A closed-loop supply chain planning based on adaptive genetic algorithm

A closed-loop supply chain operation integrating forward and reverse supplies, productions and distributions are established here based on the control engineering theory, and the status equations and mathematical model of supply chain planning and operation with existed uncertainties are analyzed also. To integrate the uncertain forward and reverse supply chain planning information, a fuzzy adaptive planning strategy based on genetic algorithm is designed, where the information of demand, purchasing, recovery, inventory and production is fuzzy. The program uses fuzzy adaptive genetic algorithm to optimize fuzzy rule table, so planning parameters can be changed with the supply chain operation and be self-adjusted according to fuzzy rules to improve the static and dynamic performance characteristics of the system. Finally, a closed-loop operation case is analyzed for authentication.