Solving the Tension/Compression Spring Design Problem by an Improved Firefly Algorithm

Since the 1970s, nature inspired meta-heuristic algorithms have become increasingly popular. These algorithms include a set of algorithmic concepts that can be used to identify heuristic methods that are used for a wide range of different tasks. The use of meta-heuristics greatly increases the possibility of finding a qualitative solution for complex, combinatorial optimization problems in a reasonable time. The most popular nature inspired meta-heuristics are those methods representing successful animal and micro-organism swarm behaviors. Firefly Algorithm (FA) is a recent one of such meta-heuristic algorithms It is based on a swarm intelligence and inspired by the social behaviors of fireflies. In this paper, we adapt the neighborhood method to FA and propose an improved firefly algorithm (IFA) to solve a well-known engineering problem, the so-called Tension/Compression Spring Design. We test the proposed IFA on this problem and compare the results with those obtained by some other meta-heuristics. The experimental modeling shows that the proposed IFA is competitive and improves the quality of solutions for the aforementioned engineering design problem.