A Decomposition Heuristic for the Maximal Covering Location Problem

This paper proposes a cluster partitioning technique to calculate improved upper bounds to the optimal solution of maximal covering location problems. Given a covering distance, a graph is built considering as vertices the potential facility locations, and with an edge connecting each pair of facili...

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Bibliographic Details
Published in:Advances in Operations Research Vol. 2010; no. 2010; pp. 2 - 13
Main Authors: Senne, Edson Luiz França, Pereira, Marcos Antonio, Lorena, Luiz Antonio Nogueira
Format: Journal Article
Language:English
Published: Cairo, Egypt Hindawi Limiteds 01.01.2010
Hindawi Puplishing Corporation
Hindawi Publishing Corporation
John Wiley & Sons, Inc
Subjects:
Algorithms
Applied mathematics
Clusters
Covering
Decomposition
Emergency services
Graphs
Heuristic
Joining
Lagrangian functions
Linear programming
Location problems (Programming)
Mathematical analysis
Operations research
Optimization
Partitions (Mathematics)
Position (location)
Programming (Mathematics)
Studies
الخوارزميات
بحوث العمليات
ISSN:1687-9147, 1687-9155
Online Access:Get full text
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Summary:This paper proposes a cluster partitioning technique to calculate improved upper bounds to the optimal solution of maximal covering location problems. Given a covering distance, a graph is built considering as vertices the potential facility locations, and with an edge connecting each pair of facilities that attend a same client. Coupling constraints, corresponding to some edges of this graph, are identified and relaxed in the Lagrangean way, resulting in disconnected subgraphs representing smaller subproblems that are computationally easier to solve by exact methods. The proposed technique is compared to the classical approach, using real data and instances from the available literature.
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ISSN:1687-9147
1687-9155
DOI:10.1155/2010/120756