Multi-Objective Genetic Local Search Algorithm for Supply Chain Simulation Optimisation

This paper presents a hybrid simulation optimisation algorithm that integrates a multi-objective genetic algorithm and response surface-based metamodelling techniques. The optimisation problem involves a search in a high dimensional space with different ranges for decision variable scales, multiple stochastic objective functions and problem specific constraints. A case study demonstrates the application of a hybrid simulation optimisation algorithm to optimal cyclic planning for a generic supply chain network