共查询到20条相似文献,搜索用时 140 毫秒
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为解决多Agent一对多、多议题协商问题,提出了具有议题属性协商阶段的多阶段协商模型,设计了一种根据Agent让步幅度变化所形成的曲线来判定Agent类型和使用何种协商方法的协商策略.详细地分析了多Agent、多阶段一对多协商的协商过程.将三角模糊数多属性决策方法引入到多Agent协商过程中降低了决策者评估对方所提出方案的难度,能更自然地对不同方案的优劣进行排序.模拟算例表明,该模型有效且可行,为多Agent协商提供可参考的模型和求解算法. 相似文献
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大型厂矿、建筑工地以及大范围游乐场所的照明设施,因面积大、距离远,为了开关灯的方便常采用多地控制。这里介绍一种多灯多地控制电路的制作方法。如图所示:它是一个三路灯三 相似文献
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在IT产业迅猛发展的今天,网络技术已深入到各行各业。许多高校更纷纷建立了校园网。电教中心的主要任务就是运用最新的科学技术提高教学质量和效率,因此各校都把工作重点放在网络教学以及远程教学上。但是我校五山校区电教中心只有一个校网络中心分配的IP地址(202.116.159.134),远远满足不了中心各室人员上网的要求。为了增加上网站点,也为了构造一个网络教与学的开发、研究、应用环境,共享软硬件资源,我们构建了一个内部网络(Intranet)。网络连接如图1所示。1 网络结构网络的拓扑结构有星型、总线型、树型、网状型等。我们采… 相似文献
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针对差分进化算法在解决大规模多目标优化问题时,出现优化后期多样性不足、收敛速度慢等问题,提出一种多群多策略差分大规模多目标优化算法.根据个体特性不同,将种群分为3个等级不同的子群,利用多群策略的优势维持种群多样性.为减少种群陷入局部最优的概率,在不同等级的子群中引入多个变异策略以较好地平衡子群个体的多样性和收敛性.为保证不同子群间信息得到有效交换,根据3个子群的进化状态确定重新分群时机,既保证个体在本群内得到充分进化,又保证个体在一定的条件下进行信息交换.为利用更多的信息生成优秀的子代,将更新后的子群与其父代子群合并,选出下一代子群.为验证所提出算法的有效性,在一组大规模基准测试问题上评估算法的性能,实验结果表明,所提出算法在两个常用测试指标IGD和HV上明显优于其他对比算法. 相似文献
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涉及多个签名人的代理签名体制有三类:第一类称为代理多签名体制;第二类称为多代理签名体制;第三类称为多代理多签名体制。针对Lee等人的强代理签名方案和代理多签名方案中的安全缺陷,给出了新的改进方案,新方案能有效地防止原始签名人的伪造攻击,在改进方案的基础上给出了安全的多代理签名方案和多代理多签名方案。 相似文献
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本文提出了多变量系统多指标最优设计法,此方法既能保证设计人员对所预计的最优极
点心中有数,又能使多变量系统的各子系统分别满足不同的最优性能指标和实现全系统的最
优控制.本设计法以一个配水系统的子系统为例,进行了数字仿真.仿真结果说明本设计法
具有灵活性、简易性和准确性. 相似文献
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将门限签名体制引入到多代理多签名方案中,首次提出了一个门限多代理多签名方案.新方案不仅能实现多个原始签名人将签名权委托给多个代理签名人,还能将每个代理人的密钥进行分享,实现一定数量的原始签名人就能授权,一定数量的代理签名人就能产生有效的代理签名.另外,新方案还可以控制代理签名的有效时间和回收代理签名权. 相似文献
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多Agent多问题协商模型 总被引:42,自引:1,他引:42
在多agent环境中,协商是多agent系统能够成功运转的关键.根据参与协商agent的数目和协商问题的数目,多agent环境中的协商可以分为双边-单问题协商、双边-多问题协商、多边-单问题协商、多边-多问题协商.前3种协商是多边-多问题协商在不同维上的简化.利用协商-协商过程-协商线程的概念建立了一个多边-多问题协商模型MMN(multi-agent multi-issue negotiation).该模型通过提供一个灵活的协商协议支持多agent环境中的不同协商形式,并且支持agent在协商过程中的学习. 相似文献
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A. N. Voronin 《Cybernetics and Systems Analysis》2012,48(2):227-232
An approach is proposed to solve a vector optimization problem for complex engineering and economic systems where the information
about experimental and statistical data necessary to set up regression models is insufficient (or absent). To solve this problem,
multiobjective optimization with nonlinear trade-off scheme is employed. 相似文献
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文章用进化算法给出了求解二层字典分层多目标最优化的方法,该算法把求解问题转化为多目标最优化,并研究了这两个问题的解集之间的联系。对多目标最优化定义了一个新的选择算子和适应值函数,这样定义的选择算子和适应值函数结合均匀设计能有效地引导搜索,直接求出问题的解而不用逐层求解。数值模拟表明该方法十分有效。 相似文献
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Shubhangi Deshpande Layne T. Watson Robert A. Canfield 《Optimization methods & software》2016,31(1):110-133
A new Pareto front approximation method is proposed for multiobjective optimization problems (MOPs) with bound constraints. The method employs a hybrid optimization approach using two derivative-free direct search techniques, and intends to solve black box simulation-based MOPs where the analytical form of the objectives is not known and/or the evaluation of the objective function(s) is very expensive. A new adaptive weighting scheme is proposed to convert a multiobjective optimization problem to a single objective optimization problem. Another contribution of this paper is the generalization of the star discrepancy-based performance measure for problems with more than two objectives. The method is evaluated using five test problems from the literature, and a realistic engineering problem. Results show that the method achieves an arbitrarily close approximation to the Pareto front with a good collection of well-distributed nondominated points for all six test problems. 相似文献
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两层多目标规划的罚函数法 总被引:4,自引:0,他引:4
研究了一类非线性两层多目标规划问题.在下层多目标规划问题的目标函数是严格凸函
数、决策变量约束集是凸集的假设下,通过将两层多目标规划问题转化成一系列单层多目标规划
问题,建立了两层多目标规划的罚函数理论,并进行了收敛性分析.从而丰富了两层多目标规划的
理论,为解决实际中的两层多目标决策问题提供了有力的工具. 相似文献
