and achieves significant improvements in throughput, spectral efficiency, fairness, and outage ratio. © 2016 IEEE.

A cooperative online learning scheme for resource allocation in 5G systems

KAUST Repository

Alqerm, Ismail

2016-07-26

The demand on mobile Internet related services has increased the need for higher bandwidth in cellular networks. The 5G technology is envisioned as a solution to satisfy this demand as it provides high data rates and scalable bandwidth. The multi-tier heterogeneous structure of 5G with dense base station deployment, relays, and device-to-device (D2D) communications intends to serve users with different QoS requirements. However, the multi-tier structure causes severe interference among the multi-tier users which further complicates the resource allocation problem. In this paper, we propose a cooperative scheme to tackle the interference problem, including both cross-tier interference that affects macro users from other tiers and co-tier interference, which is among users belong to the same tier. The scheme employs an online learning algorithm for efficient spectrum allocation with power and modulation adaptation capability. Our evaluation results show that our online scheme outperforms others and achieves significant improvements in throughput, spectral efficiency, fairness, and outage ratio. © 2016 IEEE.

Transmission usage cost allocation schemes

International Nuclear Information System (INIS)

Abou El Ela, A.A.; El-Sehiemy, R.A.

2009-01-01

This paper presents different suggested transmission usage cost allocation (TCA) schemes to the system individuals. Different independent system operator (ISO) visions are presented using the proportional rata and flow-based TCA methods. There are two proposed flow-based TCA schemes (FTCA). The first FTCA scheme generalizes the equivalent bilateral exchanges (EBE) concepts for lossy networks through two-stage procedure. The second FTCA scheme is based on the modified sensitivity factors (MSF). These factors are developed from the actual measurements of power flows in transmission lines and the power injections at different buses. The proposed schemes exhibit desirable apportioning properties and are easy to implement and understand. Case studies for different loading conditions are carried out to show the capability of the proposed schemes for solving the TCA problem. (author)

Optimal Energy-Efficient Sensing and Power Allocation in Cognitive Radio Networks

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Xia Wu

2014-01-01

Full Text Available We consider a joint optimization of sensing parameter and power allocation for an energy-efficient cognitive radio network (CRN in which the primary user (PU is protected. The optimization problem to maximize the energy efficiency of CRN is formulated as a function of two variables, which are sensing time and transmit power, subject to the average interference power to the PU and the target detection probability. During the optimizing process, the quality of service parameter (the minimum rate acceptable to secondary users (SUs has also been taken into consideration. The optimal solutions are analyzed and an algorithm combined with fractional programming that maximizes the energy efficiency for CRN is presented. Numerical results show that the performance improvement is achieved by the joint optimization of sensing time and power allocation.

Two Reconfigurable Flight-Control Design Methods: Robust Servomechanism and Control Allocation

Science.gov (United States)

Burken, John J.; Lu, Ping; Wu, Zheng-Lu; Bahm, Cathy

2001-01-01

Two methods for control system reconfiguration have been investigated. The first method is a robust servomechanism control approach (optimal tracking problem) that is a generalization of the classical proportional-plus-integral control to multiple input-multiple output systems. The second method is a control-allocation approach based on a quadratic programming formulation. A globally convergent fixed-point iteration algorithm has been developed to make onboard implementation of this method feasible. These methods have been applied to reconfigurable entry flight control design for the X-33 vehicle. Examples presented demonstrate simultaneous tracking of angle-of-attack and roll angle commands during failures of the fight body flap actuator. Although simulations demonstrate success of the first method in most cases, the control-allocation method appears to provide uniformly better performance in all cases.

Simultaneous allocation of distributed resources using improved teaching learning based optimization

International Nuclear Information System (INIS)

Kanwar, Neeraj; Gupta, Nikhil; Niazi, K.R.; Swarnkar, Anil

2015-01-01

Highlights: • Simultaneous allocation of distributed energy resources in distribution networks. • Annual energy loss reduction is optimized using a multi-level load profile. • A new penalty factor approach is suggested to check node voltage deviations. • An improved TLBO is proposed by suggesting several modifications in standard TLBO. • An intelligent search is proposed to enhance the performance of solution technique. - Abstract: Active and reactive power flow in distribution networks can be effectively controlled by optimally placing distributed resources like shunt capacitors and distributed generators. This paper presents improved variant of Teaching Learning Based Optimization (TLBO) to efficiently and effectively deal with the problem of simultaneous allocation of these distributed resources in radial distribution networks while considering multi-level load scenario. Several algorithm specific modifications are suggested in the standard form of TLBO to cope against the intrinsic flaws of this technique. In addition, an intelligent search approach is proposed to restrict the problem search space without loss of diversity. This enhances the overall performance of the proposed method. The proposed method is investigated on IEEE 33-bus, 69-bus and 83-bus test distribution systems showing promising results

A Game for Energy-Aware Allocation of Virtualized Network Functions

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Roberto Bruschi

2016-01-01

Full Text Available Network Functions Virtualization (NFV is a network architecture concept where network functionality is virtualized and separated into multiple building blocks that may connect or be chained together to implement the required services. The main advantages consist of an increase in network flexibility and scalability. Indeed, each part of the service chain can be allocated and reallocated at runtime depending on demand. In this paper, we present and evaluate an energy-aware Game-Theory-based solution for resource allocation of Virtualized Network Functions (VNFs within NFV environments. We consider each VNF as a player of the problem that competes for the physical network node capacity pool, seeking the minimization of individual cost functions. The physical network nodes dynamically adjust their processing capacity according to the incoming workload, by means of an Adaptive Rate (AR strategy that aims at minimizing the product of energy consumption and processing delay. On the basis of the result of the nodes’ AR strategy, the VNFs’ resource sharing costs assume a polynomial form in the workflows, which admits a unique Nash Equilibrium (NE. We examine the effect of different (unconstrained and constrained forms of the nodes’ optimization problem on the equilibrium and compare the power consumption and delay achieved with energy-aware and non-energy-aware strategy profiles.

Tracking Control Based on Control Allocation with an Innovative Control Effector Aircraft Application

Directory of Open Access Journals (Sweden)

Chaoyang Dong

2016-01-01

Full Text Available This paper proposes a control allocation method for the tracking control problem of a class of morphing aircraft with special actuators which are different from the conventional actuation surfaces. This design of actuators can bring about some potential advantages to the flight vehicles; however, due to the integral constraints, the desired control cannot be performed accurately; therefore, it leads to undesirable tracking errors, so influencing the performance of the system. Because the system could be control allocated, based on the designed cost function that describes the tracking errors, the cuckoo search algorithm (CSA is introduced to search for the optimum solution within the calculated actuator execution commands that are equivalent to the desired commands. Several improvement measures are proposed for boosting the efficiency of the CSA and ensuring reasonable solutions. Simulation results show that the proposed control allocation method is necessary and effective, and the improvement measures are helpful in obtaining the optimum solution.

An Analysis and Allocation System for Library Collections Budgets: The Comprehensive Allocation Process (CAP)

Science.gov (United States)

Lyons, Lucy Eleonore; Blosser, John

2012-01-01

The "Comprehensive Allocation Process" (CAP) is a reproducible decision-making structure for the allocation of new collections funds, for the reallocation of funds within stagnant budgets, and for budget cuts in the face of reduced funding levels. This system was designed to overcome common shortcomings of current methods. Its philosophical…

Outcome based state budget allocation for diabetes prevention programs using multi-criteria optimization with robust weights.

Science.gov (United States)

Mehrotra, Sanjay; Kim, Kibaek

2011-12-01

We consider the problem of outcomes based budget allocations to chronic disease prevention programs across the United States (US) to achieve greater geographical healthcare equity. We use Diabetes Prevention and Control Programs (DPCP) by the Center for Disease Control and Prevention (CDC) as an example. We present a multi-criteria robust weighted sum model for such multi-criteria decision making in a group decision setting. The principal component analysis and an inverse linear programming techniques are presented and used to study the actual 2009 budget allocation by CDC. Our results show that the CDC budget allocation process for the DPCPs is not likely model based. In our empirical study, the relative weights for different prevalence and comorbidity factors and the corresponding budgets obtained under different weight regions are discussed. Parametric analysis suggests that money should be allocated to states to promote diabetes education and to increase patient-healthcare provider interactions to reduce disparity across the US.

Application research of power allocation based on Buck circuit in DC microgrid

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Wang Zihao

2017-01-01

Full Text Available In a traditional DC microgrid, the power sharing control strategy has been always used in the distributed power converters, resulting in not making outer power allocation arbitrarily. In order to solve the power output allocation problem of wind power in DC microgrid, the intelligent Buck circuit based on PI algorithm and the load current feed-forward method was used to realize the arbitrary regulation of the output power of the wind power in the DC microgrid system. Compared with traditional distributed generators power-sharing method, the simulation and experimental results show the proposed method can realize arbitrary power outputting from distributed generators. Finally, the simulation and experimental results prove the validity and effectiveness of the control method.

Endogeneously arising network allocation rules

NARCIS (Netherlands)

Slikker, M.

2006-01-01

In this paper we study endogenously arising network allocation rules. We focus on three allocation rules: the Myerson value, the position value and the component-wise egalitarian solution. For any of these three rules we provide a characterization based on component efficiency and some balanced

Risk allocation under liquidity constraints

NARCIS (Netherlands)

Csóka, P.; Herings, P.J.J.

2013-01-01

Risk allocation games are cooperative games that are used to attribute the risk of a financial entity to its divisions. In this paper, we extend the literature on risk allocation games by incorporating liquidity considerations. A liquidity policy specifies state-dependent liquidity requirements that

A Dynamic Tap Allocation for Concurrent CMA-DD Equalizers

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Trindade DiegovonBM

2010-01-01

Full Text Available Abstract This paper proposes a dynamic tap allocation for the concurrent CMA-DD equalizer as a low complexity solution for the blind channel deconvolution problem. The number of taps is a crucial factor which affects the performance and the complexity of most adaptive equalizers. Generally an equalizer requires a large number of taps in order to cope with long delays in the channel multipath profile. Simulations show that the proposed new blind equalizer is able to solve the blind channel deconvolution problem with a specified and reduced number of active taps. As a result, it minimizes the output excess mean square error due to inactive taps during and after the equalizer convergence and the hardware complexity as well.

