In recent years, a large number of approaches to constrained multi-objective optimization problems(CMOPs) have been proposed, focusing on developing tweaked strategies and techniques for handling constraints. However,...In recent years, a large number of approaches to constrained multi-objective optimization problems(CMOPs) have been proposed, focusing on developing tweaked strategies and techniques for handling constraints. However, an overly finetuned strategy or technique might overfit some problem types,resulting in a lack of versatility. In this article, we propose a generic search strategy that performs an even search in a promising region. The promising region, determined by obtained feasible non-dominated solutions, possesses two general properties.First, the constrained Pareto front(CPF) is included in the promising region. Second, as the number of feasible solutions increases or the convergence performance(i.e., approximation to the CPF) of these solutions improves, the promising region shrinks. Then we develop a new strategy named even search,which utilizes the non-dominated solutions to accelerate convergence and escape from local optima, and the feasible solutions under a constraint relaxation condition to exploit and detect feasible regions. Finally, a diversity measure is adopted to make sure that the individuals in the population evenly cover the valuable areas in the promising region. Experimental results on 45 instances from four benchmark test suites and 14 real-world CMOPs have demonstrated that searching evenly in the promising region can achieve competitive performance and excellent versatility compared to 11 most state-of-the-art methods tailored for CMOPs.展开更多
In this paper, we present a new line search and trust region algorithm for unconstrained optimization problems. The trust region center locates at somewhere in the negative gradient direction with the current best ite...In this paper, we present a new line search and trust region algorithm for unconstrained optimization problems. The trust region center locates at somewhere in the negative gradient direction with the current best iterative point being on the boundary. By doing these, the trust region subproblems are constructed at a new way different with the traditional ones. Then, we test the efficiency of the new line search and trust region algorithm on some standard benchmarking. The computational results reveal that, for most test problems, the number of function and gradient calculations are reduced significantly.展开更多
首先分析潮流转移的原因及伴随的现象。其次讨论潮流转移区域以及区域界定,对传统广度优先遍历(breadth first search,BFS)算法进行改进,提出潮流转移影响区域的界定方法。对安全评估工作的理论基础——3个基本概念(模型量化、平均功率...首先分析潮流转移的原因及伴随的现象。其次讨论潮流转移区域以及区域界定,对传统广度优先遍历(breadth first search,BFS)算法进行改进,提出潮流转移影响区域的界定方法。对安全评估工作的理论基础——3个基本概念(模型量化、平均功率角和潮流转移灵敏度)分别进行定义。提出潮流转移模型及其灵敏度的表达式。提出安全评估的评估方法,建立安全评估的数学模型,最终得到安全评估的综合指标,并阐述了指标的使用。开发潮流转移灵敏度及安全评估程序,利用该程序对真实电网算例进行仿真验证。展开更多
基金partly supported by the National Natural Science Foundation of China(62076225)。
文摘In recent years, a large number of approaches to constrained multi-objective optimization problems(CMOPs) have been proposed, focusing on developing tweaked strategies and techniques for handling constraints. However, an overly finetuned strategy or technique might overfit some problem types,resulting in a lack of versatility. In this article, we propose a generic search strategy that performs an even search in a promising region. The promising region, determined by obtained feasible non-dominated solutions, possesses two general properties.First, the constrained Pareto front(CPF) is included in the promising region. Second, as the number of feasible solutions increases or the convergence performance(i.e., approximation to the CPF) of these solutions improves, the promising region shrinks. Then we develop a new strategy named even search,which utilizes the non-dominated solutions to accelerate convergence and escape from local optima, and the feasible solutions under a constraint relaxation condition to exploit and detect feasible regions. Finally, a diversity measure is adopted to make sure that the individuals in the population evenly cover the valuable areas in the promising region. Experimental results on 45 instances from four benchmark test suites and 14 real-world CMOPs have demonstrated that searching evenly in the promising region can achieve competitive performance and excellent versatility compared to 11 most state-of-the-art methods tailored for CMOPs.
文摘In this paper, we present a new line search and trust region algorithm for unconstrained optimization problems. The trust region center locates at somewhere in the negative gradient direction with the current best iterative point being on the boundary. By doing these, the trust region subproblems are constructed at a new way different with the traditional ones. Then, we test the efficiency of the new line search and trust region algorithm on some standard benchmarking. The computational results reveal that, for most test problems, the number of function and gradient calculations are reduced significantly.
文摘首先分析潮流转移的原因及伴随的现象。其次讨论潮流转移区域以及区域界定,对传统广度优先遍历(breadth first search,BFS)算法进行改进,提出潮流转移影响区域的界定方法。对安全评估工作的理论基础——3个基本概念(模型量化、平均功率角和潮流转移灵敏度)分别进行定义。提出潮流转移模型及其灵敏度的表达式。提出安全评估的评估方法,建立安全评估的数学模型,最终得到安全评估的综合指标,并阐述了指标的使用。开发潮流转移灵敏度及安全评估程序,利用该程序对真实电网算例进行仿真验证。