Two Improved Cuckoo Search Algorithms for Solving The Flexible Job-Shop Scheduling Problem

Abstract

The Cuckoo Search (CS) is heuristic search algorithm which inspired from cuckoo bird behavior. In this paper, we proposed two improvements for the cuckoo search algorithm of solving Flexible Job-Shop Scheduling problem (FJSP); the first one depends on Best Neighbors Generation (CS-BNG) and the second one based on Iterative Levy Flight (CS-ILF). Some adaptation for the key points of CS algorithm has been done to enhance searching in the discrete state space. The proposed algorithms have increased solutions quality and convergence rate. The improved algorithms have been tested on some FJSP benchmark instances for performance examination. The experimental results demonstrate the effectiveness of the improved algorithms in comparison to the basic cuckoo search algorithm.