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.
In present article, we study a special class of nonlinear programming problems known as multiobjective mathematical programs with equilibrium constraints. We propose Wolfe type and Mond-Weir type dual models for multi...
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A robust optimization approach is proposed for generating nondominated robust solutions for multiobjective linear programming problems with imprecise coefficients in the objective functions and constraints. Robust opt...
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A robust optimization approach is proposed for generating nondominated robust solutions for multiobjective linear programming problems with imprecise coefficients in the objective functions and constraints. Robust optimization is used in dealing with impreciseness while an interactive procedure is used in eliciting preference information from the decision maker and in making tradeoffs among the multiple objectives. Robust augmented weighted Tchebycheff programs are formulated from the multiobjective linear programming model using the concept of budget of uncertainty. A linear counterpart of the robust augmented weighted Tchebycheff program is derived. Robust nondominated solutions are generated by solving the linearized counterpart of the robust augmented weighted Tchebycheff programs.
While road electrification offers economic and environmental advantages, the non-conventional load due to electric vehicles usage and charging patterns pose challenges to distribution systems. The strategic design of ...
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ISBN:
(纸本)9781728175836
While road electrification offers economic and environmental advantages, the non-conventional load due to electric vehicles usage and charging patterns pose challenges to distribution systems. The strategic design of charging infrastructure is becoming an essential element to facilitate power system planning and decision-making process. This paper presents a probabilistic method to derive charging patterns and estimate the electric vehicle demand profiles under uncertainty and variability. We apply a Gaussian copula to capture correlations between the key multi-variates. We investigate the optimal location and size of charging stations based on queueing theory and intercepted traffic flow model. We examine the impact of the charging demand occurred in residential and public area on distribution expansion investment and incremental operational cost. The feasibility of the approach is tested on an interconnected distribution grid and transportation system. The case studies show that a careful probabilistic analysis of the randomness intrinsic to the charging behavior is of great importance to define and implement an integrated power and transportation system design.
We propose and analyse a nonmonotone quasi-Newton algorithm for unconstrained strongly convex multiobjective optimization. In our method, we allow for the decrease of a convex combination of recent function values. We...
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We propose and analyse a nonmonotone quasi-Newton algorithm for unconstrained strongly convex multiobjective optimization. In our method, we allow for the decrease of a convex combination of recent function values. We establish the global convergence and local superlinear rate of convergence under reasonable assumptions. We implement our scheme in the context of BFGS quasi-Newton method for solving unconstrained multiobjective optimization problems. Our numerical results show that the nonmonotone quasi-Newton algorithm uses fewer function evaluations than the monotone quasi-Newton algorithm.
In this paper, we establish necessary and sufficient conditions to characterize weakly efficient solutions in nonsmooth quasiconvex multiobjective programming. The results are proved in terms of the Greenberg-Pierskal...
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In this paper, we establish necessary and sufficient conditions to characterize weakly efficient solutions in nonsmooth quasiconvex multiobjective programming. The results are proved in terms of the Greenberg-Pierskalla, Penot, Plastria, Gutierrez and Suzuki-Kuroiwa subdifferentials. The established results can be used to provide powerful tools for sketching numerical algorithms and deriving duality results.
With the rapid development of mobile communication technology and the continuous expansion of operation scale, the communication network becomes more and more complex. How to reasonably plan the location of base stati...
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With the rapid development of mobile communication technology and the continuous expansion of operation scale, the communication network becomes more and more complex. How to reasonably plan the location of base stations according to the existing weak coverage points has always been a difficult problem. By establishing a mathematical model and using the method of computer simulation, this paper optimizes the selection of station site and regional division. Considering that the establishment of the base station should meet that 90% of the traffic of the weak coverage points should be covered by the planned base station, and considering the loss and construction cost caused by repeated coverage, this paper takes the minimum total construction cost and the minimum repeated coverage as the optimization goal, and establishes a multi-objective programming model under the condition of meeting the priority coverage of the weak coverage points with high traffic, The corresponding solutions for station location selection and area division are given by using the method of computer simulation.
In this article, we focus on a class of a fractional interval multivalued programming problem. For the solution concept, LU-Pareto optimality and LS-Pareto, optimality are discussed, and some nontrivial concepts are a...
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In this article, we focus on a class of a fractional interval multivalued programming problem. For the solution concept, LU-Pareto optimality and LS-Pareto, optimality are discussed, and some nontrivial concepts are also illustrated with small examples. The ideas of LU-V-invex and LS-V-invex for a fractional interval problem are introduced. Using these invexity suppositions, we establish the Karush-Kuhn-Tucker optimality conditions for the problem assuming the functions involved to begH-differentiable. Non-trivial examples are discussed throughout the manuscript to make a clear understanding of the results established. Results obtained in this paper unify and extend some previously known results appeared in the literature.
This study proposed a novel cultivated land planning approach coupling expected irrigation water prediction and crop planting structure optimization. Under the guidance of the expected irrigation water prediction, the...
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This study proposed a novel cultivated land planning approach coupling expected irrigation water prediction and crop planting structure optimization. Under the guidance of the expected irrigation water prediction, the development of agricultural planting strategies was proposed through the cultivated land planning method to improve the efficiency of water use and ensure agricultural production. This approach was consisted of two models: a combination forecasting model was developed for estimating expected irrigation water with help of remote sensing data (RSCM);and a bi-level multiobjective programming model for planning crop planting structure (BMPSOM) was formulated for crop planting structure programming. Then, the proposed approach applied to a real-world case in Northwest China for verifying its validity. Results show that: 1) the forecast accuracy of the combination forecast model has been greatly improved compared to the single forecast model, the accuracy test results are RMSE = 0.25 & times;108 m3, MAPE = 0.78%;2) the use of remote sensing data can reflect the soil moisture with spatial variability in the forecast;3) BMPSOM model can well reflect the leader-follower relationship and make tradeoff among multiple objectives of each decision maker in tackling practical problem. Application has proved that the agricultural planting strategy formulated by this approach can not only ensure economic benefits but also increase food production under limited water resources. Therefore, this method has good application prospects in areas where water resources are scarce.
To fairly distribute limited irrigation water resources in arid regions, a water allocation priority evaluation method based on remote sensing data was proposed and integrated with an optimization model. First, the wa...
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To fairly distribute limited irrigation water resources in arid regions, a water allocation priority evaluation method based on remote sensing data was proposed and integrated with an optimization model. First, the water supply response unit was divided according to canal system conditions. Then, a spatialization method was used for generating spatial agricultural output value (income from planting industry) and grain yield (yield of food crops) with the help of NDVI and the potential yield of farmland. Third, the AHP-TOPSIS method was employed to calculate the water allocation priority based on the above information. Finally, the evaluation results were integrated with a nonlinear multiobjective model to optimally allocate agricultural land and water resources, considering the combined objective of minimum envy and proportional fairness. The method was applied to Hetao irrigation area, an arid agriculture-dominant region in Northwest China. After solving the model, optimization alternatives were obtained, which indicate that: (1) the spatial method of agricultural output value can improve the accuracy by around 16% compared with the traditional method, and the spatial method of grain yield also have good accuracy (MAPE = 14.66%);(2) the rank of water allocation priority can reflect more spatial information, and provide practical decision support for the distribution of water resources;(3) the envy index can better improve the efficiency of an allocation system compared to the Gini coefficient method.
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