A Modified Artificial Bee Colony Algorithm for Scheduling Optimization of Multi-aisle AS/RS System

Abstract

A modified artificial bee colony algorithm is proposed for solving the scheduling optimization problem of multi-aisle automatic storage/retrieval system. The optimization model of the problem is analyzed and founded, in which the sequence constraint of tasks and calculation of the number of aisles are more realistic. According to the features of the problem, the encoding and decoding strategies for solutions to MABC algorithm are redesigned. Probability selection-based updating method is also introduced to enhance the neighborhood search and preserve the good fragments. The experimental results show that MABC can obtain better results than PSO and GA algorithm, and is a competitive approach for AS/RS scheduling optimization.