A GRASP heuristic with Path-Relinking for a bi-objective p-median problem

Arroyo, José Elias Claudio; Soares, Michele dos Santos; Santos, Paula M. dos

doi:10.1109/his.2010.5600091

Cited by 3 publications

(3 citation statements)

References 32 publications

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“…Recently, considering the real-world conditions, various models of p-median problems are proposed in the literature, including stochastic p-median problems, progressive p-median problems [3], dynamic p-median problems, and bi-objective p-median problems [9].…”

Section: P-median Problemsmentioning

confidence: 99%

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A Multi-objective Evolutionary Approach for Cloud Service Provider Selection Problems with Dynamic Demands

Chen

Lin

Chen

2014

Applications of Evolutionary Computation

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Abstract. This paper describes a multi-objective evolutionary approach for solving cloud computing service provider selection problems with dynamic demands. In this investigated problem, not only the service purchase costs and transmission costs of service providers are different, but the demands of service requests also change over the given periods. The objective of this problem is to select a number of cloud service provider while optimizing the total service distance, the total number of serviced demand points, the total service purchase costs, and total transmission costs simultaneously in the given continuous time periods. A multi-objective genetic approach with a seeding mechanism is proposed to solve the investigated problems. Four trail benchmark problems are designed and solved using the proposed multi-objective evolutionary algorithm. The results indicate that the proposed approach is capable of obtaining a number of non-dominated solutions for decision makers.

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Section: P-median Problemsmentioning

confidence: 99%

“…P-median problem is prominent combinatorial optimization NP-hard problem in location science and cluster analysis [3][4][5][6][7][8][9]. Many exact and heuristic approaches have been proposed for solving p-median problems [3][8] [9].…”

Section: Introductionmentioning

confidence: 99%

A Multi-objective Evolutionary Approach for Cloud Service Provider Selection Problems with Dynamic Demands

Chen

Lin

Chen

2014

Applications of Evolutionary Computation

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“…In addition to the successful use of GRASP to solve singleobjective problems, it has also been successfully applied to approximate the efficient Pareto front of different multiobjective optimization problems [63][64][65][66][67][68]. The previous cited references adapted specific components of GRASP to the corresponding problems under study.…”

Section: Description Of the Proposed Biobjective Graspmentioning

confidence: 99%

Optimizing a Biobjective Production‐Distribution Planning Problem Using a GRASP

et al. 2018

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This paper addresses a biobjective production-distribution planning problem. The problem is formulated as a mixed integer programming problem with two objectives. The objectives are to minimize the total costs and to balance the total workload of the supply chain, which consist of plants and depots, considering that it represents a company vertically integrated. In order to solve the model, we propose an adapted biobjective GRASP to obtain an approximation of the Pareto front. To evaluate the performance of the proposed algorithm, numerical experimentations are conducted over a set of instances used for similar problems. Results indicate that the proposed GRASP obtains a relatively small number of nondominated solutions for each tested instance in very short computational time. The approximated Pareto fronts are discontinuous and nonconvex. Moreover, the solutions clearly show the compromise between both objective functions.

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Multi-objective evolutionary optimization of dynamic service facility location problems

Chen

Cheng

2011

2011 Proceedings of IEEE Southeastcon

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A GRASP heuristic with Path-Relinking for a bi-objective p-median problem

Cited by 3 publications

References 32 publications

A Multi-objective Evolutionary Approach for Cloud Service Provider Selection Problems with Dynamic Demands

A Multi-objective Evolutionary Approach for Cloud Service Provider Selection Problems with Dynamic Demands

Optimizing a Biobjective Production‐Distribution Planning Problem Using a GRASP

Multi-objective evolutionary optimization of dynamic service facility location problems

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