Document Type : Research Paper


Department of Industrial Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamedan, Iran.



The inventory routing problem arises from the combination of the vehicle routing problem and the vendor-managed inventory problem. In this paper, we present a mathematical model and a novel genetic algorithm for solving the multi-period inventory routing problem. The objective is to supply products to scattered customers within a given time horizon while managing customer inventories to avoid shortages and minimize total inventory and transportation costs. To represent solutions for this problem, we introduce a new chromosomal structure. This structure offers simplicity in encoding and decoding solutions, maintains feasibility after crossover and mutation operations, addresses both routing and inventory management in a single step, and consolidates information about each solution method comprehensively. The algorithm parameters, including crossover and mutation rates, population size, number of iterations, and selection pressure, are fine-tuned using the Taguchi method. To assess algorithm efficiency, we utilize standard instances from the literature. Our results demonstrate that the proposed algorithm performs favorably compared to previous approaches.


Main Subjects

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