A Dynamic Programming-Based Genetic Algorithm for a Joint Pricing Construction Materials Procurement Problem with Uncertainties

摘要

In this paper, a dynamic programming model is proposed for a joint pricing construction materials procurement problem with multiple suppliers (JPCMPPMS) in a fuzzy random environment. In this model, the objective of the leader is to minimize total costs by deciding the purchase quantity. Demand and transport price are assumed to be fuzzy random variables in this paper. A dynamic programmingbased genetic algorithm (DP-based GA) is developed to find feasible solutions and a dynamic programming-based initialization, crossover and mutation are designed to avoid infeasible solutions. The model and the proposed solution procedure are very practical and effective, and raw material purchasing system will achieve the overall best economic interests.