A study of flexible flow shop scheduling problem with variable processing times based on improved bat algorithm

Abstract

In order to solve the problem of flexible flow shop scheduling with variable processing time (FFSP-VPT), a mathematical model is established, in this paper, based on analysing the processing time selection, defect detection, and rework of jobs with variable processing time. According to the characteristics of FFSP-VPT, a two-stage coding method is designed using ranked over value (ROV) coding. Based on the bat algorithm (BA), a self-adaptive elite bat algorithm (SEBA) is developed as the global optimisation method in this study by using Hamming distance-based elite individual set and adaptive position update. Crossover tests are designed to determine the optimal values of critical parameters in SEBA. Validity of SEBA on solving FFSP-VPT in actual production is verified by comparing the simulation test results of SEBA with those of other algorithms.