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Liquefied natural gas importing security strategy considering multi-factor: A multi-objective programming approach

EXPERT SYSTEMS WITH APPLICATIONS 2017年 87卷 56-69页

作者： Zhang, Xiao-Nan Zhong, Qiu-Yan Qu, Yi Li, Hong-Lei Liaoning Normal Univ Sch Management 850 Huanghe Rd Dalian 116029 Liaoning Peoples R China Dalian Univ Technol Fac Econ & Management 2 Linggong Rd Dalian 116024 Liaoning Peoples R China Agr Bank China Data Ctr 88 Aoni St Shanghai 201200 Peoples R China

LNG importing strategies, in the literature, are primarily studied under a common single-factor framework. However, LNG importing strategies are affected by a variety of factors. To address this existing gap, this paper proposes a multi-objective programming model, which takes into account the cost, the country risk, the shipping risk, and the impact of extreme events. A pure structural change model is used to determine the risk impact coefficient for extreme events. An enhanced Simulated Annealing Algorithm is then used to solve the LNG-importing optimization problem. An experimental study is further conducted to verify the practicability of the proposed approach in the case of China's LNG-importing data. The software implementation of the proposed model is developed in Python. The proposed model provides a decision support tool for LNG importing companies to find an efficient portfolio strategy for LNG importing. The optimization model can be used for analyzing similar scenarios involving such dimensions as economy, energy security, and especially energy diversification. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Liquefied natural gas (LNG) multi-objective programming Extreme events Improved Simulated Annealing Algorithm Software implementation

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Vector critical points and generalized quasi-efficient solutions in nonsmooth multi-objective programming

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JOURNAL OF INEQUALITIES AND APPLICATIONS 2017年第1期2017卷 1页

作者： Wang, Zhen Li, Ru Yu, Guolin North Minzu Univ Inst Appl Math Ningxia 750021 Peoples R China

In this work, several extended approximately invex vector-valued functions of higher order involving a generalized Jacobian are introduced, and some examples are presented to illustrate their existences. The notions of higher-order (weak) quasi-efficiency with respect to a function are proposed for a multi-objective programming. Under the introduced generalization of higher-order approximate invexities assumptions, we prove that the solutions of generalized vector variational-like inequalities in terms of the generalized Jacobian are the generalized quasi-efficient solutions of nonsmooth multi-objective programming problems. Moreover, the equivalent conditions are presented, namely, a vector critical point is a weakly quasi-efficient solution of higher order with respect to a function.

关键词： vector variational-like inequality multi-objective programming approximate invexity quasi-efficiency vector critical point

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Collaborative energy management in a micro-grid by multi-objective mathematical programming

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ENERGY AND BUILDINGS 2019年 203卷 109432-000页

作者： Pisacane, Ornella Severini, Marco Fagiani, Marco Squartini, Stefano Univ Politecn Marche Dipartimento Ingn Informaz Ancona Italy

In micro-grids, distributed energy generation based on renewable sources allows reducing the fossil fuel emissions. In order to manage the limited availability of renewable sources and to meet users' requirements, a proper scheduling of both tasks and storage activities is needed. Moreover, the difficulty of storing energy on a large scale represents an opportunity for the micro-grid actors to collaborate for better balancing energy supply and demand. Collaboration may be achieved through the application of suitable energy management policies tackling the specific consumers' needs. We address the Energy Management Problem in a micro-grid with collaboration among users. Specifically, a building is considered where each apartment can use both Shared and Local energy resources, the former managed by a Building Manager (BM). The problem is formulated through Bi-objective Mixed Integer Linear programming, maximizing both the BM and the apartments' profits and solved through the Augmented epsilon-Constraint approach. Numerical results, obtained on a set of realistic scenarios, are compared to those of the Weighted Sum method and evaluated according to proper performance metrics. The approach flexibility, in terms of selected management policies, is also discussed. Finally, the superiority of the collaborative paradigm versus the non-collaborative one is experimentally proven. (C) 2019 Elsevier B.V. All rights reserved.

关键词： Energy management Smart grid multi-objective programming Transactive energy

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Approximating Reachable Sets of Linear Control System Using multi-objective programming 29

Approximating Reachable Sets of Linear Control System Using ...

