Design and development of a software system for swarm intelligence based research studies

This paper introduce a software system including widely-used Swarm Intelligence algorithms or approaches to be used for the related scientific research studies associated with the subject area. The programmatic infrastructure of the system allows working on a fast, easy-to-use, interactive platform to perform Swarm Intelligence based studies in a more effective, efficient and accurate way. In this sense, the system employs all of the necessary controls for the algorithms and it ensures an interactive platform on which computer users can perform studies on a wide spectrum of solution approaches associated with simple and also more advanced problems.

[1]  Dervis Karaboga,et al.  A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm , 2007, J. Glob. Optim..

[2]  R. Poli An Analysis of Publications on Particle Swarm Optimisation Applications , 2007 .

[3]  Hamed Shah-Hosseini,et al.  Intelligent water drops algorithm: A new optimization method for solving the multiple knapsack problem , 2008, Int. J. Intell. Comput. Cybern..

[4]  Marco Dorigo,et al.  Ant colony optimization , 2006, IEEE Computational Intelligence Magazine.

[5]  Xin-She Yang,et al.  Firefly Algorithms for Multimodal Optimization , 2009, SAGA.

[6]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[7]  Christian Blum,et al.  Ant colony optimization: Introduction and recent trends , 2005 .

[8]  Hamed Shah-Hosseini,et al.  The intelligent water drops algorithm: a nature-inspired swarm-based optimization algorithm , 2009, Int. J. Bio Inspired Comput..

[9]  D. Karaboga,et al.  On the performance of artificial bee colony (ABC) algorithm , 2008, Appl. Soft Comput..

[10]  Marco Dorigo,et al.  Ant system: optimization by a colony of cooperating agents , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[11]  Xin-She Yang,et al.  Nature-Inspired Metaheuristic Algorithms , 2008 .

[12]  Riccardo Poli,et al.  Analysis of the publications on the applications of particle swarm optimisation , 2008 .

[13]  Hamed Shah-Hosseini,et al.  Optimization with the Nature-Inspired Intelligent Water Drops Algorithm , 2009 .

[14]  Hamed Shah-Hosseini,et al.  Problem solving by intelligent water drops , 2007, 2007 IEEE Congress on Evolutionary Computation.

[15]  Dervis Karaboga,et al.  AN IDEA BASED ON HONEY BEE SWARM FOR NUMERICAL OPTIMIZATION , 2005 .

[16]  Xin-She Yang,et al.  Firefly algorithm, stochastic test functions and design optimisation , 2010, Int. J. Bio Inspired Comput..

[17]  Marco Dorigo,et al.  Optimization, Learning and Natural Algorithms , 1992 .

[18]  Slawomir Zak,et al.  Firefly Algorithm for Continuous Constrained Optimization Tasks , 2009, ICCCI.