Optimization Model for cooperative water allocation and valuation in large river basins regarding environmental constraints

Science.gov (United States)

Pournazeri, S.

2011-12-01

A comprehensive optimization model named Cooperative Water Allocation Model (CWAM) is developed for equitable and efficient water allocation and valuation of Zab river basin in order to solve the draught problems of Orumieh Lake in North West of Iran. The model's methodology consists of three phases. The first represents an initial water rights allocation among competing users. The second comprises the water reallocation process for complete usage by consumers. The third phase performs an allocation of the net benefit of the stakeholders participating in a coalition by applying cooperative game theory. The environmental constraints are accounted for in the water allocation model by entering probable environmental damage in a target function, and inputting the minimum water requirement of users. The potential of underground water usage is evaluated in order to compensate for the variation in the amount of surface water. This is conducted by applying an integrated economic- hydrologic river basin model. A node-link river basin network is utilized in CWAM which consists of two major blocks. The first indicates the internal water rights allocation and the second is associated to water and net benefit reallocation. System control, loss in links by evaporation or seepage, modification of inflow into the node, loss in nodes and loss in outflow are considered in this model. Water valuation is calculated for environmental, industrial, municipal and agricultural usage by net benefit function. It can be seen that the water rights are allocated efficiently and incomes are distributed appropriately based on quality and quantity limitations.

24 CFR 791.404 - Field Office allocation planning.

Science.gov (United States)

2010-04-01

... 24 Housing and Urban Development 4 2010-04-01 2010-04-01 false Field Office allocation planning... Allocation of Budget Authority for Housing Assistance § 791.404 Field Office allocation planning. (a) General objective. The allocation planning process should provide for the equitable distribution of available budget...

Equity, tariffing, regulation: analysis of the cost allocation policies of an electric utility industry

International Nuclear Information System (INIS)

Bezzina, J.

1998-01-01

In this work, an analysis in terms of equity of policies of tariffing regulation and cost allocation of a multi-products electric company (organized as a natural monopoly) is proposed. The goal is double. In a standard point of view, the first goal is to show that today's literature in the domains of public economy, industrial organization and regulation (traditionally based on efficiency considerations) is able to supply reading keys for the analysis of moral philosophy problems. In a positive point of view, the second goal is to demonstrate that the equity criterion is operational enough to judge tariffing management practices in a particular industrial environment and can be used as a regulatory instrument by an ethics-concerned authority. The document is organized in two parts. An ethical and economical analysis of the equity concepts between allocation efficiency, production efficiency and tariffing practices of companies is proposed first. A particular equity concept is considered which is ready to be implemented for the regulation of a public utility, and the ins and outs expected with an equity theory of tariffing practices are evoked. In a second part, an analysis of goal conflicts between the authority and the regulated company is made in a point of view of equity regulation and cost allocation. An improved equity criterion is defined first, from which a measure is built and becomes a tool for the regulatory authority. Then, its use by a regulatory authority fully informed or encountering information asymmetry problems are analyzed in order to show its stakes on the cost allocation and tariffing policies of the company. (J.S.)

Joint Spectrum Sensing and Resource Allocation for OFDM-based Transmission with a Cognitive Relay

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S. Eman Mahmoodi

2014-04-01

Full Text Available In this paper, we investigate the joint spectrum sensing and resource allocation problem to maximize throughput capacity of an OFDM-based cognitive radio link with a cognitive relay. By applying a cognitive relay that uses decode and forward (D&F, we achieve more reliable communications, generating less interference (by needing less transmit power and more diversity gain. In order to account for imperfections in spectrum sensing, the proposed schemes jointly modify energy detector thresholds and allocates transmit powers to all cognitive radio (CR subcarriers, while simultaneously assigning subcarrier pairs for secondary users (SU and the cognitive relay. This problem is cast as a constrained optimization problem with constraints on (1 interference introduced by the SU and the cognitive relay to the PUs; (2 miss-detection and false alarm probabilities and (3 subcarrier pairing for transmission on the SU transmitter and the cognitive relay and (4 minimum Quality of Service (QoS for each CR subcarrier. We propose one optimal and two suboptimal schemes all of which are compared to other schemes in the literature. Simulation results show that the proposed schemes achieve significantly higher throughput than other schemes in the literature for different relay situations.

Dynamic versus static allocation policies in multipurpose multireservoir systems

Science.gov (United States)

Tilmant, A.; Goor, Q.; Pinte, D.; van der Zaag, P.

2007-12-01

As the competition for water is likely to increase in the near future due to socioeconomic development and population growth, water resources managers will face hard choices when allocating water between competing users. Because water is a vital resource used in multiple sectors, including the environment, the allocation is inherently a political and social process, which is likely to become increasingly scrutinized as the competition grows between the different sectors. Since markets are usually absent or ineffective, the allocation of water between competing demands is achieved administratively taking into account key objectives such as economic efficiency, equity and maintaining the ecological integrity. When crop irrigation is involved, water is usually allocated by a system of annual rights to use a fixed, static, volume of water. In a fully-allocated basin, moving from a static to a dynamic allocation process, whereby the policies are regularly updated according to the hydrologic status of the river basin, is the first step towards the development of river basin management strategies that increase the productivity of water. More specifically, in a multipurpose multireservoir system, continuously adjusting release and withdrawal decisions based on the latest hydrologic information will increase the benefits derived from the system. However, the extent to which such an adjustment can be achieved results from complex spatial and temporal interactions between the physical characteristics of the water resources system (storage, natural flows), the economic and social consequences of rationing and the impacts on natural ecosystems. The complexity of the decision-making process, which requires the continuous evaluation of numerous trade-offs, calls for the use of integrated hydrologic-economic models. This paper compares static and dynamic management approaches for a cascade of hydropower-irrigation reservoirs using stochastic dual dynamic programming (SDDP

Heuristics for the Buffer Allocation Problem with Collision Probability Using Computer Simulation

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Eishi Chiba

2015-01-01

Full Text Available The standard manufacturing system for Flat Panel Displays (FPDs consists of a number of pieces of equipment in series. Each piece of equipment usually has a number of buffers to prevent collision between glass substrates. However, in reality, very few of these buffers seem to be used. This means that redundant buffers exist. In order to reduce cost and space necessary for manufacturing, the number of buffers should be minimized with consideration of possible collisions. In this paper, we focus on an in-line system in which each piece of equipment can have any number of buffers. In this in-line system, we present a computer simulation method for the computation of the probability of a collision occurring. Based on this method, we try to find a buffer allocation that achieves the smallest total number of buffers under an arbitrarily specified collision probability. We also implement our proposed method and present some computational results.

A woman's place: household labour allocation in rural Kenya.

Science.gov (United States)

Neitzert, M

1994-01-01

This article synthesizes the literature on household labor allocation. The review reveals that development policies impacting on the labor market favor men over women. Male favoritism also occurs in household decision-making. Data from the 1988 Rural Labor Force Survey were used to examine rural household labor allocation in 1988 and the extent of female and male participation in home and market production and the degree of labor market discrimination against women. It is argued that the standard neoclassical model of economics does not recognize the unequal bargaining power of each member of the household in arriving at a solution to the joint welfare maximization problem. Women's position is expected to worsen during economic development. Women will have less than full participation in the labor market. Women's distinct role in household welfare provision is often disregarded. Development policy mainly focuses on market activities where women hold few positions. Labor allocation in the empirical analysis pertains to the mean hours per week in farm activities, household activities, schooling, and paid or unpaid non-farm work. Findings indicate that average earnings were lower for females than males and that returns to education and training were higher for males than females. Wage discrimination accounted for 30-66% of the earnings gap between rural men and women. Women faced discrimination on their returns to human capital and occupational choices. The concentration of women in low-paying jobs accounted for 21% of the wage gap. Women's lower education accounted for over 10%. Findings suggest that Kenyan households respond to market incentives. Women worked longer hours than men and contributed more to household welfare. Policy should focus on models of household provisioning and not on a joint utility function. Policy should encourage households to revise labor allocation strategies.

Type monotonic allocation schemes for multi-glove games

OpenAIRE

Brânzei, R.; Solymosi, T.; Tijs, S.H.

2007-01-01

Multiglove markets and corresponding games are considered.For this class of games we introduce the notion of type monotonic allocation scheme.Allocation rules for multiglove markets based on weight systems are introduced and characterized.These allocation rules generate type monotonic allocation schemes for multiglove games and are also helpful in proving that each core element of the corresponding game is extendable to a type monotonic allocation scheme.The T-value turns out to generate a ty...

Optimal dynamic water allocation: Irrigation extractions and environmental tradeoffs in the Murray River, Australia

Science.gov (United States)

Grafton, R. Quentin; Chu, Hoang Long; Stewardson, Michael; Kompas, Tom

2011-12-01

A key challenge in managing semiarid basins, such as in the Murray-Darling in Australia, is to balance the trade-offs between the net benefits of allocating water for irrigated agriculture, and other uses, versus the costs of reduced surface flows for the environment. Typically, water planners do not have the tools to optimally and dynamically allocate water among competing uses. We address this problem by developing a general stochastic, dynamic programming model with four state variables (the drought status, the current weather, weather correlation, and current storage) and two controls (environmental release and irrigation allocation) to optimally allocate water between extractions and in situ uses. The model is calibrated to Australia's Murray River that generates: (1) a robust qualitative result that "pulse" or artificial flood events are an optimal way to deliver environmental flows over and above conveyance of base flows; (2) from 2001 to 2009 a water reallocation that would have given less to irrigated agriculture and more to environmental flows would have generated between half a billion and over 3 billion U.S. dollars in overall economic benefits; and (3) water markets increase optimal environmental releases by reducing the losses associated with reduced water diversions.

