Improved two-grade delayed particle swarm optimisation (TGDPSO) for inventory facility location for perishable food distribution centres in Beijing.

Resolving inventory and location problems is the most important and fundamental tactical decision in the initial stages of developing a distribution network design. This is especially true for a logistics system dealing with perishable food. To minimise both the total inventory transportation cost of fresh agri-products and also waste in the supply chain, the evolution of the food supply chain structure is analysed and an inventory location allocation model is presented describing the real-life problem. The key issues are to describe food demand distribution and to determine the balance of transportation and inventory cost. To improve the quality of the solution, a local search is embedded in the two-grade delayed particle swarm optimisation. Experimental results demonstrate the algorithm can effectively resolve conflict between different costs and improve development decisions regarding Beijing's perishable food distribution centres. [ABSTRACT FROM AUTHOR]