Optimization Strategies to Explore Multiple Optimal Solutions and Its Application to Restraint System Design
暂无分享，去创建一个
[1] DebKalyanmoy. Multi-objective genetic algorithms , 1999 .
[2] Wang Xuan,et al. Solving Six-Hump Camel Back Function Optimization Problem by Using Thermodynamics Evolutionary Algorithm , 2010, 2010 Second International Conference on Networks Security, Wireless Communications and Trusted Computing.
[3] James Kennedy,et al. Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.
[4] Kalyanmoy Deb,et al. Multi-objective Genetic Algorithms: Problem Difficulties and Construction of Test Problems , 1999, Evolutionary Computation.
[5] Yan Fu,et al. The Effect of Initial Population Sampling on the Convergence of Multi-Objective Genetic Algorithms , 2009 .
[6] Kalyanmoy Deb,et al. A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..
[7] Mirko Krivánek,et al. Simulated Annealing: A Proof of Convergence , 1994, IEEE Trans. Pattern Anal. Mach. Intell..
[8] Sven Leyffer,et al. Integrating SQP and Branch-and-Bound for Mixed Integer Nonlinear Programming , 2001, Comput. Optim. Appl..
[9] David E. Goldberg,et al. Genetic Algorithms in Search Optimization and Machine Learning , 1988 .
[10] M Reyes Sierra,et al. Multi-Objective Particle Swarm Optimizers: A Survey of the State-of-the-Art , 2006 .
[11] C. D. Gelatt,et al. Optimization by Simulated Annealing , 1983, Science.