PS-CARA: Context-Aware Resource Allocation Scheme for Mobile Public Safety Networks

Directory of Open Access Journals (Sweden)

Zeeshan Kaleem

2018-05-01

Full Text Available The fifth-generation (5G communications systems are expecting to support users with diverse quality-of-service (QoS requirements. Beside these requirements, the task with utmost importance is to support the emergency communication services during natural or man-made disasters. Most of the conventional base stations are not properly functional during a disaster situation, so deployment of emergency base stations such as mobile personal cell (mPC is crucial. An mPC having moving capability can move in the disaster area to provide emergency communication services. However, mPC deployment causes severe co-channel interference to the users in its vicinity. The problem in the existing resource allocation schemes is its support for static environment, that does not fit well for mPC. So, a resource allocation scheme for mPC users is desired that can dynamically allocate resources based on users’ location and its connection establishment priority. In this paper, we propose a public safety users priority-based context-aware resource allocation (PS-CARA scheme for users sum-rate maximization in disaster environment. Simulations results demonstrate that the proposed PS-CARA scheme can increase the user average and edge rate around 10.3% and 32.8% , respectively because of context information availability and by prioritizing the public safety users. The simulation results ensure that call blocking probability is also reduced considerably under the PS-CARA scheme.

Optimal resource allocation for distributed video communication

CERN Document Server

He, Yifeng

2013-01-01

While most books on the subject focus on resource allocation in just one type of network, this book is the first to examine the common characteristics of multiple distributed video communication systems. Comprehensive and systematic, Optimal Resource Allocation for Distributed Video Communication presents a unified optimization framework for resource allocation across these systems. The book examines the techniques required for optimal resource allocation over Internet, wireless cellular networks, wireless ad hoc networks, and wireless sensor networks. It provides you with the required foundat

17 CFR 256.01-11 - Methods of allocation.

Science.gov (United States)

2010-04-01

... applicable and currently effective methods of allocation filed with the Commission. Both direct and allocated... 17 Commodity and Securities Exchanges 3 2010-04-01 2010-04-01 false Methods of allocation. 256.01... HOLDING COMPANY ACT OF 1935 General Instructions § 256.01-11 Methods of allocation. Indirect costs and...

Adolescence, Attention Allocation, and Driving Safety

Science.gov (United States)

Romer, Daniel; Lee, Yi-Ching; McDonald, Catherine C.; Winston, Flaura K.

2014-01-01

Motor vehicle crashes are the leading source of morbidity and mortality in adolescents in the United States and the developed world. Inadequate allocation of attention to the driving task and to driving hazards are important sources of adolescent crashes. We review major explanations for these attention failures with particular focus on the roles that brain immaturity and lack of driving experience play in causing attention problems. The review suggests that the potential for overcoming inexperience and immaturity with training to improve attention to both the driving task and hazards is substantial. Nevertheless, there are large individual differences in both attentional abilities and risky driving tendencies that pose challenges to novice driver policies. Research that can provide evidence-based direction for such policies is urgently needed. PMID:24759442

Intelligent tactical asset allocation support system

OpenAIRE

Hiemstra, Y.

1995-01-01

This paper presents an advanced support system for Tactical Asset Allocation. Asset allocation explains over 90% of portfolio performance (Brinson, Hood and Beebower, 1988). Tactical asset allocation adjusts a strategic portfolio on the basis of short term market outlooks. The system includes aprediction model that forecasts quarterly excess returns on the S and PSOO, an optimization model that adjusts a user-specified strategic portfolio on thebasis of the excess return forecast, and a compo...

A weighted possibilistic programming approach for sustainable vendor selection and order allocation in fuzzy environment

DEFF Research Database (Denmark)

Gupta, Pankaj; Govindan, Kannan; Mehlawat, Mukesh Kumar

2016-01-01

This paper focused on the analysis of imprecise information in terms of many critical parameters for a multi-objective multi-item vendor selection-order allocation problem with price-breaks. We used both quantitative and qualitative criteria taking into account the economic, technological, social...

Profit allocation of independent power producers based on cooperative Game theory

International Nuclear Information System (INIS)

Jia, N.X.; Yokoyama, R.

2003-01-01

With the development of deregulation, the retail market is being formed. The independent power producers (IPPs) can contact the customers and sell electric power to them directly to obtain the profits because IPPs can provide electricity at cheaper prices to the customers than the utilities can. If IPP can obtain further more profit through collaborating with other ones in some coalition, it will prefer to collaborate to form this coalition rather than participating individually. In coalition, also the problem of how to allocate profit rationally for each IPP should also be solved. In this paper, we discuss the cooperation of IPPs in retail market and give a formulation about the calculation of IPPs profits. After that, based on Game theory, we propose a scheme to decide the profit allocation of each IPP in the coalitions rationally and impartially. (author)

Large Portfolio Risk Management and Optimal Portfolio Allocation with Dynamic Copulas

OpenAIRE

Thorsten Lehnert; Xisong Jin

2011-01-01

Previous research focuses on the importance of modeling the multivariate distribution for optimal portfolio allocation and active risk management. However, available dynamic models are not easily applied for high-dimensional problems due to the curse of dimensionality. In this paper, we extend the framework of the Dynamic Conditional Correlation/Equicorrelation and an extreme value approach into a series of Dynamic Conditional Elliptical Copulas. We investigate risk measures like Value at Ris...

Market-Based Resource Allocation in a Wirelessly Integrated Naval Engineering Plant

Science.gov (United States)

2009-12-01

available wireless nodes will be developed. Using a multi-agent approach based on free market economics (termed market based control) will be explored...as battery power, data storage capacity, MPU time, wireless bandwidth, etc.) required to perform complex computational tasks are available only in a...network. One approach to this problem is to apply free-market economics to help allocate these resources. Free-market economies can be thought of as

Design for Warehouse with Product Flow Type Allocation using Linear Programming: A Case Study in a Textile Industry

Science.gov (United States)

Khannan, M. S. A.; Nafisah, L.; Palupi, D. L.

2018-03-01

Sari Warna Co. Ltd, a company engaged in the textile industry, is experiencing problems in the allocation and placement of goods in the warehouse. During this time the company has not implemented the product flow type allocation and product placement to the respective products resulting in a high total material handling cost. Therefore, this study aimed to determine the allocation and placement of goods in the warehouse corresponding to product flow type with minimal total material handling cost. This research is a quantitative research based on the theory of storage and warehouse that uses a mathematical model of optimization problem solving using mathematical optimization model approach belongs to Heragu (2005), aided by software LINGO 11.0 in the calculation of the optimization model. Results obtained from this study is the proportion of the distribution for each functional area is the area of cross-docking at 0.0734, the reserve area at 0.1894, and the forward area at 0.7372. The allocation of product flow type 1 is 5 products, the product flow type 2 is 9 products, the product flow type 3 is 2 products, and the product flow type 4 is 6 products. The optimal total material handling cost by using this mathematical model equal to Rp43.079.510 while it is equal to Rp 49.869.728 by using the company’s existing method. It saves Rp6.790.218 for the total material handling cost. Thus, all of the products can be allocated in accordance with the product flow type with minimal total material handling cost.

Relay Selection and Resource Allocation in One-Way and Two-Way Cognitive Relay Networks

KAUST Repository

Alsharoa, Ahmad M.

2013-05-08

In this work, the problem of relay selection and resource power allocation in one- way and two-way cognitive relay networks using half duplex channels with different relaying protocols is investigated. Optimization problems for both single and multiple relay selection that maximize the sum rate of the secondary network without degrading the quality of service of the primary network by respecting a tolerated interference threshold were formulated. Single relay selection and optimal power allocation for two-way relaying cognitive radio networks using decode-and-forward and amplify-and-forward protocols were studied. Dual decomposition and subgradient methods were used to find the optimal power allocation. The transmission process to exchange two different messages between two transceivers for two-way relaying technique takes place in two time slots. In the first slot, the transceivers transmit their signals simultaneously to the relay. Then, during the second slot the relay broadcasts its signal to the terminals. Moreover, improvement of both spectral and energy efficiency can be achieved compared with the one-way relaying technique. As an extension, a multiple relay selection for both one-way and two-way relaying under cognitive radio scenario using amplify-and-forward were discussed. A strong optimization tool based on genetic and iterative algorithms was employed to solve the 
formulated optimization problems for both single and multiple relay selection, where discrete relay power levels were considered. Simulation results show that the practical and low-complexity heuristic approaches achieve almost the same performance of the optimal relay selection schemes either with discrete or continuous power distributions while providing a considerable saving in terms of computational complexity.

[Ethical problems in organ transplantation].

Science.gov (United States)

Valenta, J; Treska, V; Hasman, D

1999-02-01

Organ transplantation is an accepted therapeutic method with good results, but it is connected with many not only medical but also ethical problems. One of the most important problems is the donor programme. In cadaverous donors the main ethical and legal question is the decision who can issue the consent with organ retrieval; in living donors it is the problem of motivation and financial compensation. Allocation of organs with low compatibility or from non-ideal donors, and the recipient's consent in these cases may involve difficult decisions.

Spectrum and power allocation in cognitive multi-beam satellite communications with flexible satellite payloads

Science.gov (United States)

Liu, Zhihui; Wang, Haitao; Dong, Tao; Yin, Jie; Zhang, Tingting; Guo, Hui; Li, Dequan

2018-02-01

In this paper, the cognitive multi-beam satellite system, i.e., two satellite networks coexist through underlay spectrum sharing, is studied, and the power and spectrum allocation method is employed for interference control and throughput maximization. Specifically, the multi-beam satellite with flexible payload reuses the authorized spectrum of the primary satellite, adjusting its transmission band as well as power for each beam to limit its interference on the primary satellite below the prescribed threshold and maximize its own achievable rate. This power and spectrum allocation problem is formulated as a mixed nonconvex programming. For effective solving, we first introduce the concept of signal to leakage plus noise ratio (SLNR) to decouple multiple transmit power variables in the both objective and constraint, and then propose a heuristic algorithm to assign spectrum sub-bands. After that, a stepwise plus slice-wise algorithm is proposed to implement the discrete power allocation. Finally, simulation results show that adopting cognitive technology can improve spectrum efficiency of the satellite communication.

Dynamic Optimization for IPS2 Resource Allocation Based on Improved Fuzzy Multiple Linear Regression

Directory of Open Access Journals (Sweden)

Maokuan Zheng

2017-01-01

Full Text Available The study mainly focuses on resource allocation optimization for industrial product-service systems (IPS2. The development of IPS2 leads to sustainable economy by introducing cooperative mechanisms apart from commodity transaction. The randomness and fluctuation of service requests from customers lead to the volatility of IPS2 resource utilization ratio. Three basic rules for resource allocation optimization are put forward to improve system operation efficiency and cut unnecessary costs. An approach based on fuzzy multiple linear regression (FMLR is developed, which integrates the strength and concision of multiple linear regression in data fitting and factor analysis and the merit of fuzzy theory in dealing with uncertain or vague problems, which helps reduce those costs caused by unnecessary resource transfer. The iteration mechanism is introduced in the FMLR algorithm to improve forecasting accuracy. A case study of human resource allocation optimization in construction machinery industry is implemented to test and verify the proposed model.

