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Sustainable fuel portfolio optimization: Integrated fuzzy multi-objective programming and multi-criteria decision making

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JOURNAL OF CLEANER PRODUCTION 2018年 176卷 304-319页

作者： Sehatpour, Mohammad-Hadi Kazemi, Aliyeh Univ Tehran Fac Management Dept Ind Management Tehran Iran

The chronic illness of transportation sector is its excessive dependence on petroleum products that necessitates immediate actions to mitigate negative externalities. Developing an environmentally benign, economically feasible, and socially acceptable fuel portfolio can generally, improve the sustainability of future transportation systems. This study aims to predict an optimal fuel portfolio based on different concerns for light-duty vehicles of Iran in the light of alternative fuels until 2025. Six potential fossil and renewable fuels including gasoline, diesel, compressed natural gas (CNG), liquid petroleum gas (LPG), a mixture of 85% ethanol and 15% gasoline (E85) and biodiesel, and one gasoline-electric hybrid technology competed through an integrated fuzzy multi-objective programming. Seven goals with environmental, cost, social and policy nature, as well as systematic constraints and fuel priority (obtained by the application of a multi-criteria decision making (MCDM) method) had to be met in the model. The solution of the model along with the sensitivity analysis of weights and aspiration levels indicated that with an acceptable possibility of achieving the goals, CNG had the greatest share in the optimal fuel portfolio followed by gasoline, LPG and diesel. Through the intended horizon, the fossil fuels' share has declined such that 13.5% of the optimal portfolio was replaced by hybrid technology, biodiesel and E85 in 2025, and more importantly, carbon dioxide emission and fuel cost could be mitigated by 11% and 18%, respectively in the same year. Two scenarios focusing on environmental and cost goals were defined through assigning 70% and 80% of the weights to the related goals, respectively;the results revealed that the main characteristics of the optimal portfolio were stable. Likewise, the analysis of the aspiration and tolerance levels of the goals proved the stability of the model and revealed that these parameters play a sensitive role in the model an

关键词： Fuel portfolio optimization Transportation alternative fuel multi-objective programming Light-duty vehicle Biofuel

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An interval multi-objective programming model for irrigation water allocation under uncertainty

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AGRICULTURAL WATER MANAGEMENT 2018年 196卷 24-36页

作者： Li, Mo Fu, Qiang Singh, Vijay P. Liu, Dong Northeast Agr Univ Sch Water Conservancy & Civil Engn Harbin 150030 Heilongjiang Peoples R China Northeast Agr Univ Key Lab Efficient Utilizat Agr Water Resources Minist Agr Harbin 150030 Heilongjiang Peoples R China Texas A&M Univ Dept Biol & Agr Engn 201 Scoates Hall2117 TAMU College Stn TX 77843 USA Texas A&M Univ Zachry Dept Civil Engn 201 Scoates Hall2117 TAMU College Stn TX 77843 USA

An interval linear multi-objective programming (ILMP) model for irrigation water allocation was developed, considering conflicting objectives and uncertainties. Based on the generation of interval numbers through statistical simulation, the ILMP model was solved using a fuzzy programming method. The model balances contradictions among economic net benefit, crop yield and water-saving in irrigation systems incorporating uncertainties in both objective functions and constraints that are based on the conjunctive use of surface water and groundwater. The model was applied to Hulan River irrigation district, northeast China. Tradeoffs between various crops in different subareas under different frequencies were analyzed, and scenarios with different objectives were considered to evaluate the changing trend of irrigation water *** indicated that the ILMP model provided effective linkages between revenue/output promotion and water saving, and offers insights into tradeoffs for irrigation water management under uncertainty. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Irrigation water allocation multi-objective programming Interval number Bootstrap Scenario analysis

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Lexicographic optimal solution of the multi-objective programming problem subject to max-product fuzzy relation inequalities

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FUZZY SETS AND SYSTEMS 2018年 341卷 92-112页

作者： Yang, Xiao-Peng Yuan, De-Hui Cao, Bing-Yuan Hanshan Normal Univ Dept Math & Stat Chaozhou 521041 Guangdong Peoples R China Guangzhou Univ Sch Math & Informat Sci Guangzhou 510006 Guangdong Peoples R China Guangzhou Vocat Coll Sci & Technol Guangzhou 510550 Guangdong Peoples R China

It is shown in this paper that the emission base stations in wireless communication can be reduced into a system of fuzzy relation inequalities with max-product composition. For optimal management in such system, we introduce the fuzzy relation multi-objective programming. Concept of feasible index set (FIS) is defined, based on which a novel algorithm, named FIS algorithm, is developed to find the unique lexicographic optimal solution of the proposed problem with polynomial computational complexity. Applying this method, we needn't to find out all the minimal solutions of the constraint. A numerical application example is provided to illustrate the feasibility and efficiency of the FIS algorithm. (c) Elsevier B.V. All rights reserved.

