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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| Published in | Journal of mathematical modelling and algorithms Vol. 12; no. 1; pp. 67 - 84 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Dordrecht
Springer Netherlands
01.03.2013
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1570-1166 2214-2487 1572-9214 2214-2495 |
| DOI | 10.1007/s10852-012-9179-3 |
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| Abstract | 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. |
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| AbstractList | 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. 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 series 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. [PUBLICATION ABSTRACT] |
| Author | Hasni, Hamadi Sabri, Houssem |
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| DOI | 10.1007/s10852-012-9179-3 |
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| Keywords | 68T20 Genetic algorithm Cuboïds packing Container loading Randomized heuristics 90C271 |
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| SubjectTerms | 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 |
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| Title | On a Hybrid Genetic Algorithm for Solving the Container Loading Problem with no Orientation Constraints |
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