Adaptive perturbed neighbourhood search for the expanding capacity multiple-choice knapsack problem

In this paper, we develop a perturbed reactive-based neighbourhood search algorithm for the expanding constraint multiple-choice knapsack problem. It combines reactive tabu search with some specific neighbourhood search strategies to approximately solve the problem. The tests were conducted on rando...

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Bibliographic Details
Published inThe Journal of the Operational Research Society Vol. 64; no. 10; pp. 1461 - 1473
Main Author Sbihi, A
Format Journal Article
LanguageEnglish
Published London Taylor & Francis 01.10.2013
Palgrave Macmillan
Palgrave Macmillan UK
Taylor & Francis Ltd
Subjects
Algorithms
Business and Management
Capital budgeting
combinatorial optimization
Dynamic programming
expanding
General Paper
General Papers
Heuristic
Heuristics
integer programming
Iterative solutions
knapsack
Knapsack problem
Management
metaheuristics
multiple-choice
Neighborhoods
Objective functions
Operations research
Operations Research/Decision Theory
Optimal solutions
Search strategies
Studies
Taboos
Tabu search
combinatorial optimization
expanding
knapsack
metaheuristics
integer programming
multiple-choice
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Summary:In this paper, we develop a perturbed reactive-based neighbourhood search algorithm for the expanding constraint multiple-choice knapsack problem. It combines reactive tabu search with some specific neighbourhood search strategies to approximately solve the problem. The tests were conducted on randomly generated instances and executed in comparable benchmark scenarios to those of the literature. The results outperform those of the Cplex solver and demonstrate the high quality of the two approach versions.
ISSN:0160-5682
1476-9360
DOI:10.1057/jors.2012.130