A Heuristic for Solving the Maximum Dispersion Problem
Mahdi Moeini () and
Oliver Wendt ()
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Mahdi Moeini: Technical University of Kaiserslautern
Oliver Wendt: Technical University of Kaiserslautern
A chapter in Operations Research Proceedings 2016, 2018, pp 405-410 from Springer
Abstract:
Abstract In this paper, we investigate solving the Maximum Dispersion Problem (MaxDP). For a given set of weighted objects, the MaxDP consists in partitioning this set into a predefined number of groups, such that the overall dispersion of elements, assigned to the same group, is maximized. Furthermore, each group has a target weight and the total weight of each group must be within a specific interval around the target weight. It has been proven that the MaxDP is NP-hard and, consequently, difficult to solve by classical exact methods. In this work, we use variants of Variable Neighborhood Search (VNS) for solving the MaxDP. In order to evaluate the efficiency of VNS, we carried out some numerical experiments on randomly generated instances. The results of the VNS is compared with the solutions provided by the solver Gurobi. According to our results, the VNS gives high quality solutions for small instances and, in solving large instances, it provides some decent solutions for all instances; however, Gurobi fails to provide any solution for some of them.
Keywords: Maximum Dispersion Problem (MaxDP); Variable Neighborhood Search (VNS); Solver Gurobi; Target Weight; High Quality Solutions (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:spr:oprchp:978-3-319-55702-1_54
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DOI: 10.1007/978-3-319-55702-1_54
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