1Assistant Professor, Department of Computer Science & IT, Jagannath University, Jaipur. Email: sandeep.kumar@jagannathuniversity.org
2Professor, Department of Mathematics, Jagannath University, Jaipur. Email: vivek.sharma@jagannathuniversity.org
3Assistant Professor, Department of Computer Science, St. Xavier's College, Jaipur. Email: rajanikpoonia@gmail.com
Online published on 22 June, 2017.
Algorithms inspired by intelligent behavior of simple agents are very popular now a day among researchers. A comparatively young algorithm motivated by extraordinary behavior of Spider Monkeys is Spider Monkey Optimization (SMO) algorithm. SMO algorithm is very successful algorithm to get to the bottom of optimization problems. This work presents a self-adaptive Spider Monkey optimization (SaSMO) algorithm for optimization problems. The proposed strategy is self-adaptive in nature and therefore no manual parameter setting is required. The proposed technique is named as Self-Adaptive Spider Monkey optimization (SaSMO) algorithm. SaSMO gives better results for considered problems. Results are compared with basic SMO and its recent variant MPU-SMO.
Spider Monkey Optimization Algorithm, Swarm intelligence, Engineering optimization problems, Nature Inspired Algorithms
