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Game theory and fuzzy programming approaches for bi-objective optimization of reservoir watershed management: a case study in Namazgah reservoir

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ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH 2015年第9期22卷 6546-6558页

作者： Ucler, N. Engin, G. Onkal Kocken, H. G. Oncel, M. S. Gebze Tech Univ Dept Environm Engn TR-41400 Gebze Turkey Yildiz Tech Univ Fac Civil Engn Dept Environm Engn TR-34220 Istanbul Turkey Yildiz Tech Univ Fac Chem Met Engn Dept Math Engn TR-34220 Istanbul Turkey

In this study, game theory and fuzzy programming approaches were used to balance economic and environmental impacts in the Namazgah reservoir, Turkey. The main goals identified were to maximize economic benefits of land use and to protect water quality of reservoir and land resources. Total phosphorous load (kg ha(-1) year(-1)) and economic income (USD ha(-1) year(-1)) from land use were determined as environmental value and economic value, respectively. The surface area of existing land use types, which are grouped under 10 headings according to the investigations on the watershed area, and the constraint values for the watershed were calculated using aerial photos, master plans, and basin slope map. The results of fuzzy programming approach were found to be very close to the results of the game theory model. It was concluded that the amount of fertilizer used in the current situation presents a danger to the reservoir and, therefore, unnecessary fertilizer use should be prevented. Additionally, nuts, fruit, and vegetable cultivation, instead of wheat and corn cultivation, was found to be more suitable due to their high economic income and low total phosphorus (TP) load. Apart from agricultural activities, livestock farming should also be considered in the area as a second source of income. It is believed that the results obtained in this study will help decision makers to identify possible problems of the watershed.

关键词： Reservoir watershed management Game theory fuzzy programming Bi-objective optimization

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Development of a fuzzy-stochastic programming with Green Z-score criterion method for planning water resources systems with a trading mechanism

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ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH 2016年第24期23卷 25245-25266页

作者： Zeng, X. T. Huang, G. H. Li, Y. P. Zhang, J. L. Cai, Y. P. Liu, Z. P. Liu, L. R. Capital Univ Econ & Business Beijing 10070 Peoples R China Univ Regina Inst Energy Environm & Sustainable Commun Regina SK S4S 0A2 Canada Beijing Normal Univ Coll Environm Beijing 100875 Peoples R China North China Elect Power Univ MOE Key Lab Reg Energy Syst Optimizat Beijing 102206 Peoples R China

This study developed a fuzzy-stochastic programming with Green Z-score criterion (FSGZ) method for water resources allocation and water quality management with a trading-mechanism (WAQT) under uncertainties. FSGZ can handle uncertainties expressed as probability distributions, and it can also quantify objective/subjective fuzziness in the decision-making process. Risk-averse attitudes and robustness coefficient are joined to express the relationship between the expected target and outcome under various risk preferences of decision makers and systemic robustness. The developed method is applied to a real-world case of WAQT in the Kaidu-Kongque River Basin in northwest China, where an effective mechanism (e.g., market trading) to simultaneously confront severely diminished water availability and degraded water quality is required. Results of water transaction amounts, water allocation patterns, pollution mitigation schemes, and system benefits under various scenarios are analyzed, which indicate that a trading-mechanism is a more sustainable method to manage water-environment crisis in the study region. Additionally, consideration of anthropogenic (e.g., a risk-averse attitude) and systemic factors (e.g., the robustness coefficient) can support the generation of a robust plan associated with risk control for WAQT when uncertainty is present. These findings assist local policy and decision makers to gain insights into water-environment capacity planning to balance the basin's social and economic growth with protecting the region's ecosystems.

关键词： fuzzy programming Two-stage stochastic programming Green Z-score criterion Strategic analysis Trading-mechanism Arid basin

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A new fuzzy bi-objective mixed-integer linear programming for designing a medical waste management network in the Coronavirus epidemic: a case study

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INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE AND ENGINEERING MANAGEMENT 2024年第3期19卷 212-227页

作者： Shaerpour, Mohammad Azani, Maede Aghsami, Amir Rabbani, Masoud Univ Tehran Coll Engn Sch Ind & Syst Engn Tehran Iran KN Toosi Univ Technol Sch Ind Engn Tehran Iran

The COVID-19 pandemic has increased medical assistance and service demand, necessitating the development of a comprehensive model for managing medical waste networks. Despite extensive research, there is a lack of models examining infectious and hazardous waste simultaneously. This paper presents a multi-layered bi-objective mixed-integer linear program model, dividing infectious and non-infectious waste into different categories. The model consists of several stages for safe recycling of medical waste. fuzzy programming and an augmented-constraint approach are employed to tackle uncertainty in parameters. A real case study from Tehran is examined, and numerical and computational results are provided to prove the model's efficiency. The results indicate that insufficient disposal centers may require increasing their capacity.

