The Experts below are selected from a list of 13383 Experts worldwide ranked by ideXlab platform
Jose Brandao - One of the best experts on this subject based on the ideXlab platform.
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a Tabu Search Algorithm for the heterogeneous fixed fleet vehicle routing problem
Computers & Operations Research, 2011Co-Authors: Jose BrandaoAbstract:In the heterogeneous fixed fleet vehicle routing problem there are different types of vehicles and a given number of vehicles of each type. The resolution of this problem consists of assigning the customers to the existing vehicles and, in relation to each vehicle, defining the order of visiting each customer for the delivery or collection of goods. The objective is to minimize the total costs, satisfying customers' requirements and visiting each customer exactly once. In this paper a Tabu Search Algorithm is proposed and tested on several benchmark problems. The computational experiments show that the proposed Algorithm produces high quality solutions within an acceptable computation time. Four new best solutions are reported for a set of test problems used in the literature.
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a new Tabu Search Algorithm for the vehicle routing problem with backhauls
European Journal of Operational Research, 2006Co-Authors: Jose BrandaoAbstract:In the distribution of goods from a central depot to geographically dispersed customers happens quite frequently that some customers, called linehauls, receive goods from that depot while others, named backhauls, send goods to it. This situation is described and studied by the vehicle routing problem with backhauls. In this paper we present a new Tabu Search Algorithm that starting from pseudo-lower bounds was able to match almost all the best published solutions and to find many new best solutions, for a large set of benchmark problems.
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a Tabu Search Algorithm for the open vehicle routing problem
European Journal of Operational Research, 2004Co-Authors: Jose BrandaoAbstract:Abstract The problem studied in this paper is different from the basic vehicle routing problem in that the vehicles do not return to the distribution depot after delivering the goods to the customers or, if they do so, they must visit the same customers, for the collection of goods, in the reverse order. The practical importance of this problem has been established some decades ago, but it has received very little attention from reSearchers. In this paper we present a new Tabu Search Algorithm that explores the structure of this type of problem and we compare its performance with another heuristic designed for the same purpose, which has been published recently.
Yao-hsin Chou - One of the best experts on this subject based on the ideXlab platform.
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entanglement enhanced quantum inspired Tabu Search Algorithm for function optimization
IEEE Access, 2017Co-Authors: Yao-hsin ChouAbstract:Many metaheuristic Algorithms have been proposed to solve combinatorial and numerical optimization problems. Most optimization problems have high dependence, meaning that variables are strongly dependent on one another. If a method were to attempt to optimize each variable independently, its performance would suffer significantly. When traditional optimization techniques are applied to high-dependence problems, they experience difficulty in finding the global optimum. To address this problem, this paper proposes a novel metaheuristic Algorithm, the entanglement-enhanced quantum-inspired Tabu Search Algorithm (Entanglement-QTS), which is based on the quantum-inspired Tabu Search (QTS) Algorithm and the feature of quantum entanglement. Entanglement-QTS differs from other quantum-inspired evolutionary Algorithms in that its $Q$ -bits have entangled states, which can express a high degree of correlation, rendering the variables more intertwined. Entangled Q-bits represent a state-of-the-art idea that can significantly improve the treatment of multimodal and high-dependence problems. Entanglement-QTS can discover optimal solutions, balance diversification and intensification, escape numerous local optimal solutions by using the quantum not gate, reinforce the intensification effect by local Search and entanglement local Search, and manage strong-dependence problems and accelerate the optimization process by using entangled states. This paper uses nine benchmark functions to test the Search ability of the entanglement-QTS Algorithm. The results demonstrate that Entanglement-QTS outperforms QTS and other metaheuristic Algorithms in both its effectiveness at finding the global optimum and its computational efficiency.
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a quantum inspired Tabu Search Algorithm for solving combinatorial optimization problems
Soft Computing, 2014Co-Authors: Huapei Chiang, Yao-hsin Chou, Chiahui Chiu, Shuyu Kuo, Yuehmin HuangAbstract:In this study, we propose a novel quantum-inspired evolutionary Algorithm (QEA), called quantum inspired Tabu Search (QTS). QTS is based on the classical Tabu Search and characteristics of quantum computation, such as superposition. The process of qubit measurement is a probability operation that increases diversification; a quantum rotation gate used to Searching toward attractive regions will increase intensification. This paper will show how to implement QTS into NP-complete problems such as 0/1 knapsack problems, multiple knapsack problems and the traveling salesman problem. These problems are important to computer science, cryptography and network security. Furthermore, our experimental results on 0/1 knapsack problems are compared with those of other heuristic Algorithms, such as a conventional genetic Algorithm, a Tabu Search Algorithm and the original QEA. The final outcomes show that QTS performs much better than other heuristic Algorithms without premature convergence and with more efficiency. Also on multiple knapsack problems and the traveling salesman problem QTS verify its effectiveness.
