China's grain-for-green policy of converting steep cultivated land to forest and grassland is one of the most important initiatives to develop its western inland regions. Using a multi-objective programming model,...
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China's grain-for-green policy of converting steep cultivated land to forest and grassland is one of the most important initiatives to develop its western inland regions. Using a multi-objective programming model, this study assessed the impacts of this policy in the upper reaches of the Yangtze River and the upper and middle reaches of the Yellow River. In addition to the strategic planning of converting cultivated land to forest and grassland and its associated impacts, three other scenarios were simulated. Results showed that impacts on grain supply at the national level were in the range of 2-3%. These results suggest that the proposed policy might not have a major impact on China's future grain supply and the world grain market. At the local level, however, impacts could be significant. (c) 2004 Elsevier Ltd. All rights reserved.
This paper concerns our use of a Vehicle Routing Problem with Soft Time Window (VRPSTW) model to solve hospital patient transportation assignment problems. A model of multi-objective programming for the hospital staff...
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This paper concerns our use of a Vehicle Routing Problem with Soft Time Window (VRPSTW) model to solve hospital patient transportation assignment problems. A model of multi-objective programming for the hospital staff assignment is set up to minimize the transportation cost (over distances that patients are moved), and penalties are imposed (i.e., punishment for not meeting patient treatment location time windows). We propose a GA-based Heuristic problem solving technique to solve the problem. Our approach improves the efficiency of patient transportation staff assignment, which reduces cost, and meets satisfactory time constraints as shown in practical cases. Furthermore, we developed a Staffing Assignments Decision Support System (SADSS) to facilitate patient transport assignment.
This paper investigates Nash equilibrium under the possibility that preferences may be incomplete. I characterize the Nash-equilibrium-set of such a game as the union of the Nash-equilibrium-sets of certain derived ga...
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This paper investigates Nash equilibrium under the possibility that preferences may be incomplete. I characterize the Nash-equilibrium-set of such a game as the union of the Nash-equilibrium-sets of certain derived games with complete preferences. These games with complete preferences can be derived from the original game by a simple linear procedure, provided that preferences admit a concave vector-representation. These theorems extend some results on finite games by Shapley and Aumann. The applicability of the theoretical results is illustrated with examples from oligopolistic theory, where firms are modelled to aim at maximizing both profits and sales (and thus have multiple objectives). Mixed strategy and trembling hand perfect equilibria are also discussed.
We give a generic regularity condition under which each weakly efficient decision making unit in the CCR model of data envelopment analysis is also CCR-efficient. Then we interpret the problem of finding maximal param...
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We give a generic regularity condition under which each weakly efficient decision making unit in the CCR model of data envelopment analysis is also CCR-efficient. Then we interpret the problem of finding maximal parameters which preserve efficiency of CCR-efficient DMUs under directional perturbations as a general semi-infinite optimization problem and use a recently suggested numerical method for this problem class to calculate maximal directionally efficient DMUs. As a practical example we investigate the efficiency of Croatian banks under additive perturbations.
In this paper we show that the inverse data envelopment analysis (DEA) models can be used to estimate inputs for a decision making unit (DMU) when some or all outputs and efficiency level of this DMU are increased or ...
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In this paper we show that the inverse data envelopment analysis (DEA) models can be used to estimate inputs for a decision making unit (DMU) when some or all outputs and efficiency level of this DMU are increased or preserved. An approach is also introduced to identify extra inputs (maximum reduction amounts in inputs) when the outputs are estimated using the proposed models by Yan et al. [European Journal of Operational Research 136 (2002) 19] and Jahanshahloo et al. [Applied Mathematics and Computation 19 (2003)]. Numeric results are presented for an example taken from the literature. (C) 2003 Elsevier Inc. All rights reserved.
This paper examines the potential to use multiple objectiveprogramming to reduce nutrient excretion from dairy cows through incorporation of nutrient excretion functions into a ration formulation framework. In a typi...
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This paper examines the potential to use multiple objectiveprogramming to reduce nutrient excretion from dairy cows through incorporation of nutrient excretion functions into a ration formulation framework. In a typical ration formulation model, a ration is formulated to minimize cost while providing sufficient nutrients to meet the needs of the animal type being fed. To reduce the nutrient loading, rations can be formulated to minimize cost, and nitrogen and phosphorus excretion using multiple objectiveprogramming. Rations were initially formulated to minimize cost, nitrogen excretion and phosphorus excretion. Compromise programming was then utilized to examine the impacts on ration formulation of combining the three individual objectives. The multiple objective ration formulation reduced phosphorus excretion by 5% and marginally reduced nitrogen excretion with a small increase in ration cost compared to the single objective minimum cost ration. multiple objectiveprogramming does have the potential to reduce nutrient excretion. (C) 2001 Elsevier Science Ltd. All rights reserved.
This paper investigates strategies to reduce CO2 emissions from the power sector of Taiwan. A multi-objective mix integer model for power generation strategy in Taiwan is proposed. A power supply problem with integer ...
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This paper investigates strategies to reduce CO2 emissions from the power sector of Taiwan. A multi-objective mix integer model for power generation strategy in Taiwan is proposed. A power supply problem with integer constraints on lowest power generation to meet the practical operation of power unit is also presented. This model can be used to plan future power units' expansion strategy, as well as to study the effect of CO2 emission constraints. Further, this model is used to investigate optimal strategies for stabilizing CO2 emissions to the desired level from the power sector in Taiwan;these accounted for about 40% of CO2 emissions in the country in 2000. Real operational data from the Taiwan Power Company are used for testing the model effectiveness. In addition, recommendations are made for implementation. (C) 2004 Elsevier Ltd. All rights reserved.
This paper develops a multi-objective optimization model for the passenger train-scheduling problem on a railroad network which includes single and multiple tracks, as well as multiple platforms with different train c...
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This paper develops a multi-objective optimization model for the passenger train-scheduling problem on a railroad network which includes single and multiple tracks, as well as multiple platforms with different train capacities. In this study, lowering the fuel consumption cost is the measure of satisfaction of the railway company and shortening the total passenger-time is being regarded as the passenger satisfaction criterion. The solution of the problem consists of two steps. First the Pareto frontier is determined using the e-constraint method, and second, based on the obtained Pareto frontier detailed multi-objective optimization is performed using the distance-based method with three types of distances. Numerical examples are given to illustrate the model and solution methodology. (C) 2004 Elsevier Ltd. All rights reserved.
Optimization of a multi-reservoir system operation is challenging due to the non-linearity, stochasticity, and dimensionality involved in such a problem. In this research, a long-term planning model is presented for o...
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Optimization of a multi-reservoir system operation is challenging due to the non-linearity, stochasticity, and dimensionality involved in such a problem. In this research, a long-term planning model is presented for optimizing the operation of Iranian Karoon-Dez reservoir system using an interior-point algorithm. The system is the largest multi-purpose reservoir system in Iran with hydropower generation, water supply, and environmental objectives-The focus is on resolving the dimensionality of this problem while considering hydropower generation and water supply objectives. The weighting and constraints methods of multi-objective programming are used to assess the trade-off between water supply and hydropower objectives so as to find noninferior solutions. The computational efficiency of the proposed approach is demonstrated using historical data taken from Karoon-Dez reservoir system.
This paper develops a model for determining locations of undesirable facilities. It is formulated as multiobjective since the problem of locating undesirable facilities faces many conflicting criteria. A method is als...
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This paper develops a model for determining locations of undesirable facilities. It is formulated as multiobjective since the problem of locating undesirable facilities faces many conflicting criteria. A method is also proposed to appropriately address uncertainty associated with this class of location problems. The methodology developed in this study is tested using the real-world data. (C) 2003 Elsevier Ltd. All rights reserved.
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