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Water-energy-ecosystem nexus modeling using multi-objective, non-linear programming in a regulated river: Exploring tradeoffs among environmental flows, cascaded small hydropower, and inter-basin water diversion projects

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JOURNAL OF ENVIRONMENTAL MANAGEMENT 2022年 308卷 114582-114582页

作者： Yin, Dongqin Li, Xiang Wang, Fang Liu, Yang Croke, Barry F. W. J. Jakeman, Anthony China Agr Univ Coll Land Sci & Technol Beijing Peoples R China China Inst Water Resources & Hydropower Res State Key Lab Simulat & Regulat Water Cycle River Beijing Peoples R China Minist Water Resources Key Lab Sediment Sci & Northern River Regulat Beijing Peoples R China Qinghai Univ State Key Lab Plateau Ecol & Agr Xining Peoples R China Australian Natl Univ Fenner Sch Environm & Soc Canberra Australia Australian Natl Univ Math Sci Inst Canberra Australia

Small hydropower (SHP) possesses significant economic, technical, and environmental advantages, and accounts for a large proportion of hydropower development in China. However, the concentrated, cascaded, and diversion-type development of SHP has resulted in long-distance dewatering of river sections, and inter-basin water transfers have led to severe exploitation of water resources and damage to river ecosystems. In this paper, the Datong River Basin, a secondary sub-basin of the Yellow River Basin in China, was selected as the illustrative case, which includes 22 hydropower projects (HPPs) and three inter-basin water diversion projects (WDPs). A nexus system model was established that used weighted multi-objective programming to consider three main objectives: the water resources utilization (local water withdrawal and inter-basin water transfer), energy production (by cascaded HPPs), and riverine environmental conservation. The Tennant method was used to estimate the environmental flows (e-flows) at the cross-sections immediately downstream of the dam/sluice gate and immediately downstream of the hydropower plant of diversion-type HPPs. The decreased percentage of regulated flow in comparison with runoff and the guaranteed rate of e-flow at the control cross-section were introduced to assess the degree of environmental impact to the river. Using a historical series of runoff data during 1956-2016 as the model input (i.e., implicit stochastic method), the multi-start solver of nonlinear programming of LINGO software was used to conduct optimizations and analyses for multiple scenarios (with/ without e-flow, with consideration of various levels of e-flow, and with/without water resources utilization). The sectoral linkages relating to the water-energy-ecosystem (WEE) nexus were quantitatively identified. The possible influences of different boundary conditions (i.e., initial/final reservoir storage, inter-basin water diversion capacity, and climate change) on the W

关键词： Reservoir operation Hydropower Inter-basin water diversion Environmental flows multi-objective programming

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Bi-Level multi-objective Production Planning Problem with multi-Choice Parameters: A Fuzzy Goal programming Algorithm

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ALGORITHMS 2019年第7期12卷 143-143页

作者： Kamal, Murshid Gupta, Srikant Chatterjee, Prasenjit Pamucar, Dragan Stevic, Zeljko Aligarh Muslim Univ Dept Stat & Operat Res Aligarh 202002 Uttar Pradesh India Jaipuria Inst Management Jaipur 302022 Rajasthan India MCKV Inst Engn Dept Mech Engn Howrah 711204 W Bengal India Univ Def Mil Acad Dept Logist Belgrade 11000 Serbia Univ East Sarajevo Fac Transport & Traff Engn Doboj Doboj 71000 Bