Current research strongly suggests that hybrid local search algorithms are more effective than heuristics based on homogenous methods. Accordingly, this paper presents a new hybrid method of Simulated Annealing and Firefly Algorithm [SAFA] for the Job Shop Scheduling Problem (JSSP) with the objective of minimising the makespan. We provide an experimental analysis of its performance based on a set of established benchmarks. Simulated Annealing [SA] continues to be a viable approach in identifying optimal and near optimal makespans for the JSSP. Similarly, recent deployments of the Firefly Algorithm [FA] have delineated its effectiveness for solving combinatorial optimisation problems efficiently. Therefore, the hybrid algorithm in question aims to combine the acclamatory strengths of SA and FA while overcoming their respective deficiencies.
CITATION STYLE
Miller-Todd, J., Steinhöfel, K., & Veenstra, P. (2018). Firefly-inspired algorithm for job shop scheduling. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11011 LNCS, pp. 423–433). Springer Verlag. https://doi.org/10.1007/978-3-319-98355-4_24
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