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第29届中国控制与决策会议

作者： Yangfan Zhang Lizhen Shao Guangda Hu Boyu Li Key Laboratory of Advanced Control of Iron and Steel Process(Ministry of Education) School of Automation and Electrical Engineering University of Science and Technology Beijing Department of Mathematics Shanghai University

ISBN: (纸本)9781509046584

A continuous control system can be discretized into a discrete control system by numerical methods for ordinary differential *** have shown that the reachable set of a continuous control system can be approximated by its discrete *** this paper,utilizing the convex property of the reachable set of a linear control system,we propose a method to approximate the convex reachable set of a discrete linear control system with multi-objective programming(MOP).We treat the reachable set problem as solving multiple MOP problems and the convex hull of the non-dominated sets of these MOPs is the reachable *** each MOP the revised normal boundary intersection method is used to obtain non-dominated ***,we use computational experiments to clearly illustrate the validity of this method.

关键词： Reachable set multi-objective programming Revised normal boundary intersection method

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Solving multi-level multi-objective Fractional programming Problems with Fuzzy Demands via FGP Approach

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International Journal of Applied and Computational Mathematics 2018年第1期4卷 1-24页

作者： Osman, M.S. Emam, O.E. El Sayed, M.A. Mathematics and Operations Research El Asher University El Asher City Egypt Department of Information Systems Faculty of Computers and Information Helwan University P.O. Box 11795 Greater Cairo Egypt Department of Basic Engineering Sciences Faculty of Engineering Benha University Benha ElQalyoubia Egypt

This paper presents a fuzzy goal programming approach for solving multi-level multi-objective fractional programming problem with fuzzy demands. It makes an extension work of Pal et al. (Fuzzy Sets Syst 139(2):395–405, 2003). Firstly, the concept of α-cut is applied to transform the fuzzy mathematical problem into a common deterministic one. Then, the membership functions for the defined fuzzy goals are developed. Also, in the proposed approach, linearization of membership goals of the objective functions is presented. Secondly, the highest degree of each of these membership goals is achieved by minimizing the sum of the negative deviational variables. Moreover, the final model is simplified by eliminating solution preferences by the decision makers at each level, thereby avoiding decision deadlock situations. Finally, an illustrative numerical examples and comparisons with the existing methods are used to demonstrate the applicability and performance of the proposed approach. © 2017, Springer (India) Private Ltd., part of Springer Nature.

关键词： Fractional programming Fuzzy goal programming Fuzzy sets multi-level programming multi-objective programming

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Logarithmic quasi-distance proximal point scalarization method for multi-objective programming

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APPLIED MATHEMATICS AND COMPUTATION 2016年 273卷 856-867页

作者： Rocha, Rogerio Azevedo Oliveira, Paulo Roberto Gregorio, Ronaldo Malheiros Souza, Michael Tocantins Fed Univ Undergrad Computat Sci Course BR-77001090 Palmas Brazil Univ Fed Rio de Janeiro Comp & Syst Engn Dept BR-2194590 Rio De Janeiro Brazil Rio de Janeiro Fed Rural Univ Technol & Languages Dept BR-26221010 Rio De Janeiro Brazil Univ Fed Ceara Dept Stat & Appl Math BR-60455760 Fortaleza Ceara Brazil

Recently, Gregorio and Oliveira developed a proximal point scalarization method (applied to multi-objective optimization problems) for an abstract strict scalar representation with a variant of the logarithmic-quadratic function of Auslender et al, as regularization. In this study, a variation of this method is proposed, using the regularization with logarithm and quasi-distance. By restricting it to a certain class of quasi-distances that are Lipschitz continuous and coercive in any of their arguments, we show that any sequence { (x(k), z(k)) subset of R-n x R-m generated by the method satisfies: {z(k)} is convergent: and {x(k)} is bounded and its accumulation points are weak Pareto solutions of the unconstrained multi-objective optimization problem (C) 2015 Elsevier Inc. All rights reserved.

关键词： Proximal point algorithm Scalar representation multi-objective programming Quasi-distance

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A multi-objective fuzzy programming model for optimal use of irrigation water and land resources under uncertainty in Gansu Province, China

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JOURNAL OF CLEANER PRODUCTION 2017年 164卷 85-94页

作者： Ren, Chongfeng Guo, Ping Tan, Qian Zhang, Liudong China Agr Univ Ctr Agr Water Res Tsinghuadong St 17 Beijing 100083 Peoples R China Changan Univ Sch Environm Sci & Engn Xian 710054 Shaanxi Peoples R China Yunnan Agr Univ Coll Water Conservancy Kunming 650201 Yunnan Peoples R China

This paper developed a multi-objective fuzzy programming method for simultaneously optimizing the use of water and land resources for irrigation under uncertainty. The developed model was then applied to a case study in Wuwei, Gansu Province, China. In this study, administrative, economic and ecological benefits were regarded as the planning objectives. Moreover, the variations of irrigation water demand with rainfall, soil moisture content and evapotranspiration were considered in the developed model. Optimal irrigation plans were obtained under different possibility levels of fUzzy parameters. The obtained results could be helpful for decision makers to make decisions on the optimal use of irrigation water and land resources under uncertainty and multiple objectives. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Fuzzy sets multi-objective programming Water and land Optimal allocation Soil water Uncertainty

