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Application of Fuzzy multi-objective programming to Regional Sewer System Planning

PROCESSES 2023年第1期11卷 183页

作者： Huang, Chung-Fu Chen, Wei-Ting Kao, Chuan-Ksing Chang, Han-Jung Kao, Po-Min Wan, Terng-Jou Zhaoqing Univ Sch Environm & Chem Engn Zhaoqing 526061 Peoples R China Zhaoqing Univ Guangdong Prov Key Lab Environm Hlth & Land Resour Zhaoqing 526061 Peoples R China St Marys Jr Coll Med Nursing & Management Dept Cosmet Applicat & Management Yilan 26644 Taiwan Natl Yunlin Univ Sci & Technol Dept Safety Hlth & Environm Engn Yunlin 64002 Taiwan Natl Yunlin Univ Sci & Technol Ctr Green Sustainable & Innovat Yunlin 64002 Taiwan Natl Yunlin Univ Sci & Technol Bachelor Program Ind Technol Yunlin 64002 Taiwan

Planning of sewer systems typically involves limitations and problems, regardless of whether traditional planning methods or optimization models are used. Such problems include non-quantifiability, fuzzy objectives, and uncertainties in decision-making variables which are commonly applied in the planning of any process. Particularly, uncertainties have prevented the inclusion of these variables in models. Consequently, the theoretical optional solution of the mathematical models is not the true optimum solution to practical problems. In this study, to solve the above problems for regional sewer system planning, multi-objective programming (MOP), nonlinear programming, mixed-integer programming, and compromise fuzzy programming were used. The objectives of this study were two-fold: (1) determination of the necessary decision-making variables or parameters, such as the optimum number of plants, piping layout, size of the plant, and extent of treatment;(2) establishment of a framework and methodology for optimal planning for designing a regional sewer system, matching demanded targets with the lowest cost, which would achieve the aim of lower space and energy requirements as well as consumption and high treatment efficiency for the purpose of meeting effluent standards. The findings of this study revealed that individual regional sewage treatment plants could be merged to form a centralized system. Land acquisition was difficult;thus, reducing the number of plants was required. Therefore, the compromise-fuzzy-based MOP method could effectively be used to build a regional sewer system plan, and the amount of in-plant establishment reached its maximized value with a minimized cost.

关键词： regional sewer system planning multi-objective programming nonlinear programming mixed-integer programming compromise fuzzy programming

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Demand response versus storage flexibility in energy: multi-objective programming considerations

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OPTIMIZATION 2021年第7期70卷 1459-1486页

作者： van Ackooij, Wim Paula Chorobura, Ana Sagastizabal, Claudia Zidani, Hasnaa EDF R&D OSIRIS Dept Palaiseau France Univ Fed Parana Postgrad Program Math Curitiba Parana Brazil State Univ Campinas IMECC UNICAMP Inst Math Stat & Sci Comp Campinas Brazil Ensta Paris UMA Palaiseau France

Intermittent sources of energy represent a challenge for electrical networks, particularly regarding demand satisfaction at peak times. Energy management tools such as load shaving or storage systems can be used to mitigate intermittency. In this work, the value of different mechanisms to move energy through time is examined through a multi-objective programming approach, that aims at minimizing operating costs as well as carbon emissions. Among main achievements, we mention a sensitivity result that provides a novel three-dimensional Pareto front. The new tool complements the traditional curves of indifference costs with a quantitative measure for assessing the relative value of the conflicting objectives. The methodology is assessed on three instances representing typical configurations in Brazil, Germany and France, respectively corresponding to a system that is hydro-dominated, thermo-dominated, and with a balanced mix of hydro and thermal power. The corresponding Pareto fronts show that lowering carbon emissions can also reduce generation costs if the power mix is sufficiently diversified.

关键词： multi-objective programming comparative study of energy management systems sensitivity analysis of Pareto fronts

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Optimization of facility location and size problem based on bi-level multi-objective programming

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COMPUTERS & OPERATIONS RESEARCH 2022年 145卷 1页

作者： Hu, Zhineng Wang, Li Qin, Jindong Lev, Benjamin Gan, Lu Sichuan Univ Business Sch Chengdu 610064 Peoples R China Sichuan Agr Univ Coll Architecture & Urban Rural Planning Dujiangyan 611830 Peoples R China Wuhan Univ Technol Sch Management Wuhan 430070 Peoples R China Drexel Univ LeBow Coll Business Philadelphia PA 19104 USA

With the rapid urbanization, solving the facility location and size problem (FLSP) of general service infrastructure (GSI) has become an essential issue in spatial planning. Due to unreasonable location and regional scale, the satisfaction of residents has been seriously affected. This paper develops a bi-level multi-objective programming (BLMOP) to optimize both facility location and size. Three major problems have been addressed: (1) solving the contradiction between supply and demand;(2) keeping a balance of social, economic, and environmental benefits;and (3) designing a multi-objective particle swarm optimization (MOPSO) algorithm by modifying the parameters and learning strategies. To obtain feasible solutions, a combination of optimistic and pessimistic approaches is adopted. Taking the rural areas of Southwest China as an example, the results find that the proposed model enables to provide objective-oriented optimization schemes depending on the decision-maker's (DM) preferences. Furthermore, the MOPSO algorithm can solve the BLMOP and provide Pareto-optimal solutions separately.