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Environmental economic dispatch of fixed head of hydrothermal power systems is viewed as a mulitobjective optimization problem in this paper. The practical hydrothermal system possesses various constraints which make the problem of finding global optimum difficult. This paper develops an improved multiobjective estimation of distribution algorithm to solving the above problem. A local learning operation is added into the original regularity model-based multiobjective estimation of distribution algorithm (RM-MEDA) in the improved approach so as to improve the local search ability and enhance the convergence efficiency. Furthermore, a repair mechanism is employed to repair the searched infeasible solutions in order to be able to search in the feasible region. In the experiment, the results obtained by the proposed approach have been compared with those from other three MOEAs: NSGA-II, NNIA, and RM-MEDA. Results from some pervious reported methods have also been employed to compare with our method. In addition, the results demonstrate the superiority of this proposed method as a promising MOEA to solve this power system multiobjective optimization problem. 相似文献
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E.E. Ammar 《Information Sciences》2008,178(2):468-484
In this paper, a multiobjective quadratic programming problem fuzzy random coefficients matrix in the objectives and constraints and the decision vector are fuzzy variables is considered. First, we show that the efficient solutions fuzzy quadratic multiobjective programming problems series-optimal-solutions of relative scalar fuzzy quadratic programming. Some theorems are to find an optimal solution of the relative scalar quadratic multiobjective programming with fuzzy coefficients, having decision vectors as fuzzy variables. An application fuzzy portfolio optimization problem as a convex quadratic programming approach is discussed and an acceptable solution to such problem is given. At the end, numerical examples are illustrated in the support of the obtained results. 相似文献
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In this paper, we propose an algorithm based on the clonal selection principle to solve multiobjective optimization problems (either constrained or unconstrained). The proposed approach uses Pareto dominance and feasibility to identify solutions that deserve to be cloned, and uses two types of mutation: uniform mutation is applied to the clones produced and non-uniform mutation is applied to the not so good antibodies (which are represented by binary strings that encode the decision variables of the problem to be solved). We also use a secondary (or external) population that stores the nondominated solutions found along the search process. Such secondary population constitutes the elitist mechanism of our approach and it allows it to move towards the true Pareto front of a problem over time. Our approach is compared with three other algorithms that are representative of the state-of-the-art in evolutionary multiobjective optimization. For our comparative study, three metrics are adopted and graphical comparisons with respect to the true Pareto front of each problem are also included. Results indicate that the proposed approach is a viable alternative to solve multiobjective optimization problems. 相似文献
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Multiobjective firefly algorithm for continuous optimization 总被引:3,自引:0,他引:3
Xin-She Yang 《Engineering with Computers》2013,29(2):175-184
Design problems in industrial engineering often involve a large number of design variables with multiple objectives, under complex nonlinear constraints. The algorithms for multiobjective problems can be significantly different from the methods for single objective optimization. To find the Pareto front and non-dominated set for a nonlinear multiobjective optimization problem may require significant computing effort, even for seemingly simple problems. Metaheuristic algorithms start to show their advantages in dealing with multiobjective optimization. In this paper, we extend the recently developed firefly algorithm to solve multiobjective optimization problems. We validate the proposed approach using a selected subset of test functions and then apply it to solve design optimization benchmarks. We will discuss our results and provide topics for further research. 相似文献