Y Kang, et al.The Combinatorial Optimization by Genetic Algorithm and Neural Network for Energy Storage System in Solar Energy Electric Vehicle. 2008 7th World Congress on Intelligent Control and Automation .S. Zhou, L. Kang, G. Guo, Y. Zhang, B. Cao, The combinatorial optimization by ...
Finally, we propose conditions ensuring that a Non-Elitist Genetic Algorithm efficiently finds approximate solutions with constant approximation ratio on the class of combinatorial optimization problems with guaranteed local optima (GLO).doi:10.48550/arXiv.1512.02047Dang, Duc-Cuong...
This is a typical combinatorial optimization problem. Because genetic algorithm (GA) is suitable to solve such problems, it is here used to integrate short line segments into long contour lines by using a graph-based genetic representation and improved genetic operations. The results of the present...
Genetic algorithm is applied to groups of the same type of modeling,applying this method for each component to form a variety of component libraries. Particle swarm algorithm is applied to the combination of the components of the complex models, combinatorial optimization of the various components ...
tOSGAandIGA. Keywords : structuralOptimizatiOndesign ; relativedifference uOtientalgOrithm ; simplegeneticalgOrithm ; imprOvedgenetic algOrithm ; cOmbinatOrialgeneticalgOrithm ( Recei edAPril6 , 2UU5 ) 5 1 3 第 3 期范 鹤等:结构优化设计中的组合遗传算法相关...
Optimization problems are often highly constrained and evolutionary algorithms (EAs) are effective methods to tackle this kind of problems. To further improve search efficiency and convergence rate of EAs, this paper presents an adaptive double chain quantum genetic algorithm (ADCQGA) for solving constr...
This paper describes libbrkga, a GNU-style dynamic shared Python/C++ library of the biased random-key genetic algorithm (BRKGA) for bound constrained global optimization. BRKGA (J Heuristics 17:487–525, 2011b) is a general search metaheuristic for finding optimal or near-optimal solutions to...
Abstract Generalized Traveling Salesman Problem (GTSP) is one of the challenging combinatorial optimization problems in a lot of applications. In general, GTSP is more complex than Traveling Salesman Problem (TSP). In this paper, a novel hybrid chromosome genetic algorithm (HCGA), in which the hy...
Based on quantum mutation, a quantum genetic algorithm (QGA) to solve combinatorial optimization problem is proposed.It has good features of genetic quantu... Y Xiong,HH Chen,FY Miao,... - 《Acta Electronica Sinica》 被引量: 119发表: 2004年 An entanglement monotone derived from Grover's al...
4.2 Tabu search algorithm (TSA) The TSA is often used for combinatorial optimization problems (Oliveira and Pardalos 2011). It explores the solution space for a number of iterations from an initial random solution to another better solution in the neighborhood of the former one. The best solution...