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A Rule-Based Dynamic Decision-Making Stock Trading System Based on Quantum-Inspired Tabu Search Algorithm
IEEE Access, 2014Co-Authors: Yao-hsin Chou, Chi-yuan Chen, Han-chieh ChaoAbstract:Heuristic methods or evolutionary Algorithms (such as genetic Algorithms and genetic programs) are common approaches applied in financial applications, such as trading systems. Determining the best time to buy or sell stocks in a stock market, and thereby maximizing profit with low risks, is an important issue in financial reSearch. Recent studies have used trading rules based on technique analysis to address this problem. This method can determine trading times by analyzing the value of technical indicators. In other words, we can make trading rules by finding the trading value of technique indicators. An example of a trading rule would be, if one technical indicator's value achieves the setting value, then either buy or sell. A combination of trading rules would become a trading strategy. The process of making trading strategies can be formulated as a combinational optimization problem. In this paper, we propose a novel method for applying a trading system. First, the proposed method uses the quantum-inspired Tabu Search Algorithm to find the optimal composition and combination of trading strategies. Second, this method uses a sliding window to avoid the major problem of over-fitting. The experiment results of earning money show much better performance than other approaches, and the proposed method outperforms the buy and hold method (which is a benchmark in this field).
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Improved Quantum-Inspired Tabu Search Algorithm for Solving Function Optimization Problem
2013 IEEE International Conference on Systems Man and Cybernetics, 2013Co-Authors: Yi-jyuan Yang, Yao-hsin ChouAbstract:After we read the paper about quantum-inspired Tabu Search Algorithm (QTS) for solving 0/1 knapsack problems [5], we got many ideas. In this study, we proposed a method which is called improved quantum-inspired Tabu Search Algorithm (IMQTS). In IMQTS, we add two skills in QTS. First, we add the probability of taking a worse solution become the guide of updating the populations. Second, we add a second rotation which is turning possible solutions away from the worst solution. We use IMQTS for solving function optimization problem to show its performance. The experiment results show that IMQTS performs well in function optimization problem, and IMQTS would not fall into local optimum.
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quantum inspired Tabu Search Algorithm for reversible logic circuit synthesis
Systems Man and Cybernetics, 2012Co-Authors: Wenhsin Wang, Chiahui Chiu, Shuyu Kuo, Shengfei Huang, Yao-hsin ChouAbstract:Reversible logic plays an important role in quantum computation, which is a promising reSearch field. The reversible logic synthesis problem focuses on generating a reversible circuit automatically and finding the lowest cost when an output function is given. The synthesis of reversible logic circuits can be formulated as a combinatorial optimization problem. This paper proposes a new evolutionary Algorithm for synthesizing reversible circuits based on Quantum-Inspired Tabu Search Algorithm (QTS). The proposed Algorithm uses the QTS-based approach to find fewer gates and reduce the cost of reversible circuits. This method is simpler, has better performance in computational cost, and reduce the gate counts of reversible circuits. This paper also compares experimental results with other heuristic and evolutionary Algorithms. The final outcome shows that the QTS-based approach performs much better than other Algorithms.
Lu Chen - One of the best experts on this subject based on the ideXlab platform.
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a Tabu Search Algorithm for the relocation problem in a warehousing system
International Journal of Production Economics, 2011Co-Authors: Lu Chen, André Langevin, Diane RiopelAbstract:Abstract Relocation of items in a warehousing system is usually used when the handling machines become the bottleneck. This paper addresses the optimization problem of relocation in a warehouse with dynamic operating policy. An integer linear programming formulation is proposed. A two-stage heuristic method is developed to generate an initial solution. A Tabu Search Algorithm is proposed to improve the solution. Two relocation policies are studied and their performances are compared.
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the storage location assignment and interleaving problem in an automated storage retrieval system with shared storage
International Journal of Production Research, 2010Co-Authors: Lu Chen, André Langevin, Diane RiopelAbstract:Storage location assignment and interleaving policy are two closely related problems in warehousing management. This paper addresses the location assignment and interleaving problem at the same time in an automated storage/retrieval system with duration-of-stay based shared storage policy. Based on the heuristics for single command operation, a two-step procedure is developed to solve the problem. A Tabu Search Algorithm is proposed to improve the solution for medium and large sized problems. The computational results indicate that the Tabu Search Algorithm is effective in finding high quality solutions, and efficient in solving large sized problems.
