Optimizing the distribution of shopping centers with parallel genetic algorithm

This study optimizes the distribution of shopping centers (SCs) to satisfy vendors and shoppers in terms of realizing the shortest car-based shopping trips in an urban area. First, modal split between car and transit is estimated, and then the interaction between land-use and transportation in the context of choice of shopping destinations is modeled to build an optimal function. Second, parallel genetic algorithm (PGA) is used to solve the optimal problem and several problems in application of GA are discussed. Finally, a case study which examines the effectiveness of the method, is carried out.