A multi-objective bi-level location planning problem for stone industrial parks

摘要: This paper focuses on a stone industrial park location problem with hierarchical structure consisting of local government and several enterprises under random environment. In contrast to previous studies, conflicts between the authority are considered. The government, being leader in hierarchy, aims minimize both total pollution emissions development operating costs. enterprises, as followers only aim addition, unit production cost transportation considered variables. complicated multi-objective bi-level optimization poses challenges, including randomness, two-level decision making, conflicting objectives, difficulty searching for optimal solutions. Various approaches employed tackle these challenges. order make model trackable, expected value operator is used deal variables objective functions chance constraint-checking method such constraints. solved using interactive based satisfactory solution Adaptive Chaotic Particle Swarm Optimization (ACPSO). Finally, case study conducted demonstrate practicality efficiency proposed algorithm. performance ACPSO algorithm was highlighted by comparing single-level basic PSO GA algorithms.