作者: Yong Xian Li, Bin Wang, Guang Ping Peng

摘要: A new intelligent orthogonal optimization algorithm for robust design is proposed in order to improve accuracy and efficiency. The next searching direction and searching range of variables are determined by variance ratio after the robust optimization model is firstly calculated by design parameters on orthogonal array. New orthogonal array for further optimization is formed intelligently by analysis of variance ratio. The intelligent orthogonal optimization is performed until error value of each variable is equal to zero or is equivalent, which is the optimal robust solution. Correspondingly, the variable range corresponding to the minimum variance ratio in the orthogonal array in preceding step is the tolerance of the optimal robust solution, which means that there is no need for special tolerance design. This paper takes a cam profile as an example to perform robust design. The simulation results prove that the new intelligent algorithm for robust design has many advantages, such as less calculation time, higher speed, no exiting of prematurity of local circulation and slow convergence of global search.

301

作者: Shu Ling Qiao, Zhi Jun Han

摘要: In this paper, determinate beam and indeterminate beam with multiple span are optimized by using genetic algorithm, the mathematic model of optimize beam is built and the processing method of constraint conditions is given. The examples show that the algorithm could be used for optimizing determinate structure, and also optimizing indeterminate structure. Compared to the linear approximation method, genetic algorithm has advantages of being simple, easy, fast convergence and has no use for changing the objective function and constraint conditions to linearity or other processing. Its results agree with linear approximation method’s. It is the other method that can be adopt in engineering field.

2365

作者: Xiao Hua Wang, Yong Mei Zhang

摘要: On the premise of ensuring safety and reliability in electricity market environment, the goal of State Grid Corporation is that purchase AGC ancillary service charges of reducing cost. This paper first takes total expense from many AGC units as an objective function, , which synthetically considers total regulation MW amount and total regulation speed constraints. A novel hybrid particle swarm optimization (PSO) algorithm is applied to solve the problem. Numerical simulation results show that the improved PSO algorithm has advantages both in the calculation accuracy and the convergence speed. Therefore, it is concluded that the algorithm is supposed to be an effective way to deal with the optimized issue in the power market.

274

作者: Si Lian Xie, Tie Bin Wu, Shui Ping Wu, Yun Lian Liu

摘要: Evolutionary algorithms are amongst the best known methods of solving difficult constrained optimization problems, for which traditional methods are not applicable. Due to the variability of characteristics in different constrained optimization problems, no single evolutionary with single operator performs consistently over a range of problems. We introduce an algorithm framework that uses multiple search operators in each generation. A composite evolutionary algorithm is proposed in this paper and combined feasibility rule to solve constrained optimization problems. The proposed evolutionary algorithm combines three crossover operators with two mutation operators. The selection criteria based on feasibility of individual is used to deal with the constraints. The proposed method is tested on five well-known benchmark constrained optimization problems, and the experimental results show that it is effective and robust

2846

摘要: This paper presents a hybrid algorithm to address the flexible job-shop scheduling problem (FJSP). Based on Differential Evolution (DE), a global search method is introduced in the hybrid algorithm, where variations are made to the mutation and crossover operators in DE, according to the quantum rotation gate. And an Interchange-based local search method is further adopted in the proposed algorithm to gain a better performance. Experiments are performed to show the efficiency of the proposed algorithm.

502