A new grouping genetic algorithm for the quadratic multiple knapsack problem

dc.contributor.author Singh, Alok
dc.contributor.author Baghel, Anurag Singh
dc.date.accessioned 2022-03-27T06:07:57Z
dc.date.available 2022-03-27T06:07:57Z
dc.date.issued 2007-01-01
dc.description.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.
dc.identifier.citation Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). v.4446 LNCS
dc.identifier.issn 03029743
dc.identifier.uri 10.1007/978-3-540-71615-0_19
dc.identifier.uri http://link.springer.com/10.1007/978-3-540-71615-0_19
dc.identifier.uri https://dspace.uohyd.ac.in/handle/1/9403
dc.subject Combinatorial optimization
dc.subject Grouping genetic algorithm
dc.subject Knapsack problem
dc.subject Quadratic multiple knapsack problem
dc.title A new grouping genetic algorithm for the quadratic multiple knapsack problem
dc.type Book Series. Conference Paper
dspace.entity.type
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