In this paper, we focus on multiobjective two-level simple recourse programming problems with discrete-type LR fuzzy random variables, in which each of the decision makers called the leader and the follower optimizes ...
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ISBN:
(纸本)9781728197326
In this paper, we focus on multiobjective two-level simple recourse programming problems with discrete-type LR fuzzy random variables, in which each of the decision makers called the leader and the follower optimizes his/her multiple objective functions independently, shortages and excesses arising from the violation of the constraints with discrete-type LR fuzzy random variables are penalized, and the sum of the objective function and the expectation of the amount of the penalties is minimized. To deal with such problems, we introduce new solution concepts called an optimistic and pessimistic Pareto Stackelberg solutions for the leader. It is shown that such optimistic and pessimistic Pareto Stackelberg solutions can be obtained by solving weighting problems of the leader. We propose an interactive algorithm to obtain a satisfactory solution of the leader from among an optimistic or pessimistic Pareto Stackelberg solution set.
In this paper, we focus on multiobjective two-level simple recourse programming problems with discrete-type LR fuzzy random variables, in which each of the decision makers called the leader and the follower optimizes ...
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In this paper, we focus on multiobjective two-level simple recourse programming problems with discrete-type LR fuzzy random variables, in which each of the decision makers called the leader and the follower optimizes his/her multiple objective functions independently, shortages and excesses arising from the violation of the constraints with discrete-type LR fuzzy random variables are penalized, and the sum of the objective function and the expectation of the amount of the penalties is minimized. To deal with such problems, we introduce a new solution concept called an estimated Pareto Stackelberg solution for the leader. To obtain a candidate of a satisfactory solution for the leader from among an estimated Pareto Stackelberg solution set, using the Kuhn-Tucker approach and the transformation technique for complementarity conditions, an original problem is transformed into a mixed integer programming problem. Then, we propose an interactive algorithm to obtain a satisfactory solution of the leader from among an estimated Pareto Stackelberg solution set. A numerical example illustrates the proposed algorithm for a multiobjective two-level fuzzy random simple recourse programming problem under the hypothetical leader.
This paper investigates the problem of efficiency measurement for parallel production systems where a number of processes are operating independently within the system, and some input/output data are fuzzy numbers. Wh...
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This paper investigates the problem of efficiency measurement for parallel production systems where a number of processes are operating independently within the system, and some input/output data are fuzzy numbers. When all observations have precise values. previous studies found that the system efficiency measured from a relational data envelopment analysis model is a weighted average of the process efficiencies. Based on the extension principle of fuzzy theory. this paper constructs a pair of two-level programming models to calculate the lower and upper bounds of the alpha-cuts of the fuzzy system and process efficiencies. It is shown that the fuzzy system efficiency is still a weighted average of the fuzzy process efficiencies. However, the weights need not be the same at different alpha levels. The case of measuring the teaching and research efficiencies of chemistry departments in UK universities with a qualitative factor of research quality discussed in the literature is used as an example to explain the idea of this paper. Fuzzy measures obtained from fuzzy observations are more informative than crisp measures obtained from assuming the fuzzy observations to be precise. (c) 2012 Elsevier B.V. All rights reserved.
In this study, a simulation-based multi-objective two-level optimization decision-making approach is developed for optimal irrigation water allocation, improving irrigation water productivity and controlling regional ...
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In this study, a simulation-based multi-objective two-level optimization decision-making approach is developed for optimal irrigation water allocation, improving irrigation water productivity and controlling regional accumulated salts. Techniques of multi-objective programming, two-level programming and simulation model of water and salt physical movement process are incorporated into the modeling framework. The simulated processes are parameterized and calibrated with field experimental data while the optimization model is used to generate optimal solutions though predefined objectives and the associated constraints. This model is applied to a case study on irrigation water allocation in the Jiefangzha Irrigation Subarea in Hetao Irrigation District, Northwest China. Firstly, the study area is delineated into several homogeneous irrigation decision-making units (IDMUs) for better characterizing their spatial variability because it's spatially heterogeneous. Afterwards, decomposition-coordination algorithm is introduced to solve such an integrated simulation-based multi-objective two-level optimization model. Finally, optimal solutions of irrigation water allocation for different crops during crop growth periods in different IDMUs can be obtained for supporting sustainable strategies of irrigation. The results can achieve balanced tradeoffs between different stakeholders (i.e., the upper-level decision-makers and the lower-level farmers) and between conflicting economic objectives and environmental objectives. Moreover, optimal solutions have a slight increase in economic returns over the baseline scenario (i.e., status quo), but the irrigation water productivity is increased by nearly 60% due to less irrigation water used. Regional accumulated salts can be controlled because the soil salinity is constrained within the predetermined salt accumulation constraint. Therefore, these findings can provide evidence for efficient use of irrigation water resources and furthe
Environmental water quality problems resulting from pollutant discharges have received extensive attention with the increasingly severe challenges facing global resources and the environment. A consideration of hierar...
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Environmental water quality problems resulting from pollutant discharges have received extensive attention with the increasingly severe challenges facing global resources and the environment. A consideration of hierarchy within water resources-environment system (WRES) management under uncertainty can effectively improve the accuracy and applicability of management decisions. This study developed an interval fuzzy-credibility constrained two-level programming (IFCTP) model for WRES planning which considers uncertain information through the use of interval values and fuzzy sets and can also resolve conflicting goals among decision-makers in different departments. The IFCTP-WRES model was then formulated and applied for planning of the middle route of South-to-North Water Diversion Project (SNWDP) in Henan Province, China. Multiple water allocation, pollution control, and economic benefit solutions encompassing three departments and thirteen water-receiving cities involving dual uncertainties and varied credibility levels were examined. The results showed that: (1) the proportion of water resources allocated to ecological flows should increase from [14.12, 14.15]% to [17.97, 17.99]% over the entire planning period;(2) the proportion of water resources allocated to small cities (e.g., Huaxian County) should show a constant increase;(3) municipal wastewater can contribute more than half of the total pollutant load;(4) as compared to the economic benefit that can be obtained through solutions identified by two single-objective models, the interval fuzzy-credibility constrained programming environmental management system (IFCP-EMS) model and interval fuzzy-credibility constrained programming water resources management system (IFCP-WMS) model, that by the IFCTP-WRES model has higher by 5.0% and lower by 4.5%, respectively. These findings can provide abundant alternatives for achieving sustainable development and can help decision-makers to effectively plan WRES management
China's national development and reform commission issued the "logistics industry adjustment and revitalization plan " in 2009 to support the development of agricultural product logistics and distributio...
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China's national development and reform commission issued the "logistics industry adjustment and revitalization plan " in 2009 to support the development of agricultural product logistics and distribution centers. China's agricultural product logistics and distribution have entered a stage of rapid development. With the rise of the sharing economy, logistics has become a bottleneck restricting the further development of agricultural product distribution. In order to realize the effective cooperation among the main body of agricultural product logistics distribution, improve the distribution efficiency and reduce the distribution cost, a logistics distribution optimization model based on the two-layer planning idea and genetic algorithm is proposed. A two-level programming model is constructed by combining qualitative and quantitative methods, theory and examples, and insertion and deletion operators are introduced to optimize the genetic algorithm. The research results show that the optimized genetic algorithm has a 54.55% increase in convergence speed, 1.08% in performance, and a 54.231% reduction in path length compared to the benchmark algorithm. It effectively improves the efficiency of path planning and saves the planning cost, and the final target value is reduced by 48.19%.
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