Distribution Center Location Based on Genetic Algorithm

<p>Source code and result data for Problem A (Supply Chain Network Establishment and Road Disruption) from the 2013 Northwestern Polytechnical University "Zhenghe Cup" Mathematical Modeling Competition. Our team employed a genetic algorithm-based distribution center location approach that features chromosome representation of potential locations, fitness evaluation based on transportation costs and network resilience, and genetic operators including tournament selection and uniform crossover. The algorithm efficiently determines optimal distribution center placements by evolving candidate solutions through multiple generations, incorporating constraints for road disruption scenarios. Through research on supply chain network establishment and road disruption challenges, we achieved significant results in optimizing network operational efficiency. The implementation successfully solves supply chain network establishment problems under road disruption conditions, providing valuable references for related research and applications. Our source code, which includes modules for population initialization, fitness calculation, and genetic operations, along with comprehensive result data, offers practical resources for other researchers and practitioners to contribute to advancements in this field.</p>