关键词： Facility location and size problem Bi-level programming multi-objective programming Particle swarm optimization

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Fuzzy goal programming approach to solve fully fuzzy multi-objective quadratic programming problem

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INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT 2024年第2期15卷 705-712页

作者： Tadesse, Admasu Acharya, M. M. Acharya, Srikumar Sahoo, Manoranjan KITT Univ Sch Appl Sci Dept Math Bhubaneswar India

The focus of this paper is to suggest a solution methodology for a fully fuzzy multi-objective quadratic programming problem. Solving the provided mathematical model using known classical methods is extremely difficult. To solve the present mathematical programming problem, three major approaches are suggested. In first step, we used arithmetic operations between two fuzzy parameters and variables. The importance is given in the next step to handle fuzzy part of objective functions by ranking functions and after the completion of the second step, the fuzzy part of the fuzzy constraints tackled by the inequality property of between two triangular fuzzy numbers. Finally, the transformed multi-objective quadratic mathematical programming problem is solved using a weighted fuzzy goal programming approach. The final solution of the suggested model is derived using existing methodology and softwares. The working procedures of the proposed method is further discussed using numerical example.

关键词： multi-objective programming Triangular fuzzy number Weighted fuzzy goal programming Fuzzy decision variables Quadratic programming Fuzzy quadratic programming

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Modeling land allocation to produce crops under economic and environmental goals in Iran: a multi-objective programming approach

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ECOLOGICAL MODELLING 2022年 471卷

作者： Nikouei, Alireza Asgharipour, Mohammad Reza Marzban, Zahra AREEO Isfahan Agr & Nat Resources Res & Educ Ctr Econ Social & Extens Res Dept Esfahan Iran Univ Zabol Fac Agr Dept Agron Unit Agroecol Zabol Iran

This study introduces a multi-objective programming model for identifying a cropping pattern to evaluate the feasibility of increasing net profit, reducing water use, and diminishing the environmental impacts, simultaneously, under life cycle assessment (LCA). The research uses data collected in 2016-2017 through a survey in the east of the Lorestan Province of Iran. Results indicate that the multi-objective cropping pattern reduces environmental indicators, including water consumption by 1%, global warming potential by 14%, and nonrenewable energy use by 14%, with no change in farms' net profit compared to the current pattern in the region. The findings reveal that a designed cropping pattern under the constraints and objectives of LCA not only minimizes the environmental impacts, but also considers the stability of the benefits in the long term. However, the currently applied cropping pattern by farmers only focuses on achieving short-term profit-oriented goals. A new approach to land allocation is necessary to produce crops with a reduction in water consumption, nonrenewable energy use, and greenhouse gas emissions in the region. In this regard, it is essential to consider the policies that reduce available water and non-renewable resources into government decisions. On the other hand, policy incentives or disincentives, developing support packages of crop pricing, insurance and facilities support to prevent the cultivation of crops with high water demand and fertilizer are also essential. This proposed planning model should be used as the foundation for long-term cropping pattern planning policies in other irrigated and rainfed farming systems around the world.

关键词： multi-objective programming non-renewable energy mineral extraction optimization net profit life cycle analysis

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Maturity level determination and optimization model of D&A system based on support vector machine and multi-objective programming

Maturity level determination and optimization model of D&A s...

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作者： Shunyu Yao China university of geoscience

In today's era of fragmented information,good data management is essential for *** data integration and analysis(D&A) is crucial to unleashing the full potential of data *** evaluation was conducted on Intercontinental Freight Company's(ICM) D&A system,with three key assessments identified:importance,connectivity,and availability *** multi-level fuzzy evaluation metrics,key points that affect the system's development were *** regression lines were used to analyze relationships between people,process,and *** performance was measured via average growth in business profits,and an index of 11 variables was created to measure the system's maturity.A growth phase distribution model was developed utilizing a support vector machine and tested on a sample of 50 US *** optimization model,based on multi-purpose functions,maximizes efficiency and can be seen by comparing factors before and after port *** experiment proves the effectiveness of the D&A system development evaluation model.

