Du K-L and Swamy M N S 2016 Search and Optimization by Metaheuristics (Springer: Switzerland).Du KL, Swamy MNS. Search and Optimization by Metaheuristics. Switzerland: Springer; 2016Du, K.-L. and Swamy, M. N. S. (2016) Search and Optimization by Metaheuristics. Switzerland: Birkhauser....
Search and Optimization by Metaheuristics is intended primarily as a textbook for graduate and advanced undergraduate students specializing in engineering and computer science. It will also serve as a valuable resource for scientists and researchers working in these areas, as well as those who are inte...
Although the SGHS algorithm was inspired by the GHS algorithm [13], the SGHS employs a new improvisation scheme and an adaptive parameter tuning methods unlike the GHS algorithm. Show abstract Search and optimization by metaheuristics: Techniques and algorithms inspired by nature 2016, Search and ...
It enhances the energy-efficient and reliable operation of power s... S Mishra,SK Patra - First International Conference on Emerging Trends in Engineering & Technology 被引量: 35发表: 2008年 Search and optimization by metaheuristics: techniques and algorithms inspired by nature Preliminary review /...
The other foraging mechanisms exercised by capuchins, known as swinging and climbing, allow the capuchins to move small distances over trees, tree branches, and the extremities of the tree branches. These locomotion mechanisms eventually lead to feasible solutions of global optimization problems. The...
Local search metaheuristics (LSMs) are efficient methods for solving hard optimization problems in science, engineering, economics and technology. By using LSMs, we could obtain satisfactory resolution (approximate optimum) in a reasonable time. However, it is still very CPU time-consuming when solving...
The complexity of engineering optimization problems is increasing. Classical gradient-based optimization algorithms are a mathematical means of solving complex problems whose ability to do so is limited. Metaheuristics have become more popular than exact
optimization17. This is because CS algorithm has two crucial search capabilities, which are local search and global search controlled by a fraction probability or discovery rate,Painternal parameter. Another advantage is CS algorithm uses Lévy flights motion with infinite mean and variance rather than...
Illustrative forms of these subroutines are described that make it possible to create methods for a wide range of optimization problems. 展开 关键词: metaheuristics evolutionary methods optimization tabu search 会议时间: 1998 被引量: 1115 收藏 引用 批量引用 报错 分享 ...
While both games and Multi-Objective Optimization (MOO) have been studied extensively in the literature, Multi-Objective Games (MOGs) have received less research attention. Existing studies deal mainly with mathematical formulations of the optimum. However, a definition and search for the representation...