Optimal Power Allocation for Downstream xDSL With Per-Modem Total Power Constraints: Broadcast Channel Optimal Spectrum Balancing (BC-OSB)

Science.gov (United States)

Le Nir, Vincent; Moonen, Marc; Verlinden, Jan; Guenach, Mamoun

2009-02-01

Recently, the duality between Multiple Input Multiple Output (MIMO) Multiple Access Channels (MAC) and MIMO Broadcast Channels (BC) has been established under a total power constraint. The same set of rates for MAC can be achieved in BC exploiting the MAC-BC duality formulas while preserving the total power constraint. In this paper, we describe the BC optimal power allo- cation applying this duality in a downstream x-Digital Subscriber Lines (xDSL) context under a total power constraint for all modems over all tones. Then, a new algorithm called BC-Optimal Spectrum Balancing (BC-OSB) is devised for a more realistic power allocation under per-modem total power constraints. The capacity region of the primal BC problem under per-modem total power constraints is found by the dual optimization problem for the BC under per-modem total power constraints which can be rewritten as a dual optimization problem in the MAC by means of a precoder matrix based on the Lagrange multipliers. We show that the duality gap between the two problems is zero. The multi-user power allocation problem has been solved for interference channels and MAC using the OSB algorithm. In this paper we solve the problem of multi-user power allocation for the BC case using the OSB algorithm as well and we derive a computational efficient algorithm that will be referred to as BC-OSB. Simulation results are provided for two VDSL2 scenarios: the first one with Differential-Mode (DM) transmission only and the second one with both DM and Phantom- Mode (PM) transmissions.

A Multi-layer Dynamic Model for Coordination Based Group Decision Making in Water Resource Allocation and Scheduling

Science.gov (United States)

Huang, Wei; Zhang, Xingnan; Li, Chenming; Wang, Jianying

Management of group decision-making is an important issue in water source management development. In order to overcome the defects in lacking of effective communication and cooperation in the existing decision-making models, this paper proposes a multi-layer dynamic model for coordination in water resource allocation and scheduling based group decision making. By introducing the scheme-recognized cooperative satisfaction index and scheme-adjusted rationality index, the proposed model can solve the problem of poor convergence of multi-round decision-making process in water resource allocation and scheduling. Furthermore, the problem about coordination of limited resources-based group decision-making process can be solved based on the effectiveness of distance-based group of conflict resolution. The simulation results show that the proposed model has better convergence than the existing models.

Identifying Memory Allocation Patterns in HEP Software

Science.gov (United States)

Kama, S.; Rauschmayr, N.

2017-10-01

HEP applications perform an excessive amount of allocations/deallocations within short time intervals which results in memory churn, poor locality and performance degradation. These issues are already known for a decade, but due to the complexity of software frameworks and billions of allocations for a single job, up until recently no efficient mechanism has been available to correlate these issues with source code lines. However, with the advent of the Big Data era, many tools and platforms are now available to do large scale memory profiling. This paper presents, a prototype program developed to track and identify each single (de-)allocation. The CERN IT Hadoop cluster is used to compute memory key metrics, like locality, variation, lifetime and density of allocations. The prototype further provides a web based visualization back-end that allows the user to explore the results generated on the Hadoop cluster. Plotting these metrics for every single allocation over time gives a new insight into application’s memory handling. For instance, it shows which algorithms cause which kind of memory allocation patterns, which function flow causes how many short-lived objects, what are the most commonly allocated sizes etc. The paper will give an insight into the prototype and will show profiling examples for the LHC reconstruction, digitization and simulation jobs.

Optimal Allocation of Water Resources Based on Water Supply Security

Directory of Open Access Journals (Sweden)

Jianhua Wang

2016-06-01

Full Text Available Under the combined impacts of climate change and human activities, a series of water issues, such as water shortages, have arisen all over the world. According to current studies in Science and Nature, water security has become a frontier critical topic. Water supply security (WSS, which is the state of water resources and their capacity and their capacity to meet the demand of water users by water supply systems, is an important part of water security. Currently, WSS is affected by the amount of water resources, water supply projects, water quality and water management. Water shortages have also led to water supply insecurity. WSS is now evaluated based on the balance of the supply and demand under a single water resources condition without considering the dynamics of the varying conditions of water resources each year. This paper developed an optimal allocation model for water resources that can realize the optimal allocation of regional water resources and comprehensively evaluate WSS. The objective of this model is to minimize the duration of water shortages in the long term, as characterized by the Water Supply Security Index (WSSI, which is the assessment value of WSS, a larger WSSI value indicates better results. In addition, the simulation results of the model can determine the change process and dynamic evolution of the WSS. Quanzhou, a city in China with serious water shortage problems, was selected as a case study. The allocation results of the current year and target year of planning demonstrated that the level of regional comprehensive WSS was significantly influenced by the capacity of water supply projects and the conditions of the natural water resources. The varying conditions of the water resources allocation results in the same year demonstrated that the allocation results and WSSI were significantly affected by reductions in precipitation, decreases in the water yield coefficient, and changes in the underlying surface.

K-Shortest-Path-Based Evacuation Routing with Police Resource Allocation in City Transportation Networks.

Directory of Open Access Journals (Sweden)

Yunyue He

Full Text Available Emergency evacuation aims to transport people from dangerous places to safe shelters as quickly as possible. Police play an important role in the evacuation process, as they can handle traffic accidents immediately and help people move smoothly on roads. This paper investigates an evacuation routing problem that involves police resource allocation. We propose a novel k-th-shortest-path-based technique that uses explicit congestion control to optimize evacuation routing and police resource allocation. A nonlinear mixed-integer programming model is presented to formulate the problem. The model's objective is to minimize the overall evacuation clearance time. Two algorithms are given to solve the problem. The first one linearizes the original model and solves the linearized problem with CPLEX. The second one is a heuristic algorithm that uses a police resource utilization efficiency index to directly solve the original model. This police resource utilization efficiency index significantly aids in the evaluation of road links from an evacuation throughput perspective. The proposed algorithms are tested with a number of examples based on real data from cities of different sizes. The computational results show that the police resource utilization efficiency index is very helpful in finding near-optimal solutions. Additionally, comparing the performance of the heuristic algorithm and the linearization method by using randomly generated examples indicates that the efficiency of the heuristic algorithm is superior.

A study of optimization problem for amplify-and-forward relaying over weibull fading channels

KAUST Repository

Ikki, Salama Said; Aissa, Sonia

2010-01-01

This paper addresses the power allocation and relay positioning problems in amplify-and-forward cooperative networks operating in Weibull fading environments. We study adaptive power allocation (PA) with fixed relay location, optimal relay location

Joint Load Balancing and Power Allocation for Hybrid VLC/RF Networks

KAUST Repository

Obeed, Mohanad

2018-01-15

In this paper, we propose and study a new joint load balancing (LB) and power allocation (PA) scheme for a hybrid visible light communication (VLC) and radio frequency (RF) system consisting of one RF\\\\access point (AP) and multiple VLC\\\\APs. An iterative algorithm is proposed to distribute the users on the APs and distribute the powers of these APs on their users. In PA subproblem, an optimization problem is formulated to allocate the power of each AP to the connected users for the total achievable data rates maximization. It is proved that the PA optimization problem is concave but not easy to tackle. Therefore, we provide a new algorithm to obtain the optimal dual variables after formulating them in terms of each other. Then, the users that are connected to the overloaded APs and receive less data rates start seeking for other APs that offer higher data rates. Users with lower data rates continue re-connecting from AP to other to balance the load only if this travel increases the summation of the achievable data rates and enhances the system fairness. The numerical results demonstrate that the proposed algorithms improve the system capacity and system fairness with fast convergence.

Joint Load Balancing and Power Allocation for Hybrid VLC/RF Networks

KAUST Repository

Obeed, Mohanad; Salhab, Anas M.; Zummo, Salam A.; Alouini, Mohamed-Slim

2018-01-01

In this paper, we propose and study a new joint load balancing (LB) and power allocation (PA) scheme for a hybrid visible light communication (VLC) and radio frequency (RF) system consisting of one RF\\access point (AP) and multiple VLC\\APs. An iterative algorithm is proposed to distribute the users on the APs and distribute the powers of these APs on their users. In PA subproblem, an optimization problem is formulated to allocate the power of each AP to the connected users for the total achievable data rates maximization. It is proved that the PA optimization problem is concave but not easy to tackle. Therefore, we provide a new algorithm to obtain the optimal dual variables after formulating them in terms of each other. Then, the users that are connected to the overloaded APs and receive less data rates start seeking for other APs that offer higher data rates. Users with lower data rates continue re-connecting from AP to other to balance the load only if this travel increases the summation of the achievable data rates and enhances the system fairness. The numerical results demonstrate that the proposed algorithms improve the system capacity and system fairness with fast convergence.

Fault-Aware Resource Allocation for Heterogeneous Data Sources with Multipath Routing

Directory of Open Access Journals (Sweden)

Xiaomei Zhang

2017-01-01

Full Text Available With the rapid development of cloud computing and big data, diverse types of traffic generated from heterogeneous data sources are delivered throughout communication networks, which consist of various node kinds such as digital sensors and smart actuators, and different applications. Due to the shared medium, communication networks are vulnerable to misbehaving nodes, and it is a crucial aspect to maintain an acceptable level of service degradation. This paper studies the fault-aware resource allocation problem by exploiting multipath routing and dynamic rate assignment for heterogeneous sources. We estimate the impacts of faults and formulate the resource allocation as a lossy network flow optimization problem based on these estimates. The traditional flow optimization solutions focus on homogeneous traffic. In our work, we model the performance of heterogeneous applications as a relaxed utility function and develop an effective utility framework of rate control for heterogeneous sources with multipath routing in presence of misbehaving nodes. We design a distributed algorithm to decide the routing strategy and obtain the rate assignments on the available paths in a lossy utility fair manner. Extensive performance evaluations corroborate the significant performance of our algorithm in effective utility and utility fairness in the presence of misbehaving nodes.

