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This validates them both. The TS has however a major drawback concerning the computation time. A problem with the enrichment as an additional parameter has been tested. In this case, the feasible domain is very narrow, and the optimization process has encountered limitations. Actually, the TS method may not be suitable to find the exact solution of the fuel management problem, but it may be used in a hybrid method such as a TS to find the global optimum region coupled with a gradient method to converge faster on the exact solution.
A tabu -search for minimising the carry-over effects value of a round The initial solution for the tabu -search algorithm was generated randomly by Three-dimensional high-precision indoor positioning strategy using Tabu search based on visible light communication. This paper proposes a three-dimensional 3-D high-precision indoor positioning strategy using Tabu search based on visible light communication. Tabu search is a powerful global optimization algorithm, and the 3-D indoor positioning can be transformed into an optimal solution problem.
Therefore, in the 3-D indoor positioning, the optimal receiver coordinate can be obtained by the Tabu search algorithm. For all we know, this is the first time the Tabu search algorithm is applied to visible light positioning. When the receiver detects optical signals with ID information from different LEDs, using the global optimization of the Tabu search algorithm, the 3-D high-precision indoor positioning can be realized when the fitness value meets certain conditions.
Simulation results show that the average positioning error is 0. The extended experiment of trajectory tracking also shows that It can be concluded from the data that the 3-D indoor positioning based on the Tabu search algorithm achieves the requirements of centimeter level indoor positioning. The algorithm used in indoor positioning is very effective and practical and is superior to other existing methods for visible light indoor positioning.
Application of multiple tabu search algorithm to solve dynamic economic dispatch considering generator constraints. This paper presents a new optimization technique based on a multiple tabu search algorithm MTS to solve the dynamic economic dispatch ED problem with generator constraints. In the constrained dynamic ED problem, the load demand and spinning reserve capacity as well as some practical operation constraints of generators, such as ramp rate limits and prohibited operating zone are taken into consideration.
The MTS algorithm introduces additional mechanisms such as initialization, adaptive searches, multiple searches, crossover and restarting process. To show its efficiency, the MTS algorithm is applied to solve constrained dynamic ED problems of power systems with 6 and 15 units.
The results obtained from the MTS algorithm are compared to those achieved from the conventional approaches, such as simulated annealing SA , genetic algorithm GA , tabu search TS algorithm and particle swarm optimization PSO. The experimental results show that the proposed MTS algorithm approaches is able to obtain higher quality solutions efficiently and with less computational time than the conventional approaches. Neural Based Tabu Search method for solving unit commitment problem with cooling-banking constraints.
The objective of this paper is to find the generation scheduling such that the total operating cost can be minimized, when subjected to a variety of constraints. This also means that it is desirable to find the optimal generating unit commitment in the power system for next H hours. A 7-unit utility power system in India demonstrates the effectiveness of the proposed approach; extensive studies have also been performed for different IEEE test systems consist of 10, 26 and 34 units.
The max—min ant system and tabu search for pressurized water reactor loading pattern design. The heuristic rules are implemented to generate the candidate LP in TS process.
The heuristic rules are comprised of two kinds of action, i. Since developed TS process is a local search algorithm, it is efficient for the minor change of LP. It means that a proper initial LP should be provided by the first step, i. The design requirements such as hot channel factor, the hot zero power moderator temperature coefficient, and cycle length are formulated in the objective function. The results show that the developed tool can obtain the satisfactory LP and dramatically reduce the computation time compared with previous tool using ant system alone.
Full Text Available The development of hybrid algorithms for solving complex optimization problems focuses on enhancing the strengths and compensating for the weakness of two or more complementary approaches. The goal is to intelligently combine the key elements of these approaches to find superior solutions to solve optimization problems. Optimal routing in communication network is considering a complex optimization problem.
The paradigm of this hybridization is embedded. The short-term memory and tabu restriction control the neuron selection process in the HNN model in order to get around the local minima problem and find an optimal solution using the HNN model to solve complex optimization problem. The proposed algorithm is intended to find the optimal path for packet transmission in the network which is fills in the field of routing problem.
The optimal path that will be selected is depending on 4-tuples delay, cost, reliability and capacity. Test results show that the propose algorithm can find path with optimal cost and a reasonable number of iterations. Martin del Campo M, C. Mexico ]. The advances in the development of a computational system for the design and optimization of cells for assemble of fuel of Boiling Water Reactors BWR are presented. The method of optimization is based on the technique of Tabu Search Tabu Search, TS implemented in progressive stages designed to accelerate the search and to reduce the time used in the process of optimization.
