Indian Journal of Science and Technology
Year: 2016, Volume: 9, Issue: 10, Pages: 1-13
K. Kanaka Vardhini 1* andT. Sita mahalakshmi 2
*Author for Correspondence
K. Kanaka Vardhini Department of CSE, ASCET, Gudur – 524101, Andhra Pradesh, India; [email protected]
Background /Objectives: In today’s world, finding a feasible solution for combinatorial problems becoming a crucial task. The main objective of this paper is to analyze and comprehend different nature based algorithms enabling to find optimal solution. Methods/statistical analysis: Bacterial Foraging Algorithm (BFOA), firefly algorithm, Ant Colony Optimization (ACO), bee colony optimization, cuckoo optimization etc. Which have been used in power load balancing, cost estimating, optimal routing, color segmentation were discussed. This paper also highlights the constraints and convergence properties of each algorithm to solve certain problems encountered in various fields of application. Findings: Ant colony algorithms were successful in finding solutions within 1% of known optimal solutions. Optimal solution was found in BFOA by adjusting chemo taxis step size. Also, this paper analyzes results of various research works done in numerous fields using the swarm intelligence techniques
Keywords: Combinatorial Problems, Optimization, Swarm Intelligence
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