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Math. Comput. Appl. 2013, 18(3), 486-494; doi:10.3390/mca18030486

A Genetic Algorithm to Solve the Multidimensional Knapsack Problem

1
Department of Computer Science, Dokuz Eylul University, Izmir, Turkey
2
Department of Mathematics, Yasar University, Izmir, Turkey
3
Department of Mathematics, Ege University, Izmir, Turkey
*
Author to whom correspondence should be addressed.
Published: 1 December 2013
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Abstract

In this paper, The Multidimensional Knapsack Problem (MKP) which occurs in many different applications is studied and a genetic algorithm to solve the MKP is proposed. Unlike the technique of the classical genetic algorithm, initial population is not randomly generated in the proposed algorithm, thus the solution space is scanned more efficiently. Moreover, the algorithm is written in C programming language and is tested on randomly generated instances. It is seen that the algorithm yields optimal solutions for all instances.
Keywords: Multidimensional Knapsack Problem; Genetic Algorithm; Heuristic Approach; Evolutionary Algorithms Multidimensional Knapsack Problem; Genetic Algorithm; Heuristic Approach; Evolutionary Algorithms
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Berberler, M.E.; Guler, A.; Nurıyev, U.G. A Genetic Algorithm to Solve the Multidimensional Knapsack Problem. Math. Comput. Appl. 2013, 18, 486-494.

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