A new grouping genetic algorithm for the quadratic multiple knapsack problem

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Date
2007-01-01
Authors
Singh, Alok
Baghel, Anurag Singh
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Abstract
The quadratic multiple knapsack problem is an extension of the well known 0/1 multiple knapsack problem. In the quadratic multiple knapsack problem, profit values are associated not only with individual objects but also with pairs of objects. Profit value associated with a pair of objects is added to the overall profit if both objects of the pair belong to the same knapsack. Being an extension of the 0/1 multiple knapsack problem, this problem is also NP-Hard. In this paper, we have proposed a new steady-state grouping genetic algorithm for the quadratic multiple knapsack problem and compared our results with two recently proposed methods - a genetic algorithm and a stochastic hill climber. The results show the effectiveness of our approach. © Springer-Verlag Berlin Heidelberg 2007.
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Keywords
Combinatorial optimization, Grouping genetic algorithm, Knapsack problem, Quadratic multiple knapsack problem
Citation
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). v.4446 LNCS