PENALTY-FREE METHOD FOR MULTI-CONSTRAINED OPTIMIZATION PROBLEMS BASED ON PARALLEL SIMULATED ANNEALING

摘要

A method is presented for addressing constraints within the context of large-scale combinatorial optimization problems. The method, based on constraint annealing, eliminates the use of traditional constraint penalty factors by treating each constraint as separate and concurrently solved minimization problems within a global optimization search framework. Results are demonstrated for a core loading pattern optimization problem.