Integrated loading and distribution scheduling of high consumption oil products from distributed warehouses

In this research, we study the scheduling of loading and distribution for high consumption oil products while distributed warehouses are assumed. The high consumption of oil products requires direct shipment of orders issued by different customers in different geographical locations. The integrated nonlinear model is proposed to minimize the total cost of the supply chain including purchasing cost, loading, transportation, and late delivery costs. Because of the NP-hard nature of the problem, we proposed a new simulation based algorithm utilizing meta-heuristic algorithms. Then, we conducted several experiments to evaluate the efficiency proposed solution approach. Moreover, we evaluated the performance of the latest versions of genetic algorithm (GA-MPC) and particles swarm optimization (SPSO 2011) as well as the traditional versions within the proposed algorithm to solve the real-world scale problems. The results illustrate the better performance of genetic algorithm for large-scale problems.