Incorporating sales and marketing considerations into a competitive multi-echelon distribution network design problem with pricing strategy in a stochastic environment

This paper presents a multi-echelon distribution network design problem with pricing strategy in a stochastic environment, where location, inventory, and pricing decisions in retail and wholesale channels are made simultaneously. The considered network is comprised of a central warehouse, a set of distribution centers, and a set of retailers and wholesalers. The objective of the problem is to maximize the supply chain profit. The decisions include the location of distribution centers and the allocation of retailers and wholesalers to them, order-size for each distribution center and product price at retail and wholesale channels for different payment conditions. A mixed-integer nonlinear mathematical model was formulated and solved using the Lagrangian relaxation method and a Genetic algorithm. Computational results indicate that Lagrangian relaxation algorithm has good performance in terms of objective function value and runtime, even in large sized problems.