On a Hybrid Genetic Algorithm for Solving the Container Loading Problem with no Orientation Constraints

This paper presents a new hybrid genetic algorithm for solving the container loading problem in the general case, precisely when the boxes have no orientation constraints. In order to improve the genetic algorithm efficiency, we developed a hybrid method, based on deterministic approaches combining...

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Bibliographic Details
Published inJournal of mathematical modelling and algorithms Vol. 12; no. 1; pp. 67 - 84
Main Authors Hasni, Hamadi, Sabri, Houssem
Format Journal Article
LanguageEnglish
Published Dordrecht Springer Netherlands 01.03.2013
Springer Nature B.V
Subjects
Algorithms
Boxes
Data Mining and Knowledge Discovery
Genetic algorithms
Heuristic
Integer programming
Management Science
Mathematical Modeling and Industrial Mathematics
Mathematical models
Mathematics
Mathematics and Statistics
Methods
Operations Research
Optimization
Packing problem
Problem solving
Studies
68T20
Genetic algorithm
Cuboïds packing
Container loading
Randomized heuristics
90C271
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ISSN1570-1166
2214-2487
1572-9214
2214-2495
DOI10.1007/s10852-012-9179-3

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Summary:This paper presents a new hybrid genetic algorithm for solving the container loading problem in the general case, precisely when the boxes have no orientation constraints. In order to improve the genetic algorithm efficiency, we developed a hybrid method, based on deterministic approaches combining the wall-building, level-slice approach and strip packing. A serie of experiments was achieved on 47 related benchmarks from the OR-Library. We could reach an average utilization of 94.47% and an average computation time of 840s on a 1.7 GHz core duo.
Bibliography:SourceType-Scholarly Journals-1
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ISSN:1570-1166
2214-2487
1572-9214
2214-2495
DOI:10.1007/s10852-012-9179-3