Recent Advances in Computer Science and Communications

Author(s): Rohit K. Sachan* and Dharmender S. Kushwaha

DOI: 10.2174/2666255813666191204145707

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Inspirations from Nature for Meta-Heuristic Algorithms: A Survey

Page: [1706 - 1718] Pages: 13

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Abstract

Background: Nature-Inspired Algorithms (NIAs) are the most efficient way to solve advanced engineering and real-world optimization problems. Since the last few decades, various researchers have proposed an immense number of NIAs. These NIAs get inspiration from natural phenomenon. A young researcher attempting to undertake or solve a problem using NIAs is bogged down by a plethora of proposals that exist today. Not every algorithm is suited for all kinds of problem. Some scores over others.

Objective: This paper presents a comprehensive study of seven NIAs, which have new and unique inspirations. This study shall useful to easily understand the fundamentals of NIAs for any new entrant.

Conclusion: Here, we classify the NIAs as natural evolution based, swarm intelligence based, biological based, science based and others. In this survey, well-establish and relatively new NIAs, namely- Shuffled Frog Leaping Algorithm (SFLA), Firefly Algorithm (FA), Gravitational Search Algorithm (GSA), Flower Pollination Algorithm (FPA), Water Cycle Algorithm (WCA), Jaya Algorithm and Anti-Predatory NIA (APNIA), have been studied. This study presents a theoretical perspective of NIAs in a simplified form based on its source of inspiration, mathematical formulations, control parameters, features, variants and area of application, where these algorithms have been successfully applied.

Keywords: Nature-inspired algorithm, firefly algorithm, flower pollination, shuffled frog leaping, swarm intelligence, antipredatory NIA.