Improved symbiotic organisms search algorithm for solving unconstrained function optimization

Article history: Received October 25, 2015 Received in revised format: February 12, 2016 Accepted February 22, 2016 Available online Februray 22 2016 Recently, Symbiotic Organisms Search (SOS) algorithm is being used for solving complex problems of optimization. This paper proposes an Improved Symbiotic Organisms Search (ISOS) algorithm for solving different complex unconstrained global optimization problems. In the improved algorithm, a random weighted reflective parameter and predation phase are suggested to enhance the performance of the algorithm. The performances of this algorithm are compared with the other state-of-the-art algorithms. The parametric study of the common control parameter has also been performed. Growing Science Ltd. All rights reserved. 6 © 201

[1]  Maryam Orouji.  Theory of constraints: A state-of-art review , 2016 .

[2]  M. Dorigo,et al.  1 Positive Feedback as a Search Strategy , 1991 .

[3]  Mohammad Reza Mohammadi,et al.  Multi-period fuzzy mean-semi variance portfolio selection problem with transaction cost and minimum transaction lots using genetic algorithm , 2016 .

[4]  Samiran Chattopadhyay,et al.  A hybrid of genetic algorithm and Fletcher-Reeves for bound constrained optimization problems , 2015 .

[5]  Amitava Chatterjee,et al.  A new social and momentum component adaptive PSO algorithm for image segmentation , 2011, Expert Syst. Appl..

[6]  Jing J. Liang,et al.  Problem Definitions and Evaluation Criteria for the CEC 2005 Special Session on Real-Parameter Optimization , 2005 .

[7]  R. Bolaños,et al.  A multiobjective non-dominated sorting genetic algorithm (NSGA-II) for the Multiple Traveling Salesman Problem , 2015 .

[8]  Alper Hamzadayi,et al.  Testing the performance of teaching-learning based optimization (TLBO) algorithm on combinatorial problems: Flow shop and job shop scheduling cases , 2014, Inf. Sci..

[9]  Min-Yuan Cheng,et al.  Optimizing Multiple-Resources Leveling in Multiple Projects Using Discrete Symbiotic Organisms Search , 2016, J. Comput. Civ. Eng..

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

[11]  Morteza Rahmani,et al.  Optimization of continuous ranked probability score using PSO , 2015 .

[12]  Yongqiang Wang,et al.  An improved self-adaptive PSO technique for short-term hydrothermal scheduling , 2012, Expert Syst. Appl..

[13]  Zong Woo Geem,et al.  A New Heuristic Optimization Algorithm: Harmony Search , 2001, Simul..

[14]  Yue Shi,et al.  A modified particle swarm optimizer , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).

[15]  R. Venkata Rao,et al.  Review of applications of TLBO algorithm and a tutorial for beginners to solve the unconstrained and constrained optimization problems , 2016 .

[16]  Xiao-Lin Li,et al.  A hybrid particle swarm optimization method for structure learning of probabilistic relational models , 2014, Inf. Sci..

[17]  Sahand Ghavidel,et al.  Application of imperialist competitive algorithm with its modified techniques for multi-objective optimal power flow problem: A comparative study , 2014, Inf. Sci..

[18]  Nuno Horta,et al.  A SAX-GA approach to evolve investment strategies on financial markets based on pattern discovery techniques , 2013, Expert Syst. Appl..

[19]  Min-Yuan Cheng,et al.  Symbiotic Organisms Search: A new metaheuristic optimization algorithm , 2014 .

[20]  Ganapati Panda,et al.  Particle swarm optimization based nonlinear active noise control under saturation nonlinearity , 2016, Appl. Soft Comput..

[21]  Sima Ghosh,et al.  Parameters Optimization of Geotechnical Problem Using Different Optimization Algorithm , 2015, Geotechnical and Geological Engineering.

[22]  Mitsuo Gen,et al.  Solving job-shop scheduling problems by genetic algorithm , 1994, Proceedings of IEEE International Conference on Systems, Man and Cybernetics.

[23]  M. A. Abido,et al.  Multiobjective particle swarm optimization for environmental/economic dispatch problem , 2009 .

[24]  Vincent F. Yu,et al.  Symbiotic Organism Search (SOS) for Solving the Capacitated Vehicle Routing Problem , 2015 .

[25]  Arian Eshraghi,et al.  A new approach for solving resource constrained project scheduling problems using differential evolution algorithm , 2016 .

[26]  R. Venkata Rao,et al.  Teaching-learning-based optimization: A novel method for constrained mechanical design optimization problems , 2011, Comput. Aided Des..

[27]  Sima Ghosh,et al.  A new ensemble algorithm of differential evolution and backtracking search optimization algorithm with adaptive control parameter for function optimization , 2016 .

[28]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[29]  Rainer Storn,et al.  Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..

[30]  Minghao Yin,et al.  Hybrid differential evolution and gravitation search algorithm for unconstrained optimization , 2011 .

[31]  Thomas Becker,et al.  Application of a modified GA, ACO and a random search procedure to solve the production scheduling of a case study bakery , 2014, Expert Syst. Appl..

[32]  Javad Rezaeian,et al.  A robust hybrid approach based on particle swarm optimization and genetic algorithm to minimize the total machine load on unrelated parallel machines , 2016, Appl. Soft Comput..

[33]  Mehmet Fatih Tasgetiren,et al.  Differential evolution algorithm with ensemble of parameters and mutation strategies , 2011, Appl. Soft Comput..

[34]  Maryam Hosseini,et al.  An efficient approach based on differential evolution algorithm for data clustering , 2014 .

[35]  Shafii Muhammad Abdulhamid,et al.  Symbiotic Organism Search optimization based task scheduling in cloud computing environment , 2016, Future Gener. Comput. Syst..

[36]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[37]  Anima Naik,et al.  Cooperative Teaching–Learning Based Optimisation for Global Function Optimisation , 2013 .

[38]  Qingfu Zhang,et al.  Differential Evolution With Composite Trial Vector Generation Strategies and Control Parameters , 2011, IEEE Transactions on Evolutionary Computation.

[39]  Ardeshir Bahreininejad,et al.  Water cycle algorithm - A novel metaheuristic optimization method for solving constrained engineering optimization problems , 2012 .

[40]  Thomas Becker,et al.  A case study on using evolutionary algorithms to optimize bakery production planning , 2013, Expert Syst. Appl..

[41]  Taher Niknam,et al.  Reliability-Oriented Reconfiguration of Vehicle-to-Grid Networks , 2015, IEEE Transactions on Industrial Informatics.

[42]  Vivekananda Mukherjee,et al.  A novel symbiotic organisms search algorithm for optimal power flow of power system with FACTS devices , 2016 .

[43]  V. Mukherjee,et al.  A novel symbiotic organisms search algorithm for congestion management in deregulated environment , 2017, J. Exp. Theor. Artif. Intell..

[44]  Uwe Aickelin,et al.  An Indirect Genetic Algorithm for a Nurse Scheduling Problem , 2004, Comput. Oper. Res..

[45]  ChatterjeeAmitava,et al.  A new social and momentum component adaptive PSO algorithm for image segmentation , 2011 .

[46]  Vivek Patel,et al.  A multi-objective improved teaching-learning based optimization algorithm for unconstrained and constrained optimization problems , 2014 .