Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Tabu Search
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
A Bionomic Approach to the Capacitated p-Median Problem
Journal of Heuristics
Using Experimental Design to Find Effective Parameter Settings for Heuristics
Journal of Heuristics
A Taxonomy of Hybrid Metaheuristics
Journal of Heuristics
Introduction to Evolutionary Computing
Introduction to Evolutionary Computing
A column generation approach to capacitated p-median problems
Computers and Operations Research
Genetic subgradient method for solving location-allocation problems
Applied Soft Computing
Fine-Tuning of Algorithms Using Fractional Experimental Designs and Local Search
Operations Research
Optimal switch location in mobile communication networks using hybrid genetic algorithms
Applied Soft Computing
Computers and Industrial Engineering
Clustering search algorithm for the capacitated centered clustering problem
Computers and Operations Research
Matheuristics: Optimization, Simulation and Control
HM '09 Proceedings of the 6th International Workshop on Hybrid Metaheuristics
Metaheuristics: From Design to Implementation
Metaheuristics: From Design to Implementation
Tuning the performance of the MMAS heuristic
SLS'07 Proceedings of the 2007 international conference on Engineering stochastic local search algorithms: designing, implementing and analyzing effective heuristics
Computers & Mathematics with Applications
Soft-computing based heuristics for location on networks: The p-median problem
Applied Soft Computing
Hybrid metaheuristics in combinatorial optimization: A survey
Applied Soft Computing
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The capacitated p-median problem (CPMP) seeks to obtain the optimal location of p medians considering distances and capacities for the services to be given by each median. This paper presents an efficient hybrid metaheuristic algorithm by combining a proposed cutting-plane neighborhood structure and a tabu search metaheuristic for the CPMP. In the proposed neighborhood structure to move from the current solution to a neighbor solution, an open median is selected and closed. Then, a linear programming (LP) model is generated by relaxing binary constraints and adding new constraints. The generated LP solution is improved using cutting-plane inequalities. The solution of this strong LP is considered as a new neighbor solution. In order to select an open median to be closed, several strategies are proposed. The neighborhood structure is combined with a tabu search algorithm in the proposed approach. The parameters of the proposed hybrid algorithm are tuned using design of experiments approach. The proposed algorithm is tested on several sets of benchmark instances. The statistical analysis shows efficiency and effectiveness of the hybrid algorithm in comparison with the best approach found in the literature.