A novel hybrid clonal selection algorithm for the corridor allocation problem with irregular material handling positions

As an essential influencing factor in the facility layout, the reasonable setting of material handling positions plays a vital role in improving operational efficiency and reducing material handling costs. In this paper, a corridor allocation problem (CAP) that allows irregular logistics material handling positions (IMHPCAP) is proposed. Compared with previous CAP studies, IMHPCAP allows facilities to set irregular material handling positions according to their characteristics to increase material handling flexibility. However, the IMHPCAP is more challenging than the traditional CAP finding the best layout solution. In order to solve this problem, a mixedinteger programming model of IMHPCAP is established. A clonal selection algorithm with social engineering optimiser based on a two-stage solution was proposed to obtain the best layout for large-scale problems. In the first stage of this algorithm, the rows in which facilities are placed, and the arrangement sequence of the facilities are established. In the second stage, the precise coordinates of the MHPs are obtained using a mathematical programming method. Finally, some benchmark instances of the CAP and IMHPCAP were solved to verify the performance of the algorithm. Furthermore, an actual case of a baby plastic product processing plant was considered to validate the IMHPCAP. The results showed that the hybrid clone algorithm performed well in solving the CAP and IMHPCAP, thereby exhibiting practical significance.

Automated summary

This paper proposes a corridor allocation problem that allows irregular logistics material handling positions. A clonal selection algorithm is used to optimize the material handling layout, and the performance of the algorithm is verified through benchmark instances and an actual case study.