Dual-rail–guided vehicle scheduling in an automated storage and retrieval system with loading and collision-avoidance constraints. Issue 8 (28th May 2021) - Ma, Changpu; Zhou, Binghai
Abstract : Purpose: The use of multiple-capacity rail-guided vehicles (RGVs) has made automated storage and retrieval system (AS/RS) optimization more complex. The paper performs dual-RGV scheduling considering loading/unloading and collision-avoidance constraints simultaneously as these issues have only been considered separately in the previous literature. Design/methodology/approach: This paper proposes a novel model for dual-RGV scheduling with two-sided loading/unloading operations and collision-avoidance constraints. To solve the proposed problem, a hybrid harmony search algorithm (HHSA) is developed. To enhance its performance, a descent-based local search with eight move operators is introduced. Findings: A group of problem instances at different scales are optimized with the proposed algorithm and the results are compared with those of two other high-performance methods. The results demonstrate that the proposed method can efficiently solve realistically sized cases of dual multi-capacity RGV scheduling problems in AS/RSs. Originality/value: For the first time in the research on dual multi-capacity RGV scheduling in an AS/RS, two-sided loading/unloading operations and collision avoidance constraints are simultaneously considered. Furthermore, a mathematical model for minimizing the makespan is developed and the HHSA is developed to determine solutions.