Supplier Selection and Order Allocation Considering Discount Using Meta-Heuristics

In this paper, a multi-objective mathematical model is presented to select suppliers and allocate orders to suppliers under uncertainty conditions. The proposed model is multi-source, multi-customer, multi-product, and multi-period at two levels of supply chain. Objective functions considered in this study are total cost including purchasing, transportation and ordering costs, timely delivering, shipment quality, partial and general coverage of suppliers, and finally, suppliers’ weights. The major limitations are price discount on products provided by suppliers which are calculated using signal function. In addition, suppliers’ weights in the fifth objective function are calculated using fuzzy TOPSIS technique. Lateness and wastes parameters in this model are considered as uncertain and random triangular fuzzy numbers. Finally, the multi-objective model is solved using two well-known multi-objective algorithms that are Non-dominated Sorting Genetic Algorithm (NSGA-II) and Particle Swarm Optimization (PSO); the results are analyzed using quantitative criteria. Furthermore, Taguchi technique is used to regulate the parameters of two algorithms.

Keywords:

Allocation of order to Supplier , Supplier selection , Fuzzy TOPSIS , Signal function discount , Non dominated sorting genetic algorithm , Multi objective particle swarm optimization