A simple and effective metaheuristic for the Minimum Latency Problem

Marcos Melo Silva, Anand Subramanian, Thibaut Vidal and Luiz Satoru Ochi

European Journal of Operational Research, 2012, vol. 221, issue 3, 513-520

Abstract: The Minimum Latency Problem (MLP) is a variant of the Traveling Salesman Problem which aims to minimize the sum of arrival times at vertices. The problem arises in a number of practical applications such as logistics for relief supply, scheduling and data retrieval in computer networks. This paper introduces a simple metaheuristic for the MLP, based on a greedy randomized approach for solution construction and iterated variable neighborhood descent with random neighborhood ordering for solution improvement. Extensive computational experiments on nine sets of benchmark instances involving up to 1000 customers demonstrate the good performance of the method, which yields solutions of higher quality in less computational time when compared to the current best approaches from the literature. Optimal solutions, known for problems with up to 50 customers, are also systematically obtained in a fraction of seconds.

Keywords: Metaheuristics; Minimum Latency Problem; GRASP; Iterated Local Search (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (27)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:221:y:2012:i:3:p:513-520

DOI: 10.1016/j.ejor.2012.03.044

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