Performance Investigation of Artificial Bee Colony (ABC) Algorithm for Permutation Flowshop Scheduling Problem (PFSP)

Abstract

The purpose of the Permutation Flowshop Scheduling Problem (PFSP) is to find the best permutation of jobs. PFSP is also considered as an optimization problem and it is often solved using the swarm intelligence approach. In this paper, Artificial Bee Colony (ABC) algorithm is used for solving PFSP. To investigate the effect of trial counter (TC) to the performance of ABC, the TC value was set to six (6), twelve (12) and eighteen (18). Additionally, the percentage of errors was selected as the response. From the experimental results, it can be concluded that ABC algorithm performs best when the TC is set at six (6) because the value of cumulative error percentages is at the lowest. Moreover, the generated data is also located in the smallest spread compared to TC = 12 and TC = 18. It can also be concluded that the exploration principle works better in a 6 jobs and 3 machines PFSP environment.