Carbon allocation in forest ecosystems

Science.gov (United States)

Creighton M. Litton; James W. Raich; Michael G. Ryan

2007-01-01

Carbon allocation plays a critical role in forest ecosystem carbon cycling. We reviewed existing literature and compiled annual carbon budgets for forest ecosystems to test a series of hypotheses addressing the patterns, plasticity, and limits of three components of allocation: biomass, the amount of material present; flux, the flow of carbon to a component per unit...

A case study of supply chain simulation for determining the best stock allocation

Directory of Open Access Journals (Sweden)

Puryani

2018-01-01

Full Text Available You Dare is a Small and Medium Enterprise (SME engaged in fashion, namely the sale of shoes. The problems that occurred in Dare are their limit on the amount of the shoes supply from suppliers and the inventory allocation policies are unplanned, so the profit is not maximized. This study simulates inventory allocation policy that Dare applies to see the impact on profits of Dare then proceed with the design of new system scenarios. The new scenario aims to implement policies more appropriately to increase the profits of Dare. Simulations are performed with ProModel software.The results of this study indicate that the policy of only using intuition cannot maximize the profits. An appropriate policy to increase profits of Dare is to consider the demand and cost allocation. Based on simulation results, Dare will only have an average profit of IDR 52.187.000, whereas if Dare uses the proposed policy, the average profit will increase to IDR 55.948.000 within two years.

Load allocation of power plant using multi echelon economic dispatch

Science.gov (United States)

Wahyuda, Santosa, Budi; Rusdiansyah, Ahmad

2017-11-01

In this paper, the allocation of power plant load which is usually done with a single echelon as in the load flow calculation, is expanded into a multi echelon. A plant load allocation model based on the integration of economic dispatch and multi-echelon problem is proposed. The resulting model is called as Single Objective Multi Echelon Economic Dispatch (SOME ED). This model allows the distribution of electrical power in more detail in the transmission and distribution substations along the existing network. Considering the interconnection system where the distance between the plant and the load center is usually far away, therefore the loss in this model is seen as a function of distance. The advantages of this model is its capability of allocating electrical loads properly, as well as economic dispatch information with the flexibility of electric power system as a result of using multi-echelon. In this model, the flexibility can be viewed from two sides, namely the supply and demand sides, so that the security of the power system is maintained. The model was tested on a small artificial data. The results demonstrated a good performance. It is still very open to further develop the model considering the integration with renewable energy, multi-objective with environmental issues and applied to the case with a larger scale.

Pollution permits allocation and imperfect competition; Allocation de permis de pollution et concurrence imparfaite

Energy Technology Data Exchange (ETDEWEB)

Schwartz, S.

2004-12-15

The aim of this thesis is to highlight the imperfections on the permits markets and to analyze their consequences on markets' efficiency. More precisely, we try to identify the implications of the initial allocation of permits when such imperfections are present. We try to draw some conclusions for the regulator concerning the different forms of the permits' allocation. After having described and compared these forms, we define in which circumstances the initial allocation matters in terms of efficiency. Then, we study different forms of imperfections. First, we take into account the information asymmetry between firms and the regulator and we define an optimal mechanism to sell pollution permits. Then, we analyze a market power on a differentiated pollution permits market. At last, we study the exclusionary manipulation of pollution permits market. (author)

Energy-Efficient Power Allocation for Fixed-Gain Amplify-and-Forward Relay Networks with Partial Channel State Information

KAUST Repository

Zafar, Ammar; Alouini, Mohamed-Slim; Chen, Yunfei; Radaydeh, Redha M.

2012-01-01

In this letter, energy-efficient transmission and power allocation for fixed-gain amplify-and-forward relay networks with partial channel state information (CSI) are studied. In the energy-efficiency problem, the total power consumed is minimized

CO_2 emissions and energy intensity reduction allocation over provincial industrial sectors in China

International Nuclear Information System (INIS)

Wu, Jie; Zhu, Qingyuan; Liang, Liang

2016-01-01

Highlights: • DEA is used to evaluate the energy and environmental efficiency of 30 provincial industrial sector in China. • A new DEA-based model is proposed to allocate the CO_2 emissions and energy intensity reduction targets. • The context-dependent DEA is used to characterize the production plans. - Abstract: High energy consumption by the industry of developing countries has led to the problems of increasing emission of greenhouse gases (GHG) (primarily CO_2) and worsening energy shortages. To address these problems, many mitigation measures have been utilized. One major measure is to mandate fixed reductions of GHG emission and energy consumption. Therefore, it is important for each developing country to disaggregate their national reduction targets into targets for various geographical parts of the country. In this paper, we propose a DEA-based approach to allocate China’s national CO_2 emissions and energy intensity reduction targets over Chinese provincial industrial sectors. We firstly evaluate the energy and environmental efficiency of Chinese industry considering energy consumption and GHG emissions. Then, considering the necessity of mitigating GHG emission and energy consumption, we develop a context-dependent DEA technique which can better characterize the changeable production with reductions of CO_2 emission and energy intensity, to help allocate the national reduction targets over provincial industrial sectors. Our empirical study of 30 Chinese regions for the period 2005–2010 shows that the industry of China had poor energy and environmental efficiency. Considering three major geographical areas, eastern China’s industrial sector had the highest efficiency scores while in this aspect central and western China were similar to each other at a lower level. Our study shows that the most effective allocation of the national reduction target requires most of the 30 regional industrial to reduce CO_2 emission and energy intensity, while a

Bribe-proof Rules in the Division Problem

OpenAIRE

Jordi MassóAuthor-Email:; Alejandro Neme

2003-01-01

The division problem consists of allocating an amount of a perfectly divisible good among a group of n agents with single-peaked preferences. A rule maps preference profiles into n shares of the amount to be allocated. A rule is bribe-proof if no group of agents can compensate another agent to misrepresent his preference and, after an appropriate redistribution of their shares, each obtain a strictly preferred share. We characterize all bribe-proof rules as the class of efficient, strategy-pr...

Energy-Efficient Resource Allocation for Phantom Cellular Networks with Imperfect CSI

KAUST Repository

Abdelhady, Amr Mohamed Abdelaziz

2017-03-28

Multi-tier heterogeneous networks have become an essential constituent for next generation cellular networks. Meanwhile, energy efficiency (EE) has been considered a critical design criterion along with the traditional spectral efficiency (SE) metric. In this context, we study power and spectrum allocation for a two-tier phantom cellular network, The optimization framework includes both EE and SE. We consider densely deployed phantom cellular networks and model the EE optimization problem taking into consideration the inevitable interference in this setup and imperfect channel estimation impairments. To this end, we propose three resource allocation strategies aiming at optimizing this network EE performance metric. Furthermore, we investigate the effect of changing some system parameters on the performance of these strategies, such as phantom cells resource units share, number of deployed phantom cells within a macro cell , number of pilots, and the phantom cells transmission power budget. It is found that increasing the number of pilots will deteriorate the EE performance of the whole setup, while increasing phantom cells transmission power budget will not affect the EE of the whole setup significantly. In addition, we observed that it is always useful to allocate most of the network resource units to the phantom cells tier.

Energy-Efficient Resource Allocation for Phantom Cellular Networks with Imperfect CSI

KAUST Repository

Abdelhady, Amr Mohamed Abdelaziz; Amin, Osama; Alouini, Mohamed-Slim

2017-01-01

Multi-tier heterogeneous networks have become an essential constituent for next generation cellular networks. Meanwhile, energy efficiency (EE) has been considered a critical design criterion along with the traditional spectral efficiency (SE) metric. In this context, we study power and spectrum allocation for a two-tier phantom cellular network, The optimization framework includes both EE and SE. We consider densely deployed phantom cellular networks and model the EE optimization problem taking into consideration the inevitable interference in this setup and imperfect channel estimation impairments. To this end, we propose three resource allocation strategies aiming at optimizing this network EE performance metric. Furthermore, we investigate the effect of changing some system parameters on the performance of these strategies, such as phantom cells resource units share, number of deployed phantom cells within a macro cell , number of pilots, and the phantom cells transmission power budget. It is found that increasing the number of pilots will deteriorate the EE performance of the whole setup, while increasing phantom cells transmission power budget will not affect the EE of the whole setup significantly. In addition, we observed that it is always useful to allocate most of the network resource units to the phantom cells tier.

Allocation an indivisible good. A questionnaire-experimental study of intercultural differences

OpenAIRE

Schokkaert, E; Devooght, Kurt; Capéau, Bart; Lelli, Sara

2007-01-01

We present the results of a questionnaire study in Belgium, Burkina Faso and Indonesia focusing on the problem of the just allocation of an indivisible good. The formal axioms proposed in social choice theory are helpful in structuring the response patterns. Interindividual differences can be interpreted in a meaningful way in terms of basic intuitions about desert, efficiency and compensation. Belgian students are most resourceegalitarian, Burkinese students attach a large weight to innate c...

A novel frame-level constant-distortion bit allocation for smooth H.264/AVC video quality

Science.gov (United States)

Liu, Li; Zhuang, Xinhua

2009-01-01

It is known that quality fluctuation has a major negative effect on visual perception. In previous work, we introduced a constant-distortion bit allocation method [1] for H.263+ encoder. However, the method in [1] can not be adapted to the newest H.264/AVC encoder directly as the well-known chicken-egg dilemma resulted from the rate-distortion optimization (RDO) decision process. To solve this problem, we propose a new two stage constant-distortion bit allocation (CDBA) algorithm with enhanced rate control for H.264/AVC encoder. In stage-1, the algorithm performs RD optimization process with a constant quantization QP. Based on prediction residual signals from stage-1 and target distortion for smooth video quality purpose, the frame-level bit target is allocated by using a close-form approximations of ratedistortion relationship similar to [1], and a fast stage-2 encoding process is performed with enhanced basic unit rate control. Experimental results show that, compared with original rate control algorithm provided by H.264/AVC reference software JM12.1, the proposed constant-distortion frame-level bit allocation scheme reduces quality fluctuation and delivers much smoother PSNR on all testing sequences.

.