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Environmental corporate responsibility for investments evaluation: an alternative multi-objective programming model

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ANNALS OF OPERATIONS RESEARCH 2016年第2期247卷 395-413页

作者： Xidonas, Panos Doukas, Haris Mavrotas, George Pechak, Olena ESSCA Ecole Management 55 Quai Alphonse Le Gallo F-92513 Paris France Natl Tech Univ Athens Sch Elect & Comp Engn Decis Support Syst Lab Zografou Campus Athens 15780 Greece Natl Tech Univ Athens Sch Chem Engn Lab Ind & Energy Econ Zografou Campus Athens 15780 Greece

Current financial and economic crisis, as well as growing environmental pressures put seriously under question traditional development patterns. The need to develop alternative models able to address current economic situation through the exploitation of sustainable patterns is of crucial importance. The innovation of this current study is the incorporation of energy and environmental corporate responsibility (EECR) in decision making, supporting particularly the development of a new model for investment evaluation. A bi-objective programming model is introduced in order to provide the Pareto optimal portfolios (Pareto set) based on the net present value of projects and the EECR score of firms. A systematic decision making approach using Monte Carlo simulation and multi-objective programming is also developed in order to deal with the inherent uncertainty in the objective functions' coefficients. The robustness of the Pareto set as a whole, as well as the robustness of the individual Pareto optimal portfolios is also assessed. The proposed approach facilitates banking organizations and institutions to the selection of firms applying for financial support and credit granting, within the frame of their EECR. Finally, an illustrative real-world application of the proposed model is presented.

关键词： multi-objective programming Economic crisis Corporate social responsibility Energy and environment Project portfolio selection Uncertainty Robustness

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Interactive Approach for multi-Level multi-objective Fractional programming Problems with Fuzzy Parameters

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Beni-Suef University Journal of Basic and Applied Sciences 2018年第1期7卷 139-149页

作者： M.S. Osman O.E. Emam M.A. Elsayed Professor of Mathematics and Operations Research Vicepresedent of ElAsher University Egypt Department of Information Systems Faculty of Computers and Information Helwan University P.O.Box 11795 Egypt Department of Basic Engineering Sciences Faculty of Engineering Benha University ElQalyoubia Egypt

In this paper, an interactive approach for solving multi-level multi-objective fractional programming (ML-MOFP) problems with fuzzy parameters is presented. The proposed interactive approach makes an extended work of Shi and Xia (1997). In the first phase, the numerical crisp model of the ML-MOFP problem has been developed at a confidence level without changing the fuzzy gist of the problem. Then, the linear model for the ML-MOFP problem is formulated. In the second phase, the interactive approach simplifies the linear multi-level multi-objective model by converting it into separate multi-objective programming problems. Also, each separate multi-objective programming problem of the linear model is solved by the ∊ -constraint method and the concept of satisfactoriness. Finally, illustrative examples and comparisons with the previous approaches are utilized to evince the feasibility of the proposed approach.

关键词： multi-level programming multi-objective programming Fractional programming Fuzzy parameters

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Research on Joint Dispatching of Class Reservoirs with multi-objective programming Model

Research on Joint Dispatching of Class Reservoirs with Multi...

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作者： Deyi Liu Cheng Yuan Zhixue Wang Nan Ji Xaojun Men Jun Lin Yu Li College of Information Engineering North China University of Science and Technology College of Electrical Engineering North China University of Science and Technology College of Science North China University of Science and Technology

Aiming at the water regulation problem of the Kaliba dam on the Zambezi River, this paper establishes a multi-objective programming model for gradient reservoir joint scheduling. Based on the consideration of reservoir safety and benefit, the two objective functions of optimal flood control capacity and maximum power generation capacity are established by combining these constraints, water capacity, reservoir capacity, hydraulic and discharge capacity. Using genetic algorithm to solve the dam flood control capacity of 120 billion cubic meters, the annual generating capacity of 640 billion kilowatts per hour. Finally,the ARIMA model was established based on the monthly flow rate of the Zambezi River in the past six years, and the maximum water flow was obtained from January to March, the maximum water flow was 2.4 cubic meters per second, the lowest water flow from July to October and the lowest water flow of 0.45 cubic Meters per second.

关键词： multi-objective programming Genetic algorithm ARIMA model

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