关键词： Fuzzy relation inequality multi-objective programming Lexicographic order Feasible index set Fuzzy relation equation Wireless communication

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A multi-objective programming Method Based on Relative Deviation 8

A Multi-objective Programming Method Based on Relative Devia...

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8th International Conference on Logistics, Informatics and Service Sciences (LISS)

作者： Li, Fachao Feng, Kaixin Hebei Univ Sci & Technol Sch Econ & Management Shijiazhuang Hebei Peoples R China

ISBN: (纸本)9781538669655

multi-objective programming, as an effective mathematical model for dealing with multiple objectives, is widely used in the fields of complex system optimization, management decision analysis and artificial intelligence. This paper first analyzes the characteristics and deficiencies of the multi-objective planning model based on priority factors, and proposes a multi-objective planning method based on relative deviations. It mainly introduces the relative deviation to describe the degree of deviation from the target value and reflect the satisfactory state of the decision results. It establishes a planning model in which each objective is at the same level, and analyzes the effectiveness of the method in conjunction with a specific case. The comprehensive analysis and the corresponding conclusions show that the solution model established not only ensures the existence of the solution, but also guarantees the reliability of the decision-making result. It has strong explanatory and operability, and to a certain extent, enriches the existing fuzzy decision-making method.

关键词： relative deviation multi-objective programming linear target programming priority factor

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Fuzzy rough bi-level multi-objective nonlinear programming problems

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ALEXANDRIA ENGINEERING JOURNAL 2019年第4期58卷 1471-1482页

作者： Elsisy, M. A. El Sayed, M. A. Benha Univ Fac Engn Dept Basic Engn Sci Elqalyoubia Egypt

Fuzzy rough bi-level multi-objective nonlinear programming problem (FRBMNPP) moved toward becoming rise normally in various real applications. In this article we develop bi-level multi-objective nonlinear programming problem (BMNPP), in which the objective functions have fuzzy nature and the constraints represented as a rough set. The fuzzy objective functions converted into deterministic ones by utilizing the alpha-cut methodology. Thus the FRBMNPP become a rough BMNPP which is transformed into two problems corresponding to the upper and lower approximation models. The Karush-Kuhn-Tucker (KKT) method and two models of technique of order preferences by similarity to ideal solution (TOPSIS) approach are developed to solve such problem. At last, applicability and efficiency of the two TOPSIS models and KKT method, suggested in this study, are presented through an algorithm and a numerical illustration. (C) 2019 The Authors. Published by Elsevier B.V. on behalf of Faculty of Engineering, Alexandria University.

关键词： Bi-level optimization multi-objective programming Rough set Fuzzy sets TOPSIS Karush-Kuhn-Tucker (KKT) method

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Portfolio Research Based on Neural Network and multi-objective programming

Portfolio Research Based on Neural Network and Multi-Objecti...

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作者： Rongjie Jian Tingting Ni Xiamen Huaxia University Xiamen Xingcai Vocational&Technical College

In financial investment, risk and benefit coexist. How to balance the benefits and risks and find the optimal investment portfolio is a key issue to be considered by investors. In this research, BP neural network is used to predict the future return on equity(ROE) of asset;a multiobjective programming model of investment portfolio is established on the basis of Markowitz's portfolio investment theory;to select the optimal investment portfolio, a comparison is made on the benefit-risk ratio of the investment portfolio with the smallest risk and at different income levels;in addition, an empirical analysis is made on the basis of the quarterly ROE data of 5 stocks during 2002-2017.

关键词： portfolio BP neural network ROE (return on equity) multi-objective programming benefit–risk ratio

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Investment Decision Model Based on multi-objective programming

Investment Decision Model Based on Multi-objective Programmi...

