A fuzzy particle swarm optimization （PSO） on the basis of elite archiving is proposed for solving multi-objective optimization problems. First, a new perturbation operator is designed, and the concepts of fuzzy glob...A fuzzy particle swarm optimization （PSO） on the basis of elite archiving is proposed for solving multi-objective optimization problems. First, a new perturbation operator is designed, and the concepts of fuzzy global best and fuzzy personal best are given on basis of the new operator. After that, particle updating equations are revised on the basis of the two new concepts to discourage the premature convergence and enlarge the potential search space; second, the elite archiving technique is used during the process of evolution, namely, the elite particles are introduced into the swarm, whereas the inferior particles are deleted. Therefore, the quality of the swarm is ensured. Finally, the convergence of this swarm is proved. The experimental results show that the nondominated solutions found by the proposed algorithm are uniformly distributed and widely spread along the Pareto front.展开更多
To assist readers to have a comprehensive understanding, the classical and intelligent methods roundly based on precursory research achievements are summarized in this paper. First, basic conception and description ab...To assist readers to have a comprehensive understanding, the classical and intelligent methods roundly based on precursory research achievements are summarized in this paper. First, basic conception and description about multi-objective (MO) optimization are introduced. Then some definitions and related terminologies are given. Furthermore several MO optimization methods including classical and current intelligent methods are discussed one by one succinctly. Finally evaluations on advantages and disadvantages about these methods are made at the end of the paper.展开更多
This paper puts forward a new integrated design met ho d based on fuzzy matter-element optimization.On the based of analyzing the mod el of multi-objective fuzzy matter-element , the paper defines the m atter-element ...This paper puts forward a new integrated design met ho d based on fuzzy matter-element optimization.On the based of analyzing the mod el of multi-objective fuzzy matter-element , the paper defines the m atter-element weightily and changes solving multi-objective fuzzy optimization into solving dependent function K(x) of the single-objective optimization according to the optimization criterion. The paper particularly describes the realization approach of GA process of multi -objective fuzzy matter-element optimization: encode, produce initial populati on, confirm fitness function, select operator, etc. In the process, the adaptive macro genetic algorithms (AMGA) is applied to enhancing the evolution speed. Th e paper improves the two genetic operators: crossover and mutation operator. The modified adaptive macro genetic algorithms (MAMGA) is put forward simultane ously. It is adopted to solve the optimization problem. Three optimization methods, namely fuzzy matter-element optimization method, li nearity weighted method and fuzzy optimization method, are compared by using the table and figure, it shows that not only MAMGA is a little better than the AMGA , but also it reaches the extent to which the effective iteration generation is 62.2% of simple genetic algorithms (SGA). By the calculation of optimum exam ple, the improved method of genetic in the paper is much better than the method in reference of paper.展开更多
针对目前海洋能区划研究中存在的计算复杂、耗时长和成本高等问题,本研究基于改进的多准则决策(Multiple criteria decision making,MCDM)方法和人工神经网络(Artificial neural network,ANN),提出了一种风浪联合开发区划智能模型。为...针对目前海洋能区划研究中存在的计算复杂、耗时长和成本高等问题,本研究基于改进的多准则决策(Multiple criteria decision making,MCDM)方法和人工神经网络(Artificial neural network,ANN),提出了一种风浪联合开发区划智能模型。为降低专家的主观偏差,应用基于层级的模糊权重评估(Fuzzy level based weight assessment,FLBWA)法来计算各评价指标权重;继而结合改进的Borda-全乘比例多目标优化(Borda-multi-objective optimization on the basis of ratio analysis plus full multiplicative form,Borda-MULTIMOORA)法计算开发适宜性指数,从而能够更加准确、高效地得到评价结果;之后,基于灰狼优化算法的反向传播(Grey wolf optimizer with back propagation,GWO-BP)神经网络构建并训练智能模型,将适宜性分析转化为自动化、高效化和智能化的过程;最后,以山东省风浪联合开发区划为例验证该模型的可行性和合理性。根据实例验证,该模型可以实现风浪联合开发区划的智能化,为相关领域的研究和政府规划提供参考。展开更多
基金the National Natural Science Foundations of China (60873099 )
文摘A fuzzy particle swarm optimization （PSO） on the basis of elite archiving is proposed for solving multi-objective optimization problems. First, a new perturbation operator is designed, and the concepts of fuzzy global best and fuzzy personal best are given on basis of the new operator. After that, particle updating equations are revised on the basis of the two new concepts to discourage the premature convergence and enlarge the potential search space; second, the elite archiving technique is used during the process of evolution, namely, the elite particles are introduced into the swarm, whereas the inferior particles are deleted. Therefore, the quality of the swarm is ensured. Finally, the convergence of this swarm is proved. The experimental results show that the nondominated solutions found by the proposed algorithm are uniformly distributed and widely spread along the Pareto front.
文摘To assist readers to have a comprehensive understanding, the classical and intelligent methods roundly based on precursory research achievements are summarized in this paper. First, basic conception and description about multi-objective (MO) optimization are introduced. Then some definitions and related terminologies are given. Furthermore several MO optimization methods including classical and current intelligent methods are discussed one by one succinctly. Finally evaluations on advantages and disadvantages about these methods are made at the end of the paper.
文摘This paper puts forward a new integrated design met ho d based on fuzzy matter-element optimization.On the based of analyzing the mod el of multi-objective fuzzy matter-element , the paper defines the m atter-element weightily and changes solving multi-objective fuzzy optimization into solving dependent function K(x) of the single-objective optimization according to the optimization criterion. The paper particularly describes the realization approach of GA process of multi -objective fuzzy matter-element optimization: encode, produce initial populati on, confirm fitness function, select operator, etc. In the process, the adaptive macro genetic algorithms (AMGA) is applied to enhancing the evolution speed. Th e paper improves the two genetic operators: crossover and mutation operator. The modified adaptive macro genetic algorithms (MAMGA) is put forward simultane ously. It is adopted to solve the optimization problem. Three optimization methods, namely fuzzy matter-element optimization method, li nearity weighted method and fuzzy optimization method, are compared by using the table and figure, it shows that not only MAMGA is a little better than the AMGA , but also it reaches the extent to which the effective iteration generation is 62.2% of simple genetic algorithms (SGA). By the calculation of optimum exam ple, the improved method of genetic in the paper is much better than the method in reference of paper.
文摘针对目前海洋能区划研究中存在的计算复杂、耗时长和成本高等问题,本研究基于改进的多准则决策(Multiple criteria decision making,MCDM)方法和人工神经网络(Artificial neural network,ANN),提出了一种风浪联合开发区划智能模型。为降低专家的主观偏差,应用基于层级的模糊权重评估(Fuzzy level based weight assessment,FLBWA)法来计算各评价指标权重;继而结合改进的Borda-全乘比例多目标优化(Borda-multi-objective optimization on the basis of ratio analysis plus full multiplicative form,Borda-MULTIMOORA)法计算开发适宜性指数,从而能够更加准确、高效地得到评价结果;之后,基于灰狼优化算法的反向传播(Grey wolf optimizer with back propagation,GWO-BP)神经网络构建并训练智能模型,将适宜性分析转化为自动化、高效化和智能化的过程;最后,以山东省风浪联合开发区划为例验证该模型的可行性和合理性。根据实例验证,该模型可以实现风浪联合开发区划的智能化,为相关领域的研究和政府规划提供参考。
