A genetic algorithm to solve the multidimensional knapsack problem
type: Item
instance of: scholarly article
title: A genetic algorithm to solve the multidimensional knapsack problem
zbMATH Open document ID: 1390.90460
author: Murat Ersen Berberler
author: Asli Guler
author: Urfat G. Nuriyev
published in: Mathematical \& Computational Applications
publication date: 2018-07-05T00:00:00Z
review text: Summary: 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.
Mathematics Subject Classification ID: 90C27
Mathematics Subject Classification ID: 90C59
zbMATH DE Number: 6898864
zbMATH Keywords: multidimensional knapsack problem
zbMATH Keywords: genetic algorithm
zbMATH Keywords: heuristic approach
zbMATH Keywords: evolutionary algorithms
MaRDI profile type: Publication
full work available at URL: mca18030486
OpenAlex ID: W2295545633
DOI: 10.3390/MCA18030486
description: scientific article; zbMATH DE number 6898864