关键词： Maturity level determination Optimization model Support vector machine multi-objective programming

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Hydropower Sharing based on multi-objective programming

International Core Journal of Engineering

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International Core Journal of Engineering 2022年第8期8卷 723-731页

作者： Ziri Jin Xuecheng He Jisheng Xu

Aiming at the problem of resource allocation, this paper establishes a regional water resource allocation model based on a multi-objective programming algorithm. Specifically, we establish a linear programming model to identify two reservoirs with optimal water supply quantity and optimal power generation volume as objective functions. In addition, we establish a multi-objective programming model and determined the functional expressions of the two objectives of social benefit and economic benefit. The entropy weight method is used to determine the weights of the four major indicators of industry, agriculture, housing and electricity. Finally, we use MATLAB to solve the corresponding water demand, and use SPSS software to analyze the correlation between water, electricity supply and water demand, and obtain the influence of different variables in the model.

关键词： Resource Allocation Linear programming multi-objective programming Entropy Weight Method Correlation Analysis

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On neutrosophic multi-level multi-objective linear programming problem with application in transportation problem

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2023年第2期44卷 2251-2267页

作者： Fathy, E. Ammar, E. Helwan Univ Fac Sci Dept Math Cairo Egypt Tanta Univ Fac Sci Dept Math Tanta Egypt

In this research, we use the harmonic mean technique to present an interactive strategy for addressing neutrosophic multi-level multi-objective linear programming (NMMLP) problems. The coefficients of the objective functions of level decision makers and constraints are represented by neutrosophic numbers. By using the interval programming technique, the NMMLP problem is transformed into two crisp MMLP problems, one of these problems is an MMLP problem with all of its coefficients being upper approximations of neutrosophic numbers, while the other is an MMLP problem with all of its coefficients being lower approximations of neutrosophic numbers. The harmonic mean method is then used to combine the many objectives of each crisp problem into a single objective. Then, a preferred solution for NMMLP problems is obtained by solving the single-objective linear programming problem. An application of our research problem is how to determine the optimality the cost of multi-objective transportation problem with neutrosophic environment. To demonstrate the proposed strategies, numerical examples are solved.

关键词： Neutrosophic number multi-level linear programming multi-objective programming harmonic mean technique

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A Two-Stage multi-objective programming Model to Improve the Reliability of Solution

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INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS 2020年第1期13卷 433-443页

作者： Jin, Chenxia Li, Fachao Feng, Kaixin Guo, Yunfeng Hebei Normal Univ Sch Math Sci Shijiazhuang 050024 Hebei Peoples R China Hebei Univ Sci & Technol Sch Econ & Management Shijiazhuang 050018 Hebei Peoples R China

Randomness is a common uncertainty encountered in practical multi-objectives decision-making. But it is always a challenge for decision-makers to process randomness in multi-objective programming problems. This paper takes the decision-making objectives as fuzzy events and aims to solve numerical multi-objective programming problems under random environment. We first analyze the effects of randomness on multi-objective decision-making results. With the expectation value and the probability of fuzzy events as quantitative index of randomness, we then establish a two-stage random multi-objective programming model based on reliability (i.e., TS-MOPM). Specifically, we give several probability calculation methods of fuzzy events with common distributions, and further present the corresponding calculation procedures for solving TS-MOPM. Finally, a case study is implemented to test the proposed model TS-MOPM. Theoretical analysis and case study indicate that our model has better interpretability and operability. The research results enrich the existing random multi-objective programming methods to some extent. (C) 2020 The Authors. Published by Atlantis Press SARL.

关键词： multi-objective programming Randomness Expectation value Fuzzy events Reliability

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A robust augmented ε-constraint method (AUGMECON-R) for finding exact solutions of multi-objective linear programming problems

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OPERATIONAL RESEARCH 2022年第2期22卷 1291-1332页

作者： Nikas, Alexandros Fountoulakis, Angelos Forouli, Aikaterini Doukas, Haris Natl Tech Univ Athens Sch Elect & Comp Engn Decis Support Syst Lab Iroon Politech 9 Athens 15780 Greece

Systems can be unstructured, uncertain and complex, and their optimisation often requires operational research techniques. In this study, we introduce AUGMECON-R, a robust variant of the augmented epsilon-constraint algorithm, for solving multi-objective linear programming problems, by drawing from the weaknesses of AUGMECON 2, one of the most widely used improvements of the epsilon-constraint method. These weaknesses can be summarised in the ineffective handling of the true nadir points of the objective functions and, most notably, in the significant amount of time required to apply it as more objective functions are added to a problem. We subsequently apply AUGMECON-R in comparison with its predecessor, in both a set of reference problems from the literature and a series of significantly more complex problems of four to six objective functions. Our findings suggest that the proposed method greatly outperforms its predecessor, by solving significantly less models in emphatically less time and allowing easy and timely solution of hard or practically impossible, in terms of time and processing requirements, problems of numerous objective functions. AUGMECON-R, furthermore, solves the limitation of unknown nadir points, by using very low or zero-value lower bounds without surging the time and resources required.

关键词： Augmecon epsilon-constraint multi-objective programming Optimisation Pareto

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