Iterated Greedy Algorithms for the Maximal Covering Location Problem
 Francisco J. Rodriguez,
 Christian Blum,
 Manuel Lozano,
 Carlos GarcíaMartínez
 … show all 4 hide
Abstract
The problem of allocating a set of facilities in order to maximise the sum of the demands of the covered clients is known as the maximal covering location problem. In this work we tackle this problem by means of iterated greedy algorithms. These algorithms iteratively refine a solution by partial destruction and reconstruction, using a greedy constructive procedure. Iterated greedy algorithms have been applied successfully to solve a considerable number of problems. With the aim of providing additional results and insights along this line of research, this paper proposes two new iterated greedy algorithms that incorporate two innovative components: a population of solutions optimised in parallel by the iterated greedy algorithm, and an improvement procedure that explores a large neighbourhood by means of an exact solver. The benefits of the proposal in comparison to a recently proposed decomposition heuristic and a standalone exact solver are experimentally shown.
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 Title
 Iterated Greedy Algorithms for the Maximal Covering Location Problem
 Book Title
 Evolutionary Computation in Combinatorial Optimization
 Book Subtitle
 12th European Conference, EvoCOP 2012, Málaga, Spain, April 1113, 2012. Proceedings
 Pages
 pp 172181
 Copyright
 2012
 DOI
 10.1007/9783642291241_15
 Print ISBN
 9783642291234
 Online ISBN
 9783642291241
 Series Title
 Lecture Notes in Computer Science
 Series Volume
 7245
 Series ISSN
 03029743
 Publisher
 Springer Berlin Heidelberg
 Copyright Holder
 SpringerVerlag Berlin Heidelberg
 Additional Links
 Topics
 Keywords

 iterated greedy algorithm
 large neighbourhood search
 maximal covering location problem
 Industry Sectors
 eBook Packages
 Editors

 JinKao Hao ^{(16)}
 Martin Middendorf ^{(17)}
 Editor Affiliations

 16. Faculty of Angers, University of Angers
 17. Department of Computer Science, University of Leipzig
 Authors

 Francisco J. Rodriguez ^{(18)}
 Christian Blum ^{(19)}
 Manuel Lozano ^{(18)}
 Carlos GarcíaMartínez ^{(20)}
 Author Affiliations

 18. Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain
 19. ALBCOM Research Group, Technical University of Catalonia, Barcelona, Spain
 20. Department of Computing and Numerical Analysis, University of Córdoba, Córdoba, Spain
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