Directory of Open Access Journals (Sweden)

Hugo Leonardo Louzada Vervloet

2016-04-01

Full Text Available Bulk cargo ships are usually contracted under the Charter Party contract between the owner and the shipper. This contract establishes a time limit for vessel to stay at port. If the vessel is below this time the shipper receives a financial award and, if not, pay a fine to the owner. After the literature review, no articles were found on the Berth Allocation Problem (BAP that addressed the issues related to premium and fine from the perspective of Charter Party contract in order to maximize the financial result of the shipper, calculated as a reward less fine. Thus, a mathematical model is proposed for the BAP with consideration of the Charter Party, and instances based in the Port of Tubarão were developed and implemented in CPLEX 12.6. The results showed the applicability of the model in the scheduling of ships and also guidelines to support the negotiation of this type of contract.

Optimal defense resource allocation in scale-free networks

Science.gov (United States)

Zhang, Xuejun; Xu, Guoqiang; Xia, Yongxiang

2018-02-01

The robustness research of networked systems has drawn widespread attention in the past decade, and one of the central topics is to protect the network from external attacks through allocating appropriate defense resource to different nodes. In this paper, we apply a specific particle swarm optimization (PSO) algorithm to optimize the defense resource allocation in scale-free networks. Results reveal that PSO based resource allocation shows a higher robustness than other resource allocation strategies such as uniform, degree-proportional, and betweenness-proportional allocation strategies. Furthermore, we find that assigning less resource to middle-degree nodes under small-scale attack while more resource to low-degree nodes under large-scale attack is conductive to improving the network robustness. Our work provides an insight into the optimal defense resource allocation pattern in scale-free networks and is helpful for designing a more robust network.

Energy-Efficient Optimal Power Allocation in Integrated Wireless Sensor and Cognitive Satellite Terrestrial Networks.

Science.gov (United States)

Shi, Shengchao; Li, Guangxia; An, Kang; Gao, Bin; Zheng, Gan

2017-09-04

This paper proposes novel satellite-based wireless sensor networks (WSNs), which integrate the WSN with the cognitive satellite terrestrial network. Having the ability to provide seamless network access and alleviate the spectrum scarcity, cognitive satellite terrestrial networks are considered as a promising candidate for future wireless networks with emerging requirements of ubiquitous broadband applications and increasing demand for spectral resources. With the emerging environmental and energy cost concerns in communication systems, explicit concerns on energy efficient resource allocation in satellite networks have also recently received considerable attention. In this regard, this paper proposes energy-efficient optimal power allocation schemes in the cognitive satellite terrestrial networks for non-real-time and real-time applications, respectively, which maximize the energy efficiency (EE) of the cognitive satellite user while guaranteeing the interference at the primary terrestrial user below an acceptable level. Specifically, average interference power (AIP) constraint is employed to protect the communication quality of the primary terrestrial user while average transmit power (ATP) or peak transmit power (PTP) constraint is adopted to regulate the transmit power of the satellite user. Since the energy-efficient power allocation optimization problem belongs to the nonlinear concave fractional programming problem, we solve it by combining Dinkelbach's method with Lagrange duality method. Simulation results demonstrate that the fading severity of the terrestrial interference link is favorable to the satellite user who can achieve EE gain under the ATP constraint comparing to the PTP constraint.

Application of the hybrid Big Bang-Big Crunch algorithm to optimal reconfiguration and distributed generation power allocation in distribution systems

International Nuclear Information System (INIS)

Sedighizadeh, Mostafa; Esmaili, Masoud; Esmaeili, Mobin

2014-01-01

In this paper, a multi-objective framework is proposed for simultaneous optimal network reconfiguration and DG (distributed generation) power allocation. The proposed method encompasses objective functions of power losses, voltage stability, DG cost, and greenhouse gas emissions and it is optimized subject to power system operational and technical constraints. In order to solve the optimization problem, the HBB-BC (Hybrid Big Bang-Big Crunch) algorithm as one of the most recent heuristic tools is modified and employed here by introducing a mutation operator to enhance its exploration capability. To resolve the scaling problem of differently-scaled objective functions, a fuzzy membership is used to bring them into a same scale and then, the fuzzy fitness of the final objective function is utilized to measure the satisfaction level of the obtained solution. The proposed method is tested on balanced and unbalanced test systems and its results are comprehensively compared with previous methods considering different scenarios. According to results, the proposed method not only offers an enhanced exploration capability but also has a better converge rate compared with previous methods. In addition, the simultaneous network reconfiguration and DG power allocation leads to a more optimal result than separately doing tasks of reconfiguration and DG power allocation. - Highlights: • Hybrid Big Bang-Big Crunch algorithm is applied to network reconfiguration problem. • Joint reconfiguration and DG power allocation leads to a more optimal solution. • A mutation operator is used to improve the exploration capability of HBB-BC method. • The HBB-BC has a better convergence rate than the compared algorithms

Dynamic fair node spectrum allocation for ad hoc networks using random matrices

Science.gov (United States)

Rahmes, Mark; Lemieux, George; Chester, Dave; Sonnenberg, Jerry

2015-05-01

Dynamic Spectrum Access (DSA) is widely seen as a solution to the problem of limited spectrum, because of its ability to adapt the operating frequency of a radio. Mobile Ad Hoc Networks (MANETs) can extend high-capacity mobile communications over large areas where fixed and tethered-mobile systems are not available. In one use case with high potential impact, cognitive radio employs spectrum sensing to facilitate the identification of allocated frequencies not currently accessed by their primary users. Primary users own the rights to radiate at a specific frequency and geographic location, while secondary users opportunistically attempt to radiate at a specific frequency when the primary user is not using it. We populate a spatial radio environment map (REM) database with known information that can be leveraged in an ad hoc network to facilitate fair path use of the DSA-discovered links. Utilization of high-resolution geospatial data layers in RF propagation analysis is directly applicable. Random matrix theory (RMT) is useful in simulating network layer usage in nodes by a Wishart adjacency matrix. We use the Dijkstra algorithm for discovering ad hoc network node connection patterns. We present a method for analysts to dynamically allocate node-node path and link resources using fair division. User allocation of limited resources as a function of time must be dynamic and based on system fairness policies. The context of fair means that first available request for an asset is not envied as long as it is not yet allocated or tasked in order to prevent cycling of the system. This solution may also save money by offering a Pareto efficient repeatable process. We use a water fill queue algorithm to include Shapley value marginal contributions for allocation.

Joint duplex mode selection, channel allocation, and power control for full-duplex cognitive femtocell networks

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Mingjie Feng

2015-02-01

Full Text Available In this paper, we aim to maximize the sum rate of a full-duplex cognitive femtocell network (FDCFN as well as guaranteeing the quality of service (QoS of users in the form of a required signal to interference plus noise ratios (SINR. We first consider the case of a pair of channels, and develop optimum-achieving power control solutions. Then, for the case of multiple channels, we formulate joint duplex model selection, power control, and channel allocation as a mixed integer nonlinear problem (MINLP, and propose an iterative framework to solve it. The proposed iterative framework consists of a duplex mode selection scheme, a near-optimal distributed power control algorithm, and a greedy channel allocation algorithm. We prove the convergence of the proposed iterative framework as well as a lower bound for the greedy channel allocation algorithm. Numerical results show that the proposed schemes effectively improve the sum rate of FDCFNs.

Sensitivity analysis on the priority order of the radiological worker allocation model using goal programming

International Nuclear Information System (INIS)

Jung, Hae Yong; Lee, Kun Jai

1998-01-01

In nuclear power plant, it has been the important object to reduce the occupational radiation exposure (ORE). Recently, the optimization concept of management science has been studied to reduce the ORE in nuclear power plant. In optimization of the worker allocation, the collective dose, working time, individual dose, and total number of worker must be considered and their priority orders must be thought because the main constraint is necessary for determining the constraints variable of the radiological worker allocation problem. The ultimate object of this study is to look into the change of the optimal allocation of the radiological worker as priority order changes. In this study, the priority order is the characteristic of goal programming that is a kind of multi-objective linear programming. From a result of study using goal programming, the total number of worker and collective dose of worker have changed as the priority order has changed and the collective dose limit have played an important role in reducing the ORE

Maintainability allocation

International Nuclear Information System (INIS)

Guyot, Christian.

1980-06-01

The author gives the general lines of a method for the allocation and for the evaluation of maintainability of complex systems which is to be developed during the conference. The maintainability objective is supposed to be formulated under the form of a mean time to repair (M.T.T.R.) [fr

On System Engineering a Barter-Based Re-allocation of Space System Key Development Resources

Science.gov (United States)

Kosmann, William J.

NASA has had a decades-long problem with cost growth during the development of space science missions. Numerous agency-sponsored studies have produced average mission level development cost growths ranging from 23 to 77%. A new study of 26 historical NASA science instrument set developments using expert judgment to re-allocate key development resources has an average cost growth of 73.77%. Twice in history, during the Cassini and EOS-Terra science instrument developments, a barter-based mechanism has been used to re-allocate key development resources. The mean instrument set development cost growth was -1.55%. Performing a bivariate inference on the means of these two distributions, there is statistical evidence to support the claim that using a barter-based mechanism to re-allocate key instrument development resources will result in a lower expected cost growth than using the expert judgment approach. Agent-based discrete event simulation is the natural way to model a trade environment. A NetLogo agent-based barter-based simulation of science instrument development was created. The agent-based model was validated against the Cassini historical example, as the starting and ending instrument development conditions are available. The resulting validated agent-based barter-based science instrument resource re-allocation simulation was used to perform 300 instrument development simulations, using barter to re-allocate development resources. The mean cost growth was -3.365%. A bivariate inference on the means was performed to determine that additional significant statistical evidence exists to support a claim that using barter-based resource re-allocation will result in lower expected cost growth, with respect to the historical expert judgment approach. Barter-based key development resource re-allocation should work on science spacecraft development as well as it has worked on science instrument development. A new study of 28 historical NASA science spacecraft

Logic of management of strategic problems of the enterprise

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Ivahnenko Aleksandr Vladimirovich

2014-12-01

Full Text Available Problems of management by firm in the conditions of changes are considered, types of strategic problems, logic of constructions of system of strategic management are allocated. Principles of formation of strategy of firm and a strategy choice in conditions not full definiteness are defined.

