Solution of structural and mathematical optimization problems using a new hybrid swarm intelligence optimization algorithm
•A new hybrid meta-heuristic optimization algorithm named as ISA (Interactive Search algorithm) is developed.•ISA combines integrated particle swarm optimization and teaching learning based optimization.•The novel algorithm (ISA) considers interaction with other particles besides the global and prev...
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| Published in: | Advances in engineering software (1992) Vol. 127; pp. 106 - 123 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
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Elsevier Ltd
01.01.2019
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| ISSN: | 0965-9978 |
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| Abstract | •A new hybrid meta-heuristic optimization algorithm named as ISA (Interactive Search algorithm) is developed.•ISA combines integrated particle swarm optimization and teaching learning based optimization.•The novel algorithm (ISA) considers interaction with other particles besides the global and previous best particles to enhance the search ability.
In this investigation a new optimization algorithm named as interactive search algorithm (ISA) is presented. This method is developed through modifying and hybridizing the affirmative features of recently developed integrated particle swarm optimization (iPSO) algorithm with the pairwise knowledge sharing mechanism of the teaching and learning based optimization (TLBO) method. Proposed ISA provides two different navigation schemes as Tracking and Interacting. Each agent based on its tendency factor can pick one of these two schemes for searching the domain. Additionally, ISA utilizes an improved fly-back technique to handle problem constraints. The proposed method is tested on a set of mathematical and structural optimization benchmark problems with discrete and continuous variables. Numerical results indicate that the new algorithm is competitive with other well-stablished metaheuristic algorithms. |
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| AbstractList | •A new hybrid meta-heuristic optimization algorithm named as ISA (Interactive Search algorithm) is developed.•ISA combines integrated particle swarm optimization and teaching learning based optimization.•The novel algorithm (ISA) considers interaction with other particles besides the global and previous best particles to enhance the search ability.
In this investigation a new optimization algorithm named as interactive search algorithm (ISA) is presented. This method is developed through modifying and hybridizing the affirmative features of recently developed integrated particle swarm optimization (iPSO) algorithm with the pairwise knowledge sharing mechanism of the teaching and learning based optimization (TLBO) method. Proposed ISA provides two different navigation schemes as Tracking and Interacting. Each agent based on its tendency factor can pick one of these two schemes for searching the domain. Additionally, ISA utilizes an improved fly-back technique to handle problem constraints. The proposed method is tested on a set of mathematical and structural optimization benchmark problems with discrete and continuous variables. Numerical results indicate that the new algorithm is competitive with other well-stablished metaheuristic algorithms. |
| Author | Moloodpoor, Mahsa Toğan, Vedat Mortazavi, Ali |
| Author_xml | – sequence: 1 givenname: Ali orcidid: 0000-0002-6089-7046 surname: Mortazavi fullname: Mortazavi, Ali email: ali.mortazavi.php@gmail.com organization: Civil Engineering Department, Usak University, Usak/Turkey – sequence: 2 givenname: Vedat orcidid: 0000-0001-8734-6300 surname: Toğan fullname: Toğan, Vedat email: togan@ktu.edu.tr organization: Civil Engineering Department, Karadeniz Technical University, 61080 Trabzon/Turkey – sequence: 3 givenname: Mahsa surname: Moloodpoor fullname: Moloodpoor, Mahsa organization: Mechanical Engineering Department, Ege University, Izmir/Turkey |
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| Keywords | Teaching and learning based optimization (TLBO) Integrated particle swarm optimization (iPSO) Hybrid optimization method |
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