关键词： Reverse logistics medical waste management network COVID-19 multi-objective fuzzy programming infectious disease C44 C02 C61

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A solving approach for fuzzy multi-objective linear fractional programming and application to an agricultural planting structure optimization problem

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CHAOS SOLITONS & FRACTALS 2020年 141卷 110352-110352页

作者： Yang, Gaiqiang Li, Xia Huo, Lijuan Liu, Qi Taiyuan Univ Sci & Technol Coll Environm & Safety Taiyuan 030024 Shanxi Peoples R China Shanxi Datong Univ Sch Life Sci Datong 037009 Shanxi Peoples R China Shanxi Land Consolidat Ctr Taiyuan 030024 Shanxi Peoples R China

In this paper, an algorithm is presented to solve fuzzy multi-objective linear fractional programming (FMOLFP) problems through an approach based on superiority and inferiority measures method (SIMM). In the model for the proposed approach, each of fuzzy goals defined for the fractional objectives and some of constraints have fuzzy numbers. To achieve the highest membership value, SIMM is adopted to deal with fuzzy number in constraints, then a linear goal programming methodology is introduced to solve the problem in which the fractional objectives is fuzzy goals. A case of agricultural planting structures optimization problem is solved to illustrate the application of the algorithm. The results show that winter wheat and summer corn acreage should be 38,386.4 ha, and cotton acreage should be 20,669.6 ha. Because of high risk in cotton cultivation at present, the ratio of grain planted area to cotton planted area is unreasonable. An improved support in policy is necessary for the government to enhance the enthusiasm of farmers to plant cotton and sustain the development of cotton market in the long term. (C) 2020 Elsevier Ltd. All rights reserved.

关键词： Superiority and inferiority measures Multi-objective linear fractional programming fuzzy programming Goal programming Planting structure

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Handling uncertainty in Multi Regional Input-Output models by entropy maximization and fuzzy programming

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TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2014年 71卷 159-172页

作者： Caggiani, Leonardo Ottomanelli, Michele Dell'Orco, Mauro Tech Univ Bari DICATECh Dept Civil Environm & Bldg Engn & Chem I-70125 Bari Italy

Recently, great attention has been paid to the uncertainties associated with Multi Regional Input-Output (MRIO) models related to the available data sources. We propose a new method based on the entropy maximization principle and fuzzy optimization, which takes explicitly into account the uncertainty embedded in available information. It allows to estimate jointly the values of production level, the trade coefficients and the final demand values assuming the availability of incomplete and/or approximate data on some elements of trade coefficients and of final demand of goods. The model, applied to real scale problem, shows good estimation performances and robustness in different scenario. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Multi Regional Input Output Model Freight demand estimation Uncertainty fuzzy programming Entropy maximization

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Integrating Decision Analysis with fuzzy programming: Application in Urban Water Distribution System Operation

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JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT 2014年第5期140卷 638-648页

作者： Xu, T. Y. Qin, X. S. Nanyang Technol Univ Sch Civil & Environm Engn Singapore 639798 Singapore Nanyang Technol Univ Earth Observ Singapore Singapore 639798 Singapore

Water-distribution operation is an essential part of an urban water-supply system to deliver high-quality water to consumers. Management of such an operation may involve deliberations of operation cost, system capacity, and environmental restriction, and is convoluted with many forms of uncertainties. In this paper, an integrated fuzzy programming and decision analysis (IFPDA) approach was proposed for a multilayer urban water-distribution system management under uncertainty. The system consisted of two water sources, four treatment plants, seven reservoirs, and seven consuming zones. Uncertain information associated with water demands, water-treatment capacities, water-transfer cost, and leakage rate was described by a trapezoidal-shaped fuzzy set and embedded into a fuzzy programming framework. The balance between the satisfaction degree of achieving the system objective and feasibility level of meeting the related constraints was analyzed by fuzzy inference procedures. The results indicate that the IFPDA approach was advantageous in (1)dealing with fuzzy uncertainties in the objective function, both sides of the model constraints, and the context of an urban water-distribution system management;(2)helping analyze tradeoffs between minimization of operation cost and reliability of running the system;and (3)linking optimization model outputs with decision analysis.

关键词： Uncertainty Trapezoidal-shaped fuzzy sets Decision-making Urban water-distribution system fuzzy programming

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fuzzy multi-objective programming problem for revenue management in food industry

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JOURNAL OF REVENUE AND PRICING MANAGEMENT 2020年第5期19卷 349-354页

作者： Gupta, Neha Sharma, J. K. Amity Univ Uttar Pradesh Amity Sch Business Noida India

Food industry is one of the fastest growing industry. With the development of varieties in this industry, the need for revenue management is vital. Revenue management is a technique to optimize the income by selling the right product to right customer at right time which is done by using data driven tactics and strategies. In this paper, a revenue management problem is formulated as multi-objective programming problem in an uncertain environment. As in real life situations most of the parameters are generally uncertain, therefore cost parameter considered as triangular fuzzy numbers. fuzzy problem is converted into deterministic problem by alpha-cut method and then the algorithm is developed to solve the multi-objective linear programming problem to optimize revenue as well as cost simultaneously. To demonstrate and justify the formulated problem a numerical illustration has been considered and solved. All the mathematical problems are solved through an optimisation software LINGO-13.