Worst-case analysis of heap allocations

DEFF Research Database (Denmark)

Puffitsch, Wolfgang; Huber, Benedikt; Schoeberl, Martin

2010-01-01

the worst-case heap allocations of tasks. The analysis builds upon techniques that are well established for worst-case execution time analysis. The difference is that the cost function is not the execution time of instructions in clock cycles, but the allocation in bytes. In contrast to worst-case execution...... time analysis, worst-case heap allocation analysis is not processor dependent. However, the cost function depends on the object layout of the runtime system. The analysis is evaluated with several real-time benchmarks to establish the usefulness of the analysis, and to compare the memory consumption...

Resource Allocation for A Mobile Application Oriented Architecture

NARCIS (Netherlands)

Guo, Y.; Smit, Gerardus Johannes Maria; Lu, W.W.; Xie, X.

2005-01-01

A Montium is a coarse-grained reconfigurable architecture designed by the CADTES group of the University of Twente for mobile applications. This paper presents a resource allocation method to allocate variables to storage places and to schedule data movements for the Montium. The resource allocation

Financial Resources Allocation of Tabriz University of Medical Sciences

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Esmaeil Afiyan

2015-08-01

Full Text Available ​ Background and Objectives : According to complexity of resource allocation, issue about how to allocate health care resources in an accurate and fair manner has become the subject of discussions and decisions of related groups. Therefore, in this research we aim to study the methods of financial resource allocation of Tabriz University of Medical Sciences in order to identify its strengths and weaknesses for its promotion. Material and Methods : This study is a descriptive, qualitative sectional research and all comments have been collected by focus group discussions with experts and managers involved in the allocation of financial resources of Tabriz University of Medical Sciences. All factors affecting the process of allocation have been reviewd carefully. Results : Results suggested that except the health sector, none of the other sectors use the formulated  and scientific methods for allocating financial resources and despite the emphasize in the 4th development plan for operating funding, the final cost of the services, has no role in allocating financial resources. Conclusion : Regarding to judgmental and subjective method of financial resources allocation of Tabriz University of Medical Sciences and lack of documented and formulated methods, there is an essential need for developing an appropriate and formulated model for scientific allocation of financial resources in order to improve the efficiency and fairness of the allocation.

Economic development and the allocation of petroleum products in Sudan

International Nuclear Information System (INIS)

Cain, M.; Yousif, M.A.R.

1991-01-01

The Sudanese economy has been characterized in recent years by severe energy shortages which have affected all economic activity. More than 94% of the commercial energy is imported and the level of such imports is seriously limited by the current foreign exchange crisis. However, the problem is not just one of foreign exchange; there is also the problem of utilization of resources to avoid bottleneck problems of supply. The allocation of petroleum products in Sudan has had a severe effect on all aspects of economic life. The aim of this paper is to highlight the problem and to build a model to optimize the distribution of petroleum products in order to achieve at least a minimal supply in all regions. A large linear programming model has been developed and the solution indicates that current facilities should be able to satisfy 96% of the 1986 demand, about 30% more than the actual supply. Furthermore, with a little investment in storage facilities and extra trucks, the supply could satisfy total demand in the immediate future

A Dynamic Programming-Based Sustainable Inventory-Allocation Planning Problem with Carbon Emissions and Defective Item Disposal under a Fuzzy Random Environment

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Kai Kang

2018-01-01

Full Text Available There is a growing concern that business enterprises focus primarily on their economic activities and ignore the impact of these activities on the environment and the society. This paper investigates a novel sustainable inventory-allocation planning model with carbon emissions and defective item disposal over multiple periods under a fuzzy random environment. In this paper, a carbon credit price and a carbon cap are proposed to demonstrate the effect of carbon emissions’ costs on the inventory-allocation network costs. The percentage of poor quality products from manufacturers that need to be rejected is assumed to be fuzzy random. Because of the complexity of the model, dynamic programming-based particle swarm optimization with multiple social learning structures, a DP-based GLNPSO, and a fuzzy random simulation are proposed to solve the model. A case is then given to demonstrate the efficiency and effectiveness of the proposed model and the DP-based GLNPSO algorithm. The results found that total costs across the inventory-allocation network varied with changes in the carbon cap and that carbon emissions’ reductions could be utilized to gain greater profits.

Payments for Ecosystem Services for watershed water resource allocations

Science.gov (United States)

Fu, Yicheng; Zhang, Jian; Zhang, Chunling; Zang, Wenbin; Guo, Wenxian; Qian, Zhan; Liu, Laisheng; Zhao, Jinyong; Feng, Jian

2018-01-01

Watershed water resource allocation focuses on concrete aspects of the sustainable management of Ecosystem Services (ES) that are related to water and examines the possibility of implementing Payment for Ecosystem Services (PES) for water ES. PES can be executed to satisfy both economic and environmental objectives and demands. Considering the importance of calculating PES schemes at the social equity and cooperative game (CG) levels, to quantitatively solve multi-objective problems, a water resources allocation model and multi-objective optimization are provided. The model consists of three modules that address the following processes: ① social equity mechanisms used to study water consumer associations, ② an optimal decision-making process based on variable intervals and CG theory, and ③ the use of Shapley values of CGs for profit maximization. The effectiveness of the proposed methodology for realizing sustainable development was examined. First, an optimization model with water allocation objective was developed based on sustainable water resources allocation framework that maximizes the net benefit of water use. Then, to meet water quality requirements, PES cost was estimated using trade-off curves among different pollution emission concentration permissions. Finally, to achieve equity and supply sufficient incentives for water resources protection, CG theory approaches were utilized to reallocate PES benefits. The potential of the developed model was examined by its application to a case study in the Yongding River watershed of China. Approximately 128 Mm3 of water flowed from the upper reach (Shanxi and Hebei Provinces) sections of the Yongding River to the lower reach (Beijing) in 2013. According to the calculated results, Beijing should pay USD6.31 M (¥39.03 M) for water-related ES to Shanxi and Hebei Provinces. The results reveal that the proposed methodology is an available tool that can be used for sustainable development with resolving PES

Setting Optimal Bounds on Risk in Asset Allocation - a Convex Program

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James E. Falk

2002-10-01

Full Text Available The 'Portfolio Selection Problem' is traditionally viewed as selecting a mix of investment opportunities that maximizes the expected return subject to a bound on risk. However, in reality, portfolios are made up of a few 'asset classes' that consist of similar opportunities. The asset classes are managed by individual `sub-managers', under guidelines set by an overall portfolio manager. Once a benchmark (the `strategic' allocation has been set, an overall manager may choose to allow the sub-managers some latitude in which opportunities make up the classes. He may choose some overall bound on risk (as measured by the variance and wish to set bounds that constrain the submanagers. Mathematically we show that the problem is equivalent to finding a hyper-rectangle of maximal volume within an ellipsoid. It is a convex program, albeit with potentially a large number of constraints. We suggest a cutting plane algorithm to solve the problem and include computational results on a set of randomly generated problems as well as a real-world problem taken from the literature.

Energy Efficient Resource Allocation for Phantom Cellular Networks

KAUST Repository

Abdelhady, Amr

2016-04-01

Multi-tier heterogeneous networks have become an essential constituent for next generation cellular networks. Meanwhile, energy efficiency (EE) has been considered a critical design criterion along with the traditional spectral efficiency (SE) metric. In this context, we study power and spectrum allocation for the recently proposed two-tier network architecture known as phantom cellular networks. The optimization framework includes both EE and SE. First, we consider sparsely deployed cells experiencing negligible interference and assume perfect channel state information (CSI). For this setting, we propose an algorithm that finds the SE and EE resource allocation strategies. Then, we compare the performance of both design strategies versus number of users, and phantom cells share of the total available resource units (RUs). We aim to investigate the effect of some system parameters to achieve improved SE performance at a non-significant loss in EE performance, or vice versa. It is found that increasing phantom cells share of RUs decreases the SE performance loss due to EE optimization when compared with the optimized SE performance. Second, we consider the densely deployed phantom cellular networks and model the EE optimization problem having into consideration the inevitable interference and imperfect channel estimation. To this end, we propose three resource allocation strategies aiming at optimizing the EE performance metric of this network. Furthermore, we investigate the effect of changing some of the system parameters on the performance of the proposed strategies, such as phantom cells share of RUs, number of deployed phantom cells within a macro cell coverage, number of pilots and the maximum power available for transmission by the phantom cells BSs. It is found that increasing the number of pilots deteriorates the EE performance of the whole setup, while increasing maximum power available for phantom cells transmissions reduces the EE of the whole setup in a

APPROPRIATE ALLOCATION OF CONTINGENCY USING RISK ANALYSIS METHODOLOGY

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Andi Andi

2004-01-01

Full Text Available Many cost overruns in the world of construction are attributable to either unforeseen events or foreseen events for which uncertainty was not appropriately accommodated. It is argued that a significant improvement to project management performance may result from greater attention to the process of analyzing project risks. The objective of this paper is to propose a risk analysis methodology for appropriate allocation of contingency in project cost estimation. In the first step, project risks will be identified. Influence diagramming technique is employed to identify and to show how the risks affect the project cost elements and also the relationships among the risks themselves. The second step is to assess the project costs with regards to the risks under consideration. Using a linguistic approach, the degree of uncertainty of identified project risks is assessed and quantified. The problem of dependency between risks is taken into consideration during this analysis. For the final step, as the main purpose of this paper, a method for allocating appropriate contingency is presented. Two types of contingencies, i.e. project contingency and management reserve are proposed to accommodate the risks. An illustrative example is presented at the end to show the application of the methodology.

Allocating subsidies to R&D or to market applications of renewable energy? Balance and geographical relevance

NARCIS (Netherlands)

Koseoglu, N.M.; van den Bergh, J.C.J.M.; Subtil Lacarda, J.

2013-01-01

This paper discusses a basic problem in innovation studies, namely the allocation of scarce funds for governmental subsidies to market and R&D support, with the aim to effectively promote a transition from fossil fuels to renewable energy technologies. Although various ideas on this exist, a general

S4HARA: System for HIV/AIDS resource allocation.

