多目标规划
- 网络multiobjective programming;Goal Programming;MOP
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共同配送中的车货配载问题多目标规划研究
MOP about the Matched Problem of Wagons and Cargo in Common Distribution
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多目标规划模型的建立则是以生态承载力、人口总量和海洋产业产值为目标函数,从海洋环境容量约束、资源约束入手。
Meanwhile , taking ecological carrying capacity , population and total output value of marine industry as the objective function , and considering the constraints of marine environment carrying capacity and marine resouces , the study have tried to set up MOP model .
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这些结果对于讨论具有控制锥的Fuzzy多目标规划是有用的。
These results are useful to investigate fuzzy multiobjective programming with domination cone .
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多目标规划问题的FUZZY像集和FUZZY点
Fuzzy Image Set and Fuzzy Point of the Problem of Multiple Objective Programming
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具有Fuzzy约束的非光滑多目标规划的Fuzzy强有效解的最优性条件
Optimal conditions for fuzzy strong efficient solutions in Nonsmooth Multiobjective Programming with fuzzy constraints
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具有Fuzzy约束的多目标规划的σ-有效解和α-弱有效解
α - efficient solutions and α - weak efficient solutions in multiobjective programming with fuzzy constraints
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后者是一类非线性多目标规划问题,我们把它称为B运输问题。
The later is a nonlinear multiobjective programming , and it is called B Transportation Problem .
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G-(F,ρ)凸意义下多目标规划真有效解的对偶性
Duality for multiobjective programming with g - ( f ,ρ) convexity
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约束中具有Fuzzy参数的多目标规划(Ⅰ)&解的定义及其性质
MULTIOBJECTIVE PROGRAMMING PROBLEMS WITH FUZZY PARAMETERS IN TEH CONSTRAINTS ( I ) & The Definition And Properties of Solutions
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不可微B-凸多目标规划
Nondifferentiable B-vex multiobjective programming
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QoS路由策略的双水平-多目标规划模型
The Model of Bilevel - Multiobjective Programming for QoS Routing Protocal
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QoS组播路由问题的多目标规划模型研究
A New Multi-Objective Programming Model of Qos-based Multicast Routing Problem
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非光滑Fuzzy多目标规划的Fuzzy有效解的Mond-weir型对偶定理
Mond-Weir type Duality for Fuzzy Efficient Solutions in Nonsmooth Fuzzy Multiobjective Programming
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多目标规划Pareto最优解的几个充分条件
Several sufficient conditions of Pareto optimum solution of multi objective programming
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基于多目标规划的DEA有效性研究
Research on DEA Efficiency Based on Multi-Objective Programming
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在此基础上,讨论了评价供应商的DEA模型与多目标规划模型。
Then DEA models and multi-objective linear programming models for vendor selection are compared .
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在(F,ρ)s-凸函数的基础上,给出了多目标规划的两个逆对偶定理。
On the basis of ( F ,ρ) _s Convex functions two converse dual theorems of multiobjective programming are given under .
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求解多目标规划问题的Pareto多目标遗传算法
A Pareto Multi-Objective Genetic Algorithm for Multi-Objective Programming Problem
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讨论多目标规划问题中的有效点集的闭性和Pareto有效解集的闭性问题。
This paper discusses closeness of pareto efficient set and efficient outcome set .
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基于多目标规划的DEA
DEA Based on Mutiple Objective Programming
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ODE法在多目标规划中的应用
Application of the Method of Ordinary Differential Equations in Multiobjective Programming
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针对模型中不确定参数的模糊随机性,利用模糊随机规划的方法和STEP多目标规划方法求解多目标模糊随机规划问题。
Because of the fussy random parameters in the model , approaches of fussy random programming and STEP multi-objects programming are used to solve the multi-objects model with fussy random parameters .
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采用VISUALBASIC语言编制电梯群控系统的仿真软件,建立仿真环境,同时嵌入最小等待时间算法和多目标规划算法,进行仿真比较分析。
The least waiting time and multi-objective planning algorithm are embedded in the simulating software and environment which are programmed with Visual Basic . The simulating result proves the superiority of multi-objective planning algorithm .
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多目标规划的ak较多有效点与ak较多最优点
Ak - Major Efficient Points and Ak - Major Optimal Points
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NoC设计中的映射属于NP问题,而面向能耗和延时的映射求解又属于多目标规划问题。
Meanwhile , energy - and latency - aware mapping problem is a Multiple Objective Programming .
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基于QFD的产品多目标规划模型
Multi - Goal Programming Model Based on QFD
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广义凸多目标规划的Wolfe型对偶定理
The Wolfe Type Duality in the Generalized Convex Multiobjective Programming
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我们利用p级数方法求解多目标规划问题MOP,并用分层法的思想确定权系数。
We use p series method to solve the multi objective programming problem MOP , and put the idea of hierarchy onto the ascertain of function power .
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多目标规划Hartley真有效解的对偶性
Duality of multiobjective programming for Hartley proper efficient solution
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然后对一般类型的多目标规划问题,定义了Hα-共轭对偶问题,证明了弱对偶定理,并利用Hα-次可微性证明了在一定条件下的强对偶定理。
The H α conjugate duality programming for general multiobjective programming and its weak duality theorem were proposed . Then the strong duality theorem under some conditions was proved using H α subdifferential .