A Hybrid Dynamic Programming for Inventory Routing Problem in Collaborative Reverse Supply Chains

Abstract

Inventory routing problems arise as simultaneous decisions in inventory and routing optimization. In the present study, vendor managed inventory is proposed as a collaborative model for reverse supply chains and the optimization problem is modeled in terms of an inventory routing problem. The studied reverse supply chains include several return generators and recovery centers and one collection center. Since the mathematical model is an NP-hard one, finding the exact solution is time consuming and complex. A hybrid heuristic model combining dynamic programming, ant colony optimization and tabu search has been proposed to solve the problem. To confirm the performance of proposed model, solutions are compared with three previous researches. The comparison reveals that the method can significantly decrease costs and solution times. To determine the ant colony parameters, four factors and three levels are selected and the optimized values of parameters are defined by design of experiments.