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A Review and Comparison of Genetic Algorithms for the 0-1 Multidimensional Knapsack Problem

  • The 0-1 multidimensional knapsack problem (MKP) is a well-known combinatorial optimization problem with several real-life applications, for example, in project selection. Genetic algorithms (GA) are effective heuristics for solving the 0-1 MKP. Multiple individual GAs with specific characteristics have been proposed in literature. However, so far, these approaches have only been partially compared in multiple studies with unequal conditions. Therefore, to identify the “best” genetic algorithm, this article reviews and compares 11 existing GAs. The authors' tests provide detailed information on the GAs themselves as well as their performance. The authors validated fitness values and required computation times in varying problem types and environments. Results demonstrate the superiority of one GA.

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Metadaten
Author:Bernhard LienlandORCiDGND, Li Zeng
DOI:https://doi.org/10.4018/ijoris.2015040102
ISSN:1947-9328
Parent Title (English):International Journal of Operations Research and Information Systems (IJORIS)
Publisher:IGI Global
Document Type:Article
Language:English
Year of first Publication:2015
Release Date:2023/12/07
Volume:6
Issue:2
Pagenumber:11
Institutes:Fakultät Betriebswirtschaft
Publication:Externe Publikationen
OpenAccess Publikationsweg:Gold Open Access- Erstveröffentlichung in einem/als Open-Access-Medium
research focus:Produktion und Systeme
Licence (German):Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG