Paper Info
Title
A hybrid method for the Probabilistic Maximal Covering Location-Allocation Problem
Abstract
This paper presents a hybrid algorithm that combines a metaheuristic and an exact method to solve the Probabilistic Maximal Covering Location-Allocation Problem. A linear programming formulation for the problem presents variables that can be partitioned into location and allocation decisions. This model is solved to optimality for small- and medium-size instances. To tackle larger instances, a flexible adaptive large neighborhood search heuristic was developed to obtain location solutions, whereas the allocation subproblems are solved to optimality. An improvement procedure based on an integer programming method is also applied. Extensive computational experiments on benchmark instances from the literature confirm the efficiency of the proposed method. The exact approach found new best solutions for 19 instances, proving the optimality for 18 of them. The hybrid method performed consistently, finding the best known solutions for 94.5% of the instances and 17 new best solutions (15 of them optimal) for a larger dataset in one-third of the time of a state-of-the-art solver.
Year
DOI
Venue
2015
10.1016/j.cor.2014.12.001
Computers and Operations Research
Keywords
DocType
Volume
Facility location,Congested systems,Hybrid algorithm,Adaptive large neighborhood search,Exact method,Queueing maximal covering location–allocation model,PMCLAP
Journal
57
Issue
ISSN
Citations 
C
0305-0548
9
PageRank 
References 
Authors
0.52
12
4
Name
Order
Citations
PageRank
Marcos A. Pereira1251.48
Leandro C. Coelho230616.97
Luiz Antonio Nogueira Lorena349836.72
Ligia C. de Souza490.52