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Feasibility-Guided Constraint-Handling Techniques for Engineering Optimization Problems
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作者 Muhammad Asif Jan Yasir Mahmood +6 位作者 Hidayat Ullah Khan Wali Khan Mashwani Muhammad Irfan Uddin Marwan Mahmoud Rashida Adeeb Khanum Ikramullah Noor Mast 《Computers, Materials & Continua》 SCIE EI 2021年第6期2845-2862,共18页
The particle swarm optimization(PSO)algorithm is an established nature-inspired population-based meta-heuristic that replicates the synchronizing movements of birds and sh.PSO is essentially an unconstrained algorithm... The particle swarm optimization(PSO)algorithm is an established nature-inspired population-based meta-heuristic that replicates the synchronizing movements of birds and sh.PSO is essentially an unconstrained algorithm and requires constraint handling techniques(CHTs)to solve constrained optimization problems(COPs).For this purpose,we integrate two CHTs,the superiority of feasibility(SF)and the violation constraint-handling(VCH),with a PSO.These CHTs distinguish feasible solutions from infeasible ones.Moreover,in SF,the selection of infeasible solutions is based on their degree of constraint violations,whereas in VCH,the number of constraint violations by an infeasible solution is of more importance.Therefore,a PSO is adapted for constrained optimization,yielding two constrained variants,denoted SF-PSO and VCH-PSO.Both SF-PSO and VCH-PSO are evaluated with respect to ve engineering problems:the Himmelblau’s nonlinear optimization,the welded beam design,the spring design,the pressure vessel design,and the three-bar truss design.The simulation results show that both algorithms are consistent in terms of their solutions to these problems,including their different available versions.Comparison of the SF-PSO and the VCHPSO with other existing algorithms on the tested problems shows that the proposed algorithms have lower computational cost in terms of the number of function evaluations used.We also report our disagreement with some unjust comparisons made by other researchers regarding the tested problems and their different variants. 展开更多
关键词 Constrained evolutionary optimization constraint handling techniques superiority of feasibility violation constraint-handling technique swarm based evolutionary algorithms particle swarm optimization engineering optimization proble
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