A Systematic Review on Firefly Algorithm: Past, Present, and Future
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ORIGINAL PAPER
A Systematic Review on Firefly Algorithm: Past, Present, and Future Vijay Kumar1 · Dinesh Kumar2 Received: 18 February 2020 / Accepted: 19 September 2020 © CIMNE, Barcelona, Spain 2020
Abstract Firefly Algorithm (FA) is one of the popular algorithm of Swarm Intelligence domain that can be used in most of the areas of optimization. FA and its variants are simple to implement and easily understood. These can be used to successfully solve the problems of different areas. Modification in original FA or hybrid FA algorithms are required to solve diverse range of engineering problems. In this paper, a comprehensive review of firefly algorithm is presented and various characteristics are discussed. The various variant of FA such as binary, multi-objective and hybrid with other meta-heuristics are discussed. The applications and performance evolution metric are presented. This paper provides the possible future research direction of FA.
1 Introduction Soft computing have various techniques for computation (as shown in Fig. 1) such as Neural system, Fuzzy, evolutionary computing, chaos theory and many more. Swarm Intelligence (SI) is one of the very promising domain of AI (Artificial Intelligence) as shown in Fig. 2, become drastically important and popular in last few years [1]. The study of behaviour of ants, fireflies, bees, worms, termites, group of birds and fishes inspires the further research done in the field of SI [2], as shown in Figs. 3 and 4. The coordinated behaviour of these groups direct them to achieve their desired goal. The simple interaction between unsophisticated individuals leads group towards a self organizing behaviour for the whole group with their collective intelligence. The simple interaction in this multi agent system forms this self organizing and coordinated behaviour. Termites and worms interacts to other individuals for construction of their nests. Ants and bees forms a collective behaviour to find out their food [3]. To get shortest way to the place where food has found from their colony, ants use chemical pheromone trails * Vijay Kumar [email protected] Dinesh Kumar [email protected] 1
Computer Science and Engineering Department, National Institute of Technology, Hamirpur, Himachal Pradesh 177005, India
Electronics and Communication Engineering Department, Delhi Technological University, Delhi 110042, India
2
while interact to each other. The informer scout bees have responsibility to find new origins of food and these bees use waggle dance to communicate or direct the other bees. During the search of new source of food, bees trade off the work of collection of new information (exploration) and the information (exploitation) [3]. The bee colony is pretty much aware about when to use the food and when to search the food, to maximize intake and minimize foraging effort. These above mentioned swarm utilize their behaviour for making decisions such as: reproduction, foraging, finding new home, division of task among each other, etc. [3]. The beauty of
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