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作者： Yukun Lu Yuqian Hu Chen Ai College of Mathematics Science Huaqiao University

The design of a portfolio investment strategy for multiple venture capital and a risk-free asset in the market needs to consider two objectives: the overall return is as large as possible and the overall risk is as small as possible. However, the two objectives are not mutually reinforcing. In a certain sense, they are opposite. In this paper, the multi-objective decision-making method is used to establish the model, and the investment benefit is the goal. The optimization model is established for the investment problem. Different investment methods have different risks and benefits. According to the principle of the optimization model, the model proposes two criteria, so that the economic benefits are as large as possible and the risks are as small as possible under certain conditions of investment. At the same time, a linear programming model for portfolio investment scheme design is given. The main idea is to integrate two design goals through linear weighting: assuming that the transaction fee function is approximately linearized on the basis of considerable investment scale, and the risk function is solved by decision variables.

关键词： Portfolio multi-objective programming Linear programming Linear Weighting

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A multi-objective programming Model for Subway Last Train Timetabling 3rd

A Multi-objective Programming Model for Subway Last Train Ti...

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3rd International Conference on Electrical Engineering and Information Technologies for Rail Transportation (EITRT)

作者： Xiang, Wanxiao Wang, Yanhui Beijing Jiaotong Univ Sch Traff & Transportat State Key Lab Rail Traff Control & Safety 3 Shang Yuan Cun Beijing Peoples R China

ISBN: (纸本)9789811079894;9789811079887

Subway last train timetabling focuses more on train coordination to make passengers transfer smoothly. Aiming to find an optimal balanced timetabling, a multi-objectives programming model is proposed with speed profile control for finding the optimal train velocity on sections and train dwell time at stations. Our work makes two contributions. First, this paper analyzes train movements in a line and provides an energy flow transferring method. Second, based on the analysis of train velocity and energy flow, an optimization model, in which passenger satisfaction, train trip time and network energy consumption are model objectives, is brought into the last train timetabling. Finally, to obtain an approximately optimal scheduling strategy, an artificial intelligence algorithm is proposed in particular to effectively solve the proposed model. The results of numerical experiments demonstrate the efficiency and effectiveness of the proposed method.

关键词： Subway Last train timetabling multi-objective programming Train coordination

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Non-smooth multi-objective fractional programming problem involving higher order functions

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INTERNATIONAL JOURNAL OF COMPUTING SCIENCE AND MATHEMATICS 2019年第4期10卷 351-363页

作者： Kharbanda, Pallavi Agarwal, Divya Higher Educ Dept Math Panchkula India Amity Univ Amity Inst Appl Sci Dept Math Noida India

In this paper, a new generalised class of higher order (F, alpha, rho, d)-V-type I function is introduced for a non-smooth multi-objective fractional programming problem involving support functions. The newly defined class extends several known classes in the literature has been justified through a non-trivial example. In the framework of new concept, we determine conditions under which a fractional function becomes higher order (F, alpha, rho, d)-V-type I function and do some computational work to substantiate the analysis. Further, we establish Karush-Kuhn-Tucker type sufficient optimality conditions and derive various duality results for higher order Mond-Weir type and Schaible type dual programs.

关键词： multi-objective programming (F, alpha, rho, d)-V-type I function fractional programming nonlinear programming efficient solution

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An inexact multi-objective programming model for an economy-energy-environment system under uncertainty: A case study of Urumqi, China

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ENERGY 2017年 126卷 165-178页

作者： Fu, Z. H. Xie, Y. L. Li, W. Lu, W. T. Guo, H. C. Peking Univ Coll Environm Sci & Engn Beijing 100871 Peoples R China Univ Sci & Technol Beijing Beijing 100871 Peoples R China North China Elect Power Univ China Canada Energy & Environm Res Ctr Beijing 102206 Peoples R China

Economic restructuring, energy planning and environmental protection are subject to inherent uncertainties in a compound system with competing decision objectives. Therefore, an inexact multi objective programming model for regional economy-energy-environment system management has been developed to obtain absolutely "optimal" solutions. Under two comparative scenarios, three subsystems, six industries, four types of energy, and three kinds of air pollution were considered in an optimization model, and a net system benefit and trade-off analysis between subsystems was conducted. The methods of interval-parameter programming and multi-objective programming were incorporated into the model to tackle the uncertainties and complexities reflected in the case study. The model results indicated that the developed model could provide effective linkages among the economy-energy environment systems and offer decision makers great insight into the reliability tradeoffs for the adjustment of the existing management policy. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： multi-objective programming Economy-energy-environment system Regional development plan Uncertainty

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