نتایج جستجو برای: non dominated sorting genetic
تعداد نتایج: 1937531 فیلتر نتایج به سال:
Computational Intelligence in Optimization of Wire Electrical Discharge Machining of Cold-Work Steel
In this study, two parameters of surface roughness and volumetric material removal rate are optimized based on computational intelligence method. Wire electrical discharge machine is used for machining of cold-work steel 2601. The relation between Input parameters including electrical current, pulse-off time, open-circuit voltage and gap voltage and output parameters is studied via Experimental...
In this paper, we propose a dynamic, non-dominated sorting, multiobjective particle-swarm-based optimizer, named Hierarchical Non-dominated Sorting Particle Swarm Optimizer (H-NSPSO), for memory usage optimization in embedded systems. It significantly reduces the computational complexity of others MultiObjective Particle Swarm Optimization (MOPSO) algorithms. Concretely, it first uses a fast no...
The scheduling of multi-user remote laboratories is modeled as a multimodal function for the proposed optimization algorithm. hybrid algorithm, hybridization Nelder-Mead Simplex and Non-dominated Sorting Genetic Algorithm (NSGA), named (SNSGA), to optimize timetable problem coordinate shared access. algorithm utilizes in terms exploration NSGA sorting local optimum points with consideration pot...
در چند دهه ی اخیر، افزایش کارایی و ایمنی سازه ها در برابر خطرات طبیعی از قبیل زلزله های شدید، با استفاده از ایده ی کنترل سازه ها توجه محققین بسیاری را به خود جلب کرده است. سیستم های مختلف کنترل سازه ها بر حسب میزان انرژی مورد نیاز و نحوه ی تأثیرگذاری روی سیستم به سه گروه عمده ی غیرفعال، فعال و نیمه فعال تقسیم می شوند. سیستم های نیمه فعال، با توجه به دارا بودن ویژگی های هر دو گروه، یعنی قابل اطم...
In this paper we have developed a new technique to determine optimal solution to box pushing problem by two robots . Non-Dominated sorting genetic algorithm and Biogeography-based optimization algorithm are combined to obtain optimal solution. A modified algorithm is developed to obtain better energy and time optimization to the box pushing problem.
A novel multi-objective evolutionary algorithm (MOEA) is developed based on Imperialist Competitive Algorithm (ICA), a newly introduced evolutionary algorithm (EA). Fast non-dominated sorting and the Sigma method are employed for ranking the solutions. The algorithm is tested on six well-known test functions each of them incorporate a particular feature that may cause difficulty to MOEAs. The n...
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