Multi-objective meta-heuristic approach supported by an improved local search strategy for the design and planning of supply chain networks

This paper explores alternative strategies for the Local Search mechanism of a Bi- Objective Simulated Annealing Algorithm. The algorithm is adapted to the planning and design of supply chain networks, where the Pareto Frontier approximations generated are compared with those based on an exact approach. Several strategies are proposed to improve the algorithm performance, which are exemplified through the solution of an example. The robustness and versatility of the proposed method is illustrated where a sensitivity analysis on two parameters of the model is performed: Final Product Demand and Facility Capacity.