Enhanced Hyper-Cube Framework Ant Colony Optimization for Combinatorial Optimization Problems
Solving of combinatorial optimization problems is a common practice in real-life engineering applications. Trusses, cranes, and composite laminated structures are some good examples that fall under this category of optimization problems. Those examples have a common feature of discrete design domain...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-09-01
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| Series: | Algorithms |
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| Online Access: | https://www.mdpi.com/1999-4893/14/10/286 |
| _version_ | 1797515571548389376 |
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| author | Ali Ahmid Thien-My Dao Ngan Van Le |
| author_facet | Ali Ahmid Thien-My Dao Ngan Van Le |
| author_sort | Ali Ahmid |
| collection | DOAJ |
| description | Solving of combinatorial optimization problems is a common practice in real-life engineering applications. Trusses, cranes, and composite laminated structures are some good examples that fall under this category of optimization problems. Those examples have a common feature of discrete design domain that turn them into a set of NP-hard optimization problems. Determining the right optimization algorithm for such problems is a precious point that tends to impact the overall cost of the design process. Furthermore, reinforcing the performance of a prospective optimization algorithm reduces the design cost. In the current study, a comprehensive assessment criterion has been developed to assess the performance of meta-heuristic (MH) solutions in the domain of structural design. Thereafter, the proposed criterion was employed to compare five different variants of Ant Colony Optimization (ACO). It was done by using a well-known structural optimization problem of laminate Stacking Sequence Design (SSD). The initial results of the comparison study reveal that the Hyper-Cube Framework (HCF) ACO variant outperforms the others. Consequently, an investigation of further improvement led to introducing an enhanced version of HCFACO (or EHCFACO). Eventually, the performance assessment of the EHCFACO variant showed that the average practical reliability became more than twice that of the standard ACO, and the normalized price decreased more to hold at 28.92 instead of 51.17. |
| first_indexed | 2024-03-10T06:47:17Z |
| format | Article |
| id | doaj.art-67fc7f880d4e4fa880ad239c14b41616 |
| institution | Directory Open Access Journal |
| issn | 1999-4893 |
| language | English |
| last_indexed | 2024-03-10T06:47:17Z |
| publishDate | 2021-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Algorithms |
| spelling | doaj.art-67fc7f880d4e4fa880ad239c14b416162023-11-22T17:08:21ZengMDPI AGAlgorithms1999-48932021-09-01141028610.3390/a14100286Enhanced Hyper-Cube Framework Ant Colony Optimization for Combinatorial Optimization ProblemsAli Ahmid0Thien-My Dao1Ngan Van Le2Independent Researcher, Montréal, QC H3C 1K3, CanadaMechanical Engineering Department, École de Technologie Supérieure ÉTS, Montréal, QC H3C 1K3, CanadaMechanical Engineering Department, École de Technologie Supérieure ÉTS, Montréal, QC H3C 1K3, CanadaSolving of combinatorial optimization problems is a common practice in real-life engineering applications. Trusses, cranes, and composite laminated structures are some good examples that fall under this category of optimization problems. Those examples have a common feature of discrete design domain that turn them into a set of NP-hard optimization problems. Determining the right optimization algorithm for such problems is a precious point that tends to impact the overall cost of the design process. Furthermore, reinforcing the performance of a prospective optimization algorithm reduces the design cost. In the current study, a comprehensive assessment criterion has been developed to assess the performance of meta-heuristic (MH) solutions in the domain of structural design. Thereafter, the proposed criterion was employed to compare five different variants of Ant Colony Optimization (ACO). It was done by using a well-known structural optimization problem of laminate Stacking Sequence Design (SSD). The initial results of the comparison study reveal that the Hyper-Cube Framework (HCF) ACO variant outperforms the others. Consequently, an investigation of further improvement led to introducing an enhanced version of HCFACO (or EHCFACO). Eventually, the performance assessment of the EHCFACO variant showed that the average practical reliability became more than twice that of the standard ACO, and the normalized price decreased more to hold at 28.92 instead of 51.17.https://www.mdpi.com/1999-4893/14/10/286combinatorial optimizationAnt Colony Optimization (ACO)buckling load factorcomposite laminate |
| spellingShingle | Ali Ahmid Thien-My Dao Ngan Van Le Enhanced Hyper-Cube Framework Ant Colony Optimization for Combinatorial Optimization Problems Algorithms combinatorial optimization Ant Colony Optimization (ACO) buckling load factor composite laminate |
| title | Enhanced Hyper-Cube Framework Ant Colony Optimization for Combinatorial Optimization Problems |
| title_full | Enhanced Hyper-Cube Framework Ant Colony Optimization for Combinatorial Optimization Problems |
| title_fullStr | Enhanced Hyper-Cube Framework Ant Colony Optimization for Combinatorial Optimization Problems |
| title_full_unstemmed | Enhanced Hyper-Cube Framework Ant Colony Optimization for Combinatorial Optimization Problems |
| title_short | Enhanced Hyper-Cube Framework Ant Colony Optimization for Combinatorial Optimization Problems |
| title_sort | enhanced hyper cube framework ant colony optimization for combinatorial optimization problems |
| topic | combinatorial optimization Ant Colony Optimization (ACO) buckling load factor composite laminate |
| url | https://www.mdpi.com/1999-4893/14/10/286 |
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