A Combination of Shuffled Frog Leaping and Fuzzy Logic for Flexible Job-Shop Scheduling Problems

Abstract

Abstract Flexible Job-Shop Scheduling Problem (FJSP) is a well known NP-hard combinatorial optimization problem. Over the last decade, many algorithms have been proposed to tackle FJSP. Evolutionary algorithms, which solve problems by mimicking the process of natural evolution, are the most widely used techniques in solving FJSP. This paper proposes a novel evolutionary algorithm that integrates the concept of a fuzzy logic into Shuffled Frog Leaping Algorithm. In the proposed SFLA-FS model, the fuzzy roulette wheel selection is used in selecting frogs to form a sub-memeplex. This selection method is proved to be better than the typically used rank selection. The objective of this research is to find a schedule for each of the 10 benchmark problems that minimize their makespan. The experimental results obtained from SFLA-FS show that the SFLA-FS is very efficient for all tested problems.