A Heuristic Method for Load Retrievals Route Programming in Puzzle-based Storage Systems

TL;DR

This paper introduces a heuristic algorithm for optimizing load retrieval routes in puzzle-based storage systems with multiple targets, escorts, and IOs, improving space utilization and operational efficiency.

Contribution

It presents a novel heuristic algorithm based on Markov decision processes for load retrieval routing in PBSSs with multiple targets, a problem not previously addressed.

Findings

The algorithm effectively reduces retrieval time.

It improves space utilization in PBSSs.

Case studies confirm its efficiency.

Abstract

Recently, many enterprises are facing the difficulties brought out by the limitation of warehouse land and the increase of loan cost. As a promising approach to improve space utilization rate, puzzle-based storage systems (PBSSs) are drawing more attention from logistics researchers. In previous research about PBSS, concentration has been paid to single target item problems. However, there are no consensus algorithms to solve load retrievals route programming in PBSSs with multiple target items. In this paper, a heuristic algorithm is proposed to solve load retrievals route programming in PBSSs with multiple target items, multiple escorts and multiple IOs. In this paper, new concepts about the proposed algorithm are defined, including target IOs, target position of escorts, number of escorts required, et al. Then, the decision procedures are designed according to these concepts. Based on Markov decision process, the proposed algorithm makes the decision of the next action by analyzing the current status, until all the target items arrive at the IOs. The case study results have shown the effectiveness and efficiency of the proposed heuristic algorithm.