Energy policies and technological progress in the development of wind turbines have made wind power the fastest growing renewable power source worldwide. The inherent variability of this resource requires special atte...
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Energy policies and technological progress in the development of wind turbines have made wind power the fastest growing renewable power source worldwide. The inherent variability of this resource requires special attention when analyzing the impacts of high penetration on the distribution network. A time-series steady-state analysis is proposed that assesses technical issues such as energy export, losses, and short-circuit levels. A multiobjective programming approach based on the nondominated sorting genetic algorithm (NSGA) is applied in order to find configurations that maximize the integration of distributed wind power generation (DWPG) while satisfying voltage and thermal limits. The approach has been applied to a medium voltage distribution network considering hourly demand and wind profiles for part of the U.K. The Pareto optimal solutions obtained highlight the drawbacks of using a single demand and generation scenario, and indicate the importance of appropriate substation voltage settings for maximizing the connection of MPG.
We propose a model for the design of protected habitat reserves, which maximizes the number of species represented at least once in a limited set of reserved sites or parcels. Most models for reserve design do not dif...
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We propose a model for the design of protected habitat reserves, which maximizes the number of species represented at least once in a limited set of reserved sites or parcels. Most models for reserve design do not differentiate eligible habitat sites by their size. Also, they assume that protection is guaranteed through the selection of one site for any species, not taking into consideration that habitat needs vary from species to species. Our model acknowledges the fact that different species require reserves of different sizes, and that these reserves should be compact areas, as opposed to a set of disconnected parcels. Computational experience is shown on a landscape modeled as a regular grid, in which individual species require 1-, 2- or 4-parcel compact reserves. The results are compared to output from a Maximum Species Covering Model. (C) 2006 Elsevier Ltd. All rights reserved.
In this paper, we establish characterizations for efficient solutions to multiobjective programming problems, which generalize the characterization of established results for optimal solutions to scalar programming pr...
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In this paper, we establish characterizations for efficient solutions to multiobjective programming problems, which generalize the characterization of established results for optimal solutions to scalar programming problems. So, we prove that in order for Kuhn-Tucker points to be efficient solutions it is necessary and sufficient that the multiobjective problem functions belong to a new class of functions, which we introduce. Similarly, we obtain characterizations for efficient solutions by using Fritz-John optimality conditions. Some examples are proposed to illustrate these classes of functions and optimality results. We study the dual problem and establish weak, strong and converse duality results. (C) 2007 Published by Elsevier Ltd.
We take into consideration the first-order sufficient conditions, established by Jimenez and Novo (Numer. Funct. Anal. Optim. 2002;23: 303-322) for strict local Pareto minima. We give here a more operative condition f...
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We take into consideration the first-order sufficient conditions, established by Jimenez and Novo (Numer. Funct. Anal. Optim. 2002;23: 303-322) for strict local Pareto minima. We give here a more operative condition for a strict local Pareto minimum of order 1.
In this brief, objective prioritization of multiobjective cost functions using the lexicographic approach is applied in the model predictive control (MPC) framework of sewer networks. Using the lexicographic approach,...
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In this brief, objective prioritization of multiobjective cost functions using the lexicographic approach is applied in the model predictive control (MPC) framework of sewer networks. Using the lexicographic approach, the control problem solution can be obtained by solving a sequence of single objective, constrained, convex programming problems. This brief demonstrates with an elaborated case study treating a portion of the Barcelona sewer network, that important improvements can be achieved in performance using lexicographic optimization. At the same time, costly commissioning and implementation efforts related to the traditional weight based approach for implementation of priorities are avoided.
In this paper, a pair of multiobjective fractional variational symmetric dual problems over cones is formulated. Weak, strong and converse duality theorems are established under generalized F-convexity assumptions. Mo...
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In this paper, a pair of multiobjective fractional variational symmetric dual problems over cones is formulated. Weak, strong and converse duality theorems are established under generalized F-convexity assumptions. Moreover, self duality theorem is also discussed. (C) 2007 Elsevier B.V. All rights reserved.
In this paper, a graphical characterization, in the decision space, of the properly efficient solutions of a convex multiobjective problem is derived. This characterization takes into account the relative position of ...
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In this paper, a graphical characterization, in the decision space, of the properly efficient solutions of a convex multiobjective problem is derived. This characterization takes into account the relative position of the gradients of the objective functions and the active constraints at the given feasible solution. The unconstrained case with two objective functions and with any number of functions and the general constrained case are studied separately. In some cases, these results can provide a visualization of the efficient set, for problems with two or three variables. Besides, a proper efficiency test for general convex multiobjective problems is derived, which consists of solving a single linear optimization problem.
We present a method of obtaining some classes of generalized V-univex type-I multiobjective optimization problems starting from classes of problems involving functions defined on R". In this way, examples of mult...
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ISBN:
(纸本)9789955282839
We present a method of obtaining some classes of generalized V-univex type-I multiobjective optimization problems starting from classes of problems involving functions defined on R". In this way, examples of multiobjective optimization problems given in previous articles, which are mentioned in the references, can be reformulated as optimization problems with generalized vectorial functions and having the same properties as the original ones.
Rural-urban land conversion is an inevitable phenomenon in urbanization arid industrialization. And the decision-making issue about this conversion is multi-objective because the social decision maker (the whole of c...
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Rural-urban land conversion is an inevitable phenomenon in urbanization arid industrialization. And the decision-making issue about this conversion is multi-objective because the social decision maker (the whole of central government and local authority) has to integrate the requirements of different interest groups (rural collective economic organizations, peasants, urban land users and the ones affected indirectly) and harmonize the sub-objects (economic, social and ecological outcomes) of this land allocation process. This paper established a multi-objective programming model for rural-urban land conversion decision-making and made some social welfare analysis correspondingly. Result shows that the general object of rural-urban land conversion decision-making is to reach the optimal level of social welfare in a certain state of resources allocation, while the preference of social decision makers and the value judgment of interest groups are two crucial factors which determine the realization of the rural-urban land conversion decision-making objects.
As a complex system, the urban environment usually presents multiobjective, uncertain, and dynamic characteristics, which leads to difficulties in urban environmental planning. In this study, an interval fuzzy multiob...
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As a complex system, the urban environment usually presents multiobjective, uncertain, and dynamic characteristics, which leads to difficulties in urban environmental planning. In this study, an interval fuzzy multiobjective programming method is proposed for tackling such problems and the associated solution algorithm is also discussed. Based on the proposed method, an interval fuzzy multiobjective environment planning model is further developed with specific focus on urban systems. The proposed approach allows uncertainties and comprehensive interaction of system components to be effectively communicated into the optimisation process. Furthermore, using scenario analysis and interactive solution processes, stakeholder preferences are efficiently integrated, promoting feasibility and robustness of decisions. The developed model was tested by a real-world case study in Kunming City, China. An analysis of the results shows that the proposed approach is an effective means for urban environmental planning.
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