Solving multiobjective, multiconstraint knapsack problems using mathematical programming and evolutionary algorithms

In this paper, we solve instances of the multiobjective multiconstraint (or multidimensional) knapsack problem (MOMCKP) from the literature, with three objective functions and three constraints. We use exact as well as approximate algorithms. The exact algorithm is a properly modified version of the...

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Veröffentlicht in:	European journal of operational research Jg. 203; H. 1; S. 14 - 21
Hauptverfasser:	Florios, Kostas, Mavrotas, George, Diakoulaki, Danae
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier B.V 16.05.2010 Elsevier Elsevier Sequoia S.A
Schriftenreihe:	European Journal of Operational Research
Schlagworte:	Applied sciences Approximation Branch & bound algorithms Branch and bound Branch and bound Knapsack problem Multiobjective Evolutionary algorithms Evolutionary algorithms Exact sciences and technology Flows in networks. Combinatorial problems Genetic algorithms Heuristic Knapsack problem Mathematical programming Multiobjective Operational research and scientific management Operational research. Management science Studies Multiobjective Evolutionary algorithms Branch and bound Knapsack problem Branching Adaptive algorithm Pareto optimum Multicriteria analysis Branch and bound method Evolutionary algorithm Multiobjective programming Parameter variation Coverage Adaptive method Genetic algorithm Heuristic method Metric Objective function Multidimensional system Metamodel Mathematical programming
ISSN:	0377-2217, 1872-6860
Online-Zugang:	Volltext
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