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a Tabu Search Algorithm for the integrated scheduling problem of container handling systems in a maritime terminal
European Journal of Operational Research, 2007Co-Authors: Lu Chen, Nathalie Bostel, Pierre Dejax, Jianguo CaiAbstract:The scheduling problem in a container terminal is characterized by the coordination of different types of equipment. In this paper, we present an integrated model to schedule the equipment. The objective is to minimize the makespan, or the time it takes to serve a given set of ships. The problem is formulated as a Hybrid Flow Shop Scheduling problem with precedence and Blocking constraints (HFSS-B). A Tabu Search Algorithm is proposed to solve this problem. Certain mechanisms are developed and introduced into the Algorithm to assure its quality and efficiency. The performance of the Tabu Search Algorithm is analyzed from the computational point of view.
Gilbert Laporte - One of the best experts on this subject based on the ideXlab platform.
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designing an efficient method for tandem agv network design problem using Tabu Search
Applied Mathematics and Computation, 2006Co-Authors: Gilbert Laporte, Reza Zanjirani Farahani, Elnaz MiandoabchiAbstract:A tandem AGV configuration connects all cells of a manufacturing area by means of non-overlapping, single-vehicle closed loops. Each loop has at least one additional P/D station, provided as interface between adjacent loops. This study describes the development of a Tabu Search Algorithm for the design of tandem AGV systems. Starting from an initial partition generated by a k-means clustering method, the Tabu Search Algorithm partitions the stations into loops by minimizing the maximum workload of the system, without allowing the paths of loops to cross each other. The new Algorithm and the partitioning Algorithm presented by Bozer and Srinivasan are compared on, randomly generated problems. Results show that in large scale problems, the partitioning Algorithm often leads to infeasible configurations with crossed loops in spite of its shorter running time. However the newly developed Algorithm avoids infeasible configurations and often yields better objective function values.
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A Tabu Search Algorithm for a Routing and Container Loading Problem
Transportation Science, 2006Co-Authors: Michel Gendreau, Manuel Iori, Gilbert Laporte, Silvano MartelloAbstract:This article considers a combination of capacitated vehicle routing and three-dimensional loading, with additional constraints frequently encountered in freight transportation. It proposes a Tabu Search Algorithm that iteratively invokes an inner Tabu Search procedure for the solution of the loading subproblem. The Algorithm is experimentally evaluated both on instances adapted from vehicle routing instances from the literature and on new real-world instances.
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improved Tabu Search Algorithm for the handling of route duration constraints in vehicle routing problems with time windows
Journal of the Operational Research Society, 2004Co-Authors: Jeanfrancois Cordeau, Gilbert Laporte, Anne MercierAbstract:This note introduces a refinement to a previously proposed Tabu Search Algorithm for vehicle routing problems with time windows. This refinement yields new best known solutions on a set of benchmark instances of the multi-depot, the periodic and the site-dependent vehicle routing problems with time windows.
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a Tabu Search heuristic for the multi depot vehicle routing problem
Computers & Operations Research, 1996Co-Authors: Jacques Renaud, Gilbert Laporte, Fayez F BoctorAbstract:This article describes a Tabu Search Algorithm for the multi-depot vehicle routing problem with capacity and route length restrictions. The Algorithm is tested on a set of 23 benchmark instances. It is shown to outperform existing heuristics.
Peng Tian - One of the best experts on this subject based on the ideXlab platform.
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a multistart adaptive memory based Tabu Search Algorithm for the heterogeneous fixed fleet open vehicle routing problem
Expert Systems With Applications, 2012Co-Authors: Stephen C H Leung, Peng TianAbstract:This paper addressed the heterogeneous fixed fleet open vehicle routing problem (HFFOVRP), in which the demands of customers are fulfilled by a fleet of fixed number of vehicles with various capacities and related costs. Moreover, the vehicles start at the depot and terminate at one of the customers. This problem is an important variant of the classical vehicle routing problem and can cover more practical situations in transportation and logistics. We propose a multistart adaptive memory programming metaheuristic with modified Tabu Search Algorithm to solve this new vehicle routing problem. The Algorithmic efficiency and effectiveness are experimentally evaluated on a set of generated instances.
