Paper Info
Title
Iterated greedy algorithms for the maximal covering location problem
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.
Year
DOI
Venue
2012
10.1007/978-3-642-29124-1_15
Lecture Notes in Computer Science
Keywords
Field
DocType
additional result,iterated greedy algorithm,covered client,location problem,new iterated greedy algorithm,considerable number,exact solver,improvement procedure,standalone exact solver,greedy constructive procedure
Iterated greedy,Population,Mathematical optimization,Heuristic,Computer science,Constructive,Algorithm,Greedy algorithm,Solver,Greedy randomized adaptive search procedure,Iterated greedy algorithm,Distributed computing
Conference
Citations 
PageRank 
References 
3
0.43
7
Authors
4
Name
Order
Citations
PageRank
Francisco J. Rodriguez115319.73
Christian Blum2128558.68
Manuel Lozano3136949.59
Carlos GarcíA-MartíNez452027.80