Conventional power distribution system is evolving with the growth of distributed generation and electric vehicle integration. The methods of this multidisciplinary planning under uncertainty have not yet been closely...
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ISBN:
(数字)9781728160214
ISBN:
(纸本)9781728160214
Conventional power distribution system is evolving with the growth of distributed generation and electric vehicle integration. The methods of this multidisciplinary planning under uncertainty have not yet been closely examined. In this work, we propose a framework for distribution network expansion planning considering the stochastic nature of DGs, charging stations associated with carbon impact. The proposed model aims to minimize the overall investment cost, the operation and maintenance cost, energy losses and carbon emissions by optimizing alternative feeder routes, the reinforcement of existing substations or new constructions, and the deployment of DGs and charging stations. A multiobjective mixed-integer nonlinear programme is formulated and recast as a two-stage stochastic problem based on analytical probabilistic approach. The model is solved with Tchebycheff decomposition method based evolutionary algorithm. The proposed approach is examined with a modified case-54 distribution and node-25 transportation system. Sensitivity analysis proves carbon emissions can influence the overall investment cost up to 21%. System cost and energy loss has the potential of 1.5% reduction by integrating wind generators. Numerical results obtained effectively demonstrate the capability and feasibility of proposed method.
This paper extends the defensive location problem (DLP), proposed by Uno and Katagiri, considering the situations that the defender locates defensive facilities for preventing invaders from reaching some important ver...
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ISBN:
(纸本)9781424473175
This paper extends the defensive location problem (DLP), proposed by Uno and Katagiri, considering the situations that the defender locates defensive facilities for preventing invaders from reaching some important vertices in a network. Their DLPs assumed that invaders, with a given energy, exist on a given vertex in it. On the other hand, this paper considers a new DLP that invaders' sites and energies are given uncertainly. By representing their existing vertices and energies as random variables with scenarios, the new DLP can be formulated as a multiobjective bilevel stochastic programming problem. In order to find a satisficing solution of the decision maker for the multiobjective DLP, an interactive fuzzy satisficing method with tabu search algorithm based on strategic oscillation is proposed. The efficiency of the proposed method is shown by applying it to numerical examples of the DLPs.
The combat environment of Unmanned Aerial Vehicles (UAVs) is filled with uncertain factors, which is complex and dynamic. This paper is devoted to the UAV mission planning problem under uncertain environment with thre...
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ISBN:
(纸本)9783038351153
The combat environment of Unmanned Aerial Vehicles (UAVs) is filled with uncertain factors, which is complex and dynamic. This paper is devoted to the UAV mission planning problem under uncertain environment with three optimization objectives, such as flight time, fuel usage and threat imposed by enemy. Based on the uncertainty theory and multiobjective programming method, the UAV uncertain multiobjective mission plaaning model is built and solved.
In this paper, we propose an interactive algorithm for multiobjective bimatrix games with fuzzy payoffs. Using necessity measure and the weighted Tchebycheff norm method, an equilibrium solution concept is defined, wh...
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ISBN:
(纸本)9789897585340
In this paper, we propose an interactive algorithm for multiobjective bimatrix games with fuzzy payoffs. Using necessity measure and the weighted Tchebycheff norm method, an equilibrium solution concept is defined, which depends on weighting vectors specified by each player. Since it is very difficult to obtain such equilibrium solutions directly, instead of equilibrium conditions in the necessity measure space, equilibrium conditions in the expected payoff space are provided. Under the assumption that a player can estimate the opponent player's preference as the weighting vector of the weighted Tchebycheff norm method, the interactive algorithm is proposed to obtain a satisfactory solution of the player from among an equilibrium solution set by updating the weighting vector.
We define the multiobjective Quadratic Assignment Problem. Because of the difficulties of the weighted objectives method we develop local algorithms which are based in the methodologies of efficient, lexicographic and...
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For a nonsmooth multiobjective nonlinear program which involves inequality and equality constraints. Fritz John and Kuhn-Tucker type sufficient optimality conditions are obtained. Some duality theorems are also establ...
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For a nonsmooth multiobjective nonlinear program which involves inequality and equality constraints. Fritz John and Kuhn-Tucker type sufficient optimality conditions are obtained. Some duality theorems are also established for Mond-Weir type of duals. All results are given under generalized convexity assumptions.
In this paper, we have considered a class of constrained nonsmooth multiobjective programming problem involving semi-directionally differentiable functions from a view point of generalized convexity. A newgeneralized ...
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In this paper, we have considered a class of constrained nonsmooth multiobjective programming problem involving semi-directionally differentiable functions from a view point of generalized convexity. A newgeneralized class of (d(I)-.rho-sigma)-V-type I univex functions is introduced under which various weak, strong, converse and strict converse duality theorems are established for Mond- Weir type dual program in order to relate the efficient and weak efficient solutions of primal and dual problem. Also, we have illustrated through various non- trivial examples that this class extends many earlier studied classes in literature.
Optimality conditions and several duality results are established under convexity and generalizedρconvexity assumptions for constrained multiobjective measurable subset selection problems
Optimality conditions and several duality results are established under convexity and generalizedρconvexity assumptions for constrained multiobjective measurable subset selection problems
Multipurpose operation is adopted by most reservoirs in Taiwan in order to maximize the benefits of power generation, water supply, irrigation and recreational purposes. A multiobjective approach can be used to obtain...
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Multipurpose operation is adopted by most reservoirs in Taiwan in order to maximize the benefits of power generation, water supply, irrigation and recreational purposes. A multiobjective approach can be used to obtain trade-off curves among these multipurpose targets. The weighting method, in which different weighting factors are used for different purposes, was used in this research work. In Taiwan, most major reservoirs are operated by rule curves. Genetic algorithms with characteristics of artificial intelligence were applied to obtain the optimal rule curves of the multireservoir system under multipurpose operation in Chou-Shui River Basin in central Taiwan. The model results reveal that different shapes of rule curves under different weighting factors on targets can be efficiently obtained by genetic algorithms. Pareto optimal solutions for a trade-off between water supply and hydropower were obtained and analyzed.
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