关键词： Multi-objective programming problem Revenue management fuzzy numbers fuzzy programming

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fuzzy Geometric programming Approach in Multivariate Stratified Sample Surveys Under Two Stage Randomized Response Model

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Journal of Mathematical Modelling and Algorithms in Operations Research 2015年第4期14卷 407-424页

作者： Ullah, Shafi Ali, Irfan Bari, Abdul Department of Statistics & Operations Research Aligarh Muslim University Aligarh India

This paper provide a profound study on optimum allocation of two stage multivariate stratified Warner’s randomized response (RR) model with linear and non linear cost function. The multi-objective problem is formulated as a Geometric programming Problem (GPP). The fuzzy programming approach is adopted to solve the formulated problem. A numerical example is given to illustrate the computational details of the suggested method. © 2015, Springer Science+Business Media Dordrecht.

关键词： fuzzy programming Geometric programming Multiple sensitive questions Multivariate stratified sampling Optimum allocation Two-stage randomized response technique

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Integrated Possibilistic Linear programming with Beta-Skewness Degree for a fuzzy Multi-Objective Aggregate Production Planning Problem Under Uncertain Environments

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fuzzy INFORMATION AND ENGINEERING 2020年第3期12卷 355-380页

作者： Sutthibutr, Noppasorn Chiadamrong, Navee Thammasat Univ Sch Mfg Syst & Mech Engn Pathum Thani Thailand

This study proposes an improved fuzzy programming (FP) approach to optimise multi-objective Aggregate Production Planning (APP) problem under uncertain environments. The proposed approach integrates the concept of Possibilistic Linear programming (PLP) with Beta-Skewness Degree that decision-makers can manipulate the best level of data fuzziness as well as maintain such fuzziness in the optimisation process (by not turning it to deterministic data too early). The effectiveness of the proposed approach is demonstrated through a case study by minimising the highest overall deviation from the ideal solution of total costs under imprecise operating costs, customer demand, labour level, and machine capacity. Our comparative result clearly shows that the obtained solution outperforms the solutions from traditional defuzzification methods. The proposed approach also helps decision-makers not only to know and optimise the most likely situation, but also realise the outcomes in the optimistic and the pessimistic business situations so that decision makers can prepare and take necessary actions for future uncertainty.

关键词： Aggregate Production Planning Possibilistic Linear programming defuzzification methods Beta-Skewness Degree fuzzy programming

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Study on Optimal Allocation of Water Resources Based on Uncertain Multi-Objective fuzzy Model: A Case of Pingliang City, China

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WATER 2024年第15期16卷 2099页

作者： Zhao, Yun Zhang, Rui Shu, Heping Xu, Zhi Fan, Shangbin Wang, Qiang Li, Yaxian An, Yapeng Gansu Agr Univ Coll Water Resources & Hydropower Engn Lanzhou 730070 Peoples R China Gansu Prov Dept Water Resources Soil & Water Conservat Ctr Lanzhou 730000 Peoples R China Pingliang City Water Affairs Bur Gansu Prov Pingliang 744000 Gansu Peoples R China

Water shortages are serious in northwest China due to the level of social and economic development, engineering, resource shortages, and other factors being restricted, so the conflict between supply and demand for water resources is prominent in different regions and different water use sectors. Therefore, Pingliang City was selected as the research object in this study. The membership function was introduced, and an interactive algorithm to correct model parameters based on the fairness constraint was derived. An uncertain multi-objective fuzzy programming model was also established. The results show that the optimal allocation of water will be 38,051.9 similar to 40,740 x 10(4) m(3) and 39,938.4 similar to 41,317.5 x 10(4) m(3) under a normal year (p = 50%) and a dry year (p = 75%) in 2025, respectively, and the corresponding water shortage rates will be 4.2% and 6.7%. In 2035, the optimal water allocation will be 45,644.1 similar to 49,245.9 x 10(4) m(3) and 46,442.4 similar to 50,044.2 x 10(4) m(3) and the water shortage rates will be 7.0% and 7.0%, respectively. The proportion of groundwater supply will decrease by 8.8% and 13.8% in 2025 and 2035 after the optimal allocation, the proportion of surface water supply will increase by 9.6% and 12.2%, and the proportion of reclaimed water will increase by -0.78% and 2.1%, respectively. The results can provide a technical reference for the development and utilization of water resources in other cities and similar areas in semi-arid regions.

关键词： optimal allocation of water resources uncertainty fuzzy programming fairness membership function

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