|
|||||
|
|
Ant colony approaches for multiobjective structural optimization problems with a cardinality constraint |
|
| Affiliation: | 1. Laboratório Nacional de Computação Científica, Petrópolis, RJ, Brazil;2. Universidade Federal de Juiz de Fora, Juiz de Fora, MG, Brazil;1. Middle East Technical University, Dept. of Civil Eng., Ankara, Turkey;2. Atilim University, Department of Civil Engineering, Ankara, Turkey;1. Department of Civil Engineering, Dicle University, 21280 Diyarbakır, Turkey;2. Dipartimento di Meccanica, Matematica e Management, Politecnico di Bari, 70125 Bari, Italy;1. Department of Computational Engineering, Vietnamese-German University, Viet Nam;2. Department of Infrastructure Engineering, The University of Melbourne, Parkville, VIC 3010, Australia;3. CIRTeh Institute, Ho Chi Minh City University of Technology (HUTECH), Ho Chi Minh City, Viet Nam;4. Department of Architectural Engineering, Sejong University, 209 Neungdong-ro, Gwangjin-gu, Seoul 05006, Republic of Korea;1. Dipartimento di Meccanica, Matematica e Management, Politecnico di Bari, Bari 70125, Italy;2. Department of Civil Engineering, Dicle University, 21280 Diyarbakır, Turkey |
| Abstract: | Two Ant Colony Optimization algorithms are proposed to tackle multiobjective structural optimization problems with an additional constraint. A cardinality constraint is introduced in order to limit the number of distinct values of the design variables appearing in any candidate solution. Such constraint is directly enforced when an ant builds a candidate solution, while the other mechanical constraints are handled by means of an adaptive penalty method (APM). The test-problems are composed by structural optimization problems with discrete design variables, and the objectives are to minimize both the structure’s weight and its maximum nodal displacement. The Pareto sets generated in the computational experiments are evaluated by means of performance metrics, and the obtained designs are also compared with solutions available from single-objective studies in the literature. |
| Keywords: | Structural optimization Cardinality constraint Multiobjective optimization Ant colony algorithm Adaptive penalty Multicriteria tournament decision |
| 本文献已被 ScienceDirect 等数据库收录！ | |