Science.gov (United States)

Lasry, Arielle; Carter, Michael W; Zaric, Gregory S

2008-03-26

HIV/AIDS resource allocation decisions are influenced by political, social, ethical and other factors that are difficult to quantify. Consequently, quantitative models of HIV/AIDS resource allocation have had limited impact on actual spending decisions. We propose a decision-support System for HIV/AIDS Resource Allocation (S4HARA) that takes into consideration both principles of efficient resource allocation and the role of non-quantifiable influences on the decision-making process for resource allocation. S4HARA is a four-step spreadsheet-based model. The first step serves to identify the factors currently influencing HIV/AIDS allocation decisions. The second step consists of prioritizing HIV/AIDS interventions. The third step involves allocating the budget to the HIV/AIDS interventions using a rational approach. Decision-makers can select from several rational models of resource allocation depending on availability of data and level of complexity. The last step combines the results of the first and third steps to highlight the influencing factors that act as barriers or facilitators to the results suggested by the rational resource allocation approach. Actionable recommendations are then made to improve the allocation. We illustrate S4HARA in the context of a primary healthcare clinic in South Africa. The clinic offers six types of HIV/AIDS interventions and spends US$750,000 annually on these programs. Current allocation decisions are influenced by donors, NGOs and the government as well as by ethical and religious factors. Without additional funding, an optimal allocation of the total budget suggests that the portion allotted to condom distribution be increased from 1% to 15% and the portion allotted to prevention and treatment of opportunistic infections be increased from 43% to 71%, while allocation to other interventions should decrease. Condom uptake at the clinic should be increased by changing the condom distribution policy from a pull system to a push

Coexistence of Cognitive Small Cell and WiFi System: A Traffic Balancing Dual-Access Resource Allocation Scheme

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Xiaoge Huang

2018-01-01

Full Text Available We consider a holistic approach for dual-access cognitive small cell (DACS networks, which uses the LTE air interface in both licensed and unlicensed bands. In the licensed band, we consider a sensing-based power allocation scheme to maximize the sum data rate of DACSs by jointly optimizing the cell selection, the sensing operation, and the power allocation under the interference constraint to macrocell users. Due to intercell interference and the integer nature of the cell selection, the resulting optimization problems lead to a nonconvex integer programming. We reformulate the problem to a nonconvex power allocation game and find the relaxed equilibria, quasi-Nash equilibrium. Furthermore, in order to guarantee the fairness of the whole system, we propose a dynamic satisfaction-based dual-band traffic balancing (SDTB algorithm over licensed and unlicensed bands for DACSs which aims at maximizing the overall satisfaction of the system. We obtain the optimal transmission time in the unlicensed band to ensure the proportional fair coexistence with WiFi while guaranteeing the traffic balancing of DACSs. Simulation results demonstrate that the SDTB algorithm could achieve a considerable performance improvement relative to the schemes in literature, while providing a tradeoff between maximizing the total data rate and achieving better fairness among networks.

An Integrated Model of Material Supplier Selection and Order Allocation Using Fuzzy Extended AHP and Multiobjective Programming

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Zhi Li

2013-01-01

Full Text Available This paper presents a supplier selection and order allocation (SSOA model to solve the problem of a multiperiod supplier selection and then order allocation in the environment of short product life cycle and frequent material purchasing, for example, fast fashion environment in apparel industry. At the first stage, with consideration of multiple decision criteria and the fuzziness of the data involved in deciding the preferences of multiple decision variables in supplier selection, the fuzzy extent analytic hierarchy process (FEAHP is adopted. In the second stage, supplier ranks are inputted into an order allocation model that aims at minimizing the risk of material purchasing and minimizing the total material purchasing costs using a dynamic programming approach, subject to constraints on deterministic customer demand and deterministic supplier capacity. Numerical examples are presented, and computational results are reported.

Methods of Thrust Allocation in a DP Simulation System of Maritime University of Szczecin

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Zalewski Paweł

2016-12-01

Full Text Available Vessels conducting dynamic positioning (DP operations are usually equipped with thruster configurations that enable generation of resultant force and moment in any direction. These configurations are deliberately redundant in order to reduce the consequences of thruster failures and increase the safety. On such vessels a thrust allocation system must be used to distribute the control actions determined by the DP controller among the thrusters. The optimal allocation of thrusters′ settings in DP systems is a problem that can be solved by several convex optimization methods depending on criteria and constraints used. The paper presents linear programming (LP and quadratic programming (QP methods adopted in DP control model which is being developed in Maritime University of Szczecin for ship simulation purposes.

DSTATCOM allocation in distribution networks considering reconfiguration using differential evolution algorithm

International Nuclear Information System (INIS)

Jazebi, S.; Hosseinian, S.H.; Vahidi, B.

2011-01-01

Highlights: → Reconfiguration and DSTATCOM allocation are implemented for RDS planning. → Differential evolution algorithm is applied to solve the nonlinear problem. → Optimal status of tie switches, DSTATCOM size and location are determined. → The goal is to minimize network losses and to improve voltage profile. → The results show the effectiveness of the proposed method to satisfy objectives. -- Abstract: The main idea in distribution network reconfiguration is usually to reduce loss by changing the status of sectionalizing switches and determining appropriate tie switches. Recently Distribution FACTS (DFACTS) devices such as DSTATCOM also have been planned for loss reduction and voltage profile improvement in steady state conditions. This paper implements a combinatorial process based on reconfiguration and DSTATCOM allocation in order to mitigate losses and improve voltage profile in power distribution networks. The distribution system tie switches, DSTATCOM location and size have been optimally determined to obtain an appropriate operational condition. Differential evolution algorithm (DEA) has been used to solve and overcome the complicity of this combinatorial nonlinear optimization problem. To validate the accuracy of results a comparison with particle swarm optimization (PSO) has been made. Simulations have been applied on 69 and 83 busses distribution test systems. All optimization results show the effectiveness of the combinatorial approach in loss reduction and voltage profile improvement.

Resource Allocation for OFDMA-Based Cognitive Radio Networks with Application to H.264 Scalable Video Transmission

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Coon JustinP

2011-01-01

Full Text Available Resource allocation schemes for orthogonal frequency division multiple access- (OFDMA- based cognitive radio (CR networks that impose minimum and maximum rate constraints are considered. To demonstrate the practical application of such systems, we consider the transmission of scalable video sequences. An integer programming (IP formulation of the problem is presented, which provides the optimal solution when solved using common discrete programming methods. Due to the computational complexity involved in such an approach and its unsuitability for dynamic cognitive radio environments, we propose to use the method of lift-and-project to obtain a stronger formulation for the resource allocation problem such that the integrality gap between the integer program and its linear relaxation is reduced. A simple branching operation is then performed that eliminates any noninteger values at the output of the linear program solvers. Simulation results demonstrate that this simple technique results in solutions very close to the optimum.

Adolescence, attention allocation, and driving safety.

Science.gov (United States)

Romer, Daniel; Lee, Yi-Ching; McDonald, Catherine C; Winston, Flaura K

2014-05-01

Motor vehicle crashes are the leading source of morbidity and mortality in adolescents in the United States and the developed world. Inadequate allocation of attention to the driving task and to driving hazards are important sources of adolescent crashes. We review major explanations for these attention failures with particular focus on the roles that brain immaturity and lack of driving experience play in causing attention problems. The review suggests that the potential for overcoming inexperience and immaturity with training to improve attention to both the driving task and hazards is substantial. Nevertheless, there are large individual differences in both attentional abilities and risky driving tendencies that pose challenges to novice driver policies. Research that can provide evidence-based direction for such policies is urgently needed. Copyright © 2014 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

A heuristic approach to handle capacitated facility location problem evaluated using clustering internal evaluation

Science.gov (United States)

Sutanto, G. R.; Kim, S.; Kim, D.; Sutanto, H.

2018-03-01

One of the problems in dealing with capacitated facility location problem (CFLP) is occurred because of the difference between the capacity numbers of facilities and the number of customers that needs to be served. A facility with small capacity may result in uncovered customers. These customers need to be re-allocated to another facility that still has available capacity. Therefore, an approach is proposed to handle CFLP by using k-means clustering algorithm to handle customers’ allocation. And then, if customers’ re-allocation is needed, is decided by the overall average distance between customers and the facilities. This new approach is benchmarked to the existing approach by Liao and Guo which also use k-means clustering algorithm as a base idea to decide the facilities location and customers’ allocation. Both of these approaches are benchmarked by using three clustering evaluation methods with connectedness, compactness, and separations factors.

A note on the sensitivity of the strategic asset allocation problem

Directory of Open Access Journals (Sweden)

W.J. Hurley

2015-12-01

Full Text Available The Markowitz mean–variance portfolio optimization problem is a quadratic programming problem whose first-order conditions require the solution of a linear system. It is well known that the optimal portfolio weights are sensitive to parameter estimates, particularly the mean return vector. This has generally been attributed to the interaction of estimation error and optimization. In this paper we present some examples that suggest the linear system produced by the first-order conditions is ill-conditioned and it is this property that gives rise to the sensitivity of the optimal weights.

Optimal Power Allocation Algorithm for Radar Network Systems Based on Low Probability of Intercept Optimization(in English

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Shi Chen-guang

2014-08-01

Full Text Available A novel optimal power allocation algorithm for radar network systems is proposed for Low Probability of Intercept (LPI technology in modern electronic warfare. The algorithm is based on the LPI optimization. First, the Schleher intercept factor for a radar network is derived, and then the Schleher intercept factor is minimized by optimizing the transmission power allocation among netted radars in the network to guarantee target-tracking performance. Furthermore, the Nonlinear Programming Genetic Algorithm (NPGA is used to solve the resulting nonconvex, nonlinear, and constrained optimization problem. Numerical simulation results show the effectiveness of the proposed algorithm.

Joint Transmit Antenna Selection and Power Allocation for ISDF Relaying Mobile-to-Mobile Sensor Networks.

Science.gov (United States)

Xu, Lingwei; Zhang, Hao; Gulliver, T Aaron

2016-02-19

The outage probability (OP) performance of multiple-relay incremental-selective decode-and-forward (ISDF) relaying mobile-to-mobile (M2M) sensor networks with transmit antenna selection (TAS) over N-Nakagami fading channels is investigated. Exact closed-form OP expressions for both optimal and suboptimal TAS schemes are derived. The power allocation problem is formulated to determine the optimal division of transmit power between the broadcast and relay phases. The OP performance under different conditions is evaluated via numerical simulation to verify the analysis. These results show that the optimal TAS scheme has better OP performance than the suboptimal scheme. Further, the power allocation parameter has a significant influence on the OP performance.