TAILIEUCHUNG - A novel hybrid backtracking search optimization algorithm for continuous function optimization

Backtracking Search Optimization Algorithm (BSA) is a new stochastic evolutionary algorithm and the aim of this paper is to introduce a hybrid approach combining the BSA and Quadratic approximation (QA), called HBSAfor solving unconstrained non-linear, non-differentiable optimization problems. | Nội dung Text A novel hybrid backtracking search optimization algorithm for continuous function optimization Decision Science Letters 8 2019 163 174 Contents lists available at GrowingScience Decision Science Letters homepage dsl A novel hybrid backtracking search optimization algorithm for continuous function optimization Sukanta Namaa and Apu Kumar Sahab aDepartment of Mathematics Ram Thakur College Agartala . Nagar-799003 West Tripura India bDepartment of Mathematics National Institute of Technology Agartala Barjala Jirania Tripura-799046 India CHRONICLE ABSTRACT Article history Stochastic optimization algorithm provides a robust and efficient approach for solving complex Received April 3 2018 real world problems. Backtracking Search Optimization Algorithm BSA is a new stochastic Received in revised format evolutionary algorithm and the aim of this paper is to introduce a hybrid approach combining the May 10 2018 BSA and Quadratic approximation QA called HBSAfor solving unconstrained non-linear Accepted July 9 2018 Available online non-differentiable optimization problems. For the validity of the proposed method the results are July 9 2018 compared with five state-of-the-art particle swarm optimization PSO variant approaches in Keywords terms of the numerical result of the solutions. The sensitivity analysis of the BSA control Backtracking Search Optimization parameter F is also performed. Algorithm BSA Quadratic approximation QA Hybrid Algorithm Unconstrained non-linear function optimization 2018 by the authors licensee Growing Science Canada. 1. Introduction Stochastic Optimization algorithms are effective and powerful tool for solving nonlinear complex optimization problem. Many nature based stochastic algorithms have been introduced and studied by many authors . Yang amp Press 2010 . The success of an optimization algorithm depends on its significant development of exploration and exploitation abilities. The first attempt to .

• Cơ khí - Chế tạo máy
• Backtracking Search Optimization Algorithm
• Unconstrained non linear function optimization
• BSA and Quadratic approximation
• Non differentiable optimization problem
• Continuous function optimization
• BMC Bioinformatics
• Parameter inference
• Regulatory network
• Mathematical model
• Continuous objective function
• Robustness analysis