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Firefly-Inspired Algorithm for Job Shop Scheduling

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Original languageEnglish
Title of host publicationAdventures Between Lower Bounds and Higher Altitudes
Subtitle of host publicationEssays Dedicated to Juraj Hromkovic on the Occasion of His 60th Birthday
ISBN (Electronic)9783319983554
ISBN (Print)9783319983547
Accepted/In press2 May 2018
E-pub ahead of print9 Aug 2018

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743


King's Authors


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.

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