Supply chain network design represents a critical strategic decision that significantly impacts operational efficiency and cost competitiveness. This paper addresses the multi-facility supply chain network design problem (MFSCNDP) which determines optimal facility locations, capacity allocations, and material flows to minimize total system costs. We propose a mixed-integer linear programming (MILP) formulation that considers facility establishment costs, transportation costs, and operational costs while satisfying demand requirements and capacity constraints. To solve large-scale instances efficiently, we develop a hybrid metaheuristic algorithm combining genetic algorithm operators with local search procedures. Computational experiments on benchmark instances demonstrate the effectiveness of our approach, achieving optimal solutions for small-to-medium instances and high-quality solutions for large-scale problems within reasonable computational time. The proposed method provides decision-makers with an efficient tool for strategic supply chain network planning.