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  5. A new exact algorithm to solve the Multiple-Choice Multidimensional Knapsack Problem: The Utility Sorted Branch and Bound Algorithm
 
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2021
Erstveröffentlichung
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Verlagsversion

A new exact algorithm to solve the Multiple-Choice Multidimensional Knapsack Problem: The Utility Sorted Branch and Bound Algorithm

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Hauptpublikation
Kreß et al. (2021) A new exact algorithm to solve the Multiple-Choice Multidimensional Knapsack Problem.pdf
CC BY 4.0 International
Format: Adobe PDF
Size: 359.19 KB
TUDa URI
tuda/7375
URN
urn:nbn:de:tuda-tuprints-194043
DOI
10.26083/tuprints-00019404
Autor:innen
Kreß, Antonio ORCID 0000-0002-3614-444X
Kiel, Florian
Metternich, Joachim
Kurzbeschreibung (Abstract)

This paper offers an exact algorithm for one of the most complex members of the Knapsack Problem family: The Multiple-choice Multidimensional Knapsack Problem (MMKP). Based on a literature survey, only a few exact algorithms exist for the MMKP. The proposed algorithm excludes ranges of the possible solution space through systematic variations of ranked elements by utility sorting. Based on logical rules, successor nodes of a feasible node cannot include the optimal solution. Besides a literature survey as well as a detailed description of the algorithm and the test design, the results of a computational study on 11,160 instances are presented. The efficiency of the algorithm depends on the number of classes, elements per class, number of restrictions, and the degree of restrictiveness. Using the distribution of a search quotient shows the relative number of examined solutions being investigated. Testing against a brute-force algorithm reveals that all problem instances could be solved exactly while reducing the number of node enumerations. Furthermore, the structure of the algorithm allows its usage on other members of the knapsack problem family.

Sprache
Englisch
Fachbereich/-gebiet
16 Fachbereich Maschinenbau > Institut für Produktionsmanagement, Technologie und Werkzeugmaschinen (PTW)
16 Fachbereich Maschinenbau > Institut für Produktionsmanagement, Technologie und Werkzeugmaschinen (PTW) > CiP Center für industrielle Produktivität
DDC
500 Naturwissenschaften und Mathematik > 510 Mathematik
600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften und Maschinenbau
Institution
Universitäts- und Landesbibliothek Darmstadt
Ort
Darmstadt
PPN
486168034

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