A hybrid particle swarm optimization approach for design of agri-food supply chain network

Optimization of agri-food supply chain network (ASCN) is critical to reduce the sum of production cost and transportation cost. A mixed integer programming (MIP) model is presented to handle facility location and production capacity selection as well as choice of transportation mode for ASCN design (ASCND) problem. Due to the complexity of the optimization problem, a hybrid particle swarm optimization (PSO) approach is proposed. To facilitate finding optimal binary decision variables, a reduced variable neighborhood local search is embedded into PSO to enhance the explorability. Given binary variables, LINGO is adapted to solve the linear programming problem derived from the MIP. Case study illustrates the effectiveness of the proposed hybrid PSO approach. The computational results of case study show that hybrid PSO is superior to original binary PSO for ASCND problem.