A multi-population genetic algorithm for transportation scheduling

作者：Zegordi S H^*; Nia M A Beheshti

来源：Transportation Research Part E: Logistics and Transportation Review , 2009, 45(6): 946-959.

DOI：10.1016/j.tre.2009.05.002

• Scheduling
• Supply chain management
• Genetic algorithm
• Transportation
• Tardiness

This study considers the integration of production and transportation scheduling in a two-stage supply chain environment. The objective function minimizes the total tardiness and total deviations of assigned work loads of suppliers from their quotas. After modeling the problem as a mixed integer programming problem, a genetic algorithm with three populations, namely, a multi-society genetic algorithm (MSGA), is proposed for solving it. MSGA is compared with the optimum solutions for small problems and a heuristic and a random search approach for larger problems. Additionally, an MSGA is compared with a generic genetic algorithm. The experimental results show the superiority of the MSGA.

• 出版日期2009-11