It was programed an algorithm to create the first solution. Also for to diversify the generation of random numbers, required by the technical TS, it was used the Makoto Matsumoto function obtaining excellent results. The objective function has been coded in such a way that can adapt to optimize different parameters like they can be the enrichment average or the peak factor of radial power.
In the work the main characteristics of the system are described and an application example is presented to the design of a cell of 10x10 bars of fuel with 10 different enrichment compositions and gadolinium content. El algoritmo propuesto es usado para resolver un caso real de asignación de supervisores forestales. Los resultados muestran que el algoritmo desarrollado es eficiente en la resolución de este tipo de problema y tiene un amplio rango de aplicación para otras situaciones reales.
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This study presents a mathematical model for a generic problem of staff allocation. A solution is implemented and evaluated by means of the Tabu Search metaheuristic. The proposed algorithm is used to solve a real case of forestry supervisors' allocation. The results show that the developed algorithm is efficient solving this kind of problems and that it has a wide range of application for other real situations.
Tabu search approaches for the multi-level warehouse layout problem with adjacency constraints.
A new multi-level warehouse layout problem, the multi-level warehouse layout problem with adjacency constraints MLWLPAC , is investigated. The same item type is required to be located in adjacent cells, and horizontal and vertical unit travel costs are product dependent.
An integer programming model is proposed to formulate the problem, which is NP hard.
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Along with a cube-per-order index policy based heuristic, the standard tabu search TS , greedy TS, and dynamic neighbourhood based TS are presented to solve the problem. The computational results show that the proposed approaches can reduce the transportation cost significantly. A hybridised variable neighbourhood tabu search heuristic to increase security in a utility network. We propose a decision model aimed at increasing security in a utility network e.
The network is modelled as a graph, the edges of which are unreliable.
We assume that all edges e. We develop a mathematical programming model and a metaheuristic approach that uses a greedy random adaptive search procedure to find an initial solution and uses tabu search hybridised with iterated local search and a variable neighbourhood descend heuristic to improve this solution. The main goal is to reduce the risk of service failure between an origin and a destination node by selecting the right combination of security measures for each network edge given a limited security budget.
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Full Text Available The Sudoku problem is a well-known logic-based puzzle of combinatorial number-placement. Such a puzzle belongs to the NP-complete collection of problems, to which there exist diverse exact and approximate methods able to solve it. In this paper, we propose a new hybrid algorithm that smartly combines a classic tabu search procedure with the alldifferent global constraint from the constraint programming world. The alldifferent constraint is known to be efficient for domain filtering in the presence of constraints that must be pairwise different, which are exactly the kind of constraints that Sudokus own.
This ability clearly alleviates the work of the tabu search, resulting in a faster and more robust approach for solving Sudokus. We illustrate interesting experimental results where our proposed algorithm outperforms the best results previously reported by hybrids and approximate methods. Cooperative mobile agents search using beehive partitioned structure and Tabu Random search algorithm.
In search and surveillance operations, deploying a team of mobile agents provides a robust solution that has multiple advantages over using a single agent in efficiency and minimizing exploration time. This paper addresses the challenge of identifying a target in a given environment when using a team of mobile agents by proposing a novel method of mapping and movement of agent teams in a cooperative manner. The approach consists of two parts. First, the region is partitioned into a hexagonal beehive structure in order to provide equidistant movements in every direction and to allow for more natural and flexible environment mapping.
Additionally, in search environments that are partitioned into hexagons, mobile agents have an efficient travel path while performing searches due to this partitioning approach. Second, we use a team of mobile agents that move in a cooperative manner and utilize the Tabu Random algorithm to search for the target. Due to the ever-increasing use of robotics and Unmanned Aerial Vehicle UAV platforms, the field of cooperative multi-agent search has developed many applications recently that would benefit from the use of the approach presented in this work, including: search and rescue operations, surveillance, data collection, and border patrol.
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In this paper, the increased efficiency of the Tabu Random Search algorithm method in combination with hexagonal partitioning is simulated, analyzed, and advantages of this approach are presented and discussed. Optimization of fuel cells for BWR based in Tabu modified search. An intelligent hybrid scheme for optimizing parking space: A Tabu metaphor and rough set based approach. Full Text Available Congested roads, high traffic, and parking problems are major concerns for any modern city planning.
Congestion of on-street spaces in official neighborhoods may give rise to inappropriate parking areas in office and shopping mall complex during the peak time of official transactions. This paper proposes an intelligent and optimized scheme to solve parking space problem for a small city e.