Periodic product distribution from multi-depots under limited supplies

Abstract

Physical distribution is one of the key functions in logistics systems, involving the flow of products from manufacturing plants or distribution centers through the transportation network to consumers. It is a very costly function, especially for the distribution industries. While maintaining the desired customer service levels, an effort is made in this paper to improve distribution strategies and reduce the distribution cost for the multi-product, multi-depot periodic distribution problem. In industry practice, depots typically operate independently and solely within their own territories. However, it may be beneficial to allow those depots to operate interdependently, particularly when the product supplies are limited at some depots. In such cases, the distributors may satisfy customers' requests by delivering products from other depots that hold more supplies. In particular, the impact of interdependent operations among depots, which has not previously been addressed in the context of industrial applications, is investigated in this research. A mixed-integer linear programming model is formulated to represent the multi-product, multi-depot periodic distribution problem. Three tabu search heuristics with different long-term memory applications are developed to solve the problem. The performance of the heuristics is evaluated by comparing the solutions obtained with the optimal solutions or lower bounds from the regular branch-and-bound method as well as a fast technique to find a lower bound that is developed in this research. The heuristics provide optimal/good quality solutions in a much shorter time. A randomized complete block design is applied to test the performance of the heuristics on various problem structures. The experimental results show that the tabu search heuristic that incorporates the use of a long-term memory in the diversification process outperforms the other heuristics. The heuristic is further applied to investigate the impact of interdependent operations among depots. The results reveal that interdependent operations among depots provide significant savings in costs over independent operations among depots, especially for large-size problems.

Acknowledgements

We are grateful to the Director of Transportation at SYSCO Food Services of Portland, Inc. for offering guidelines on data generation. We thank Professor Panos Kouvelis—the Department Editor, an anonymous Area Editor, and three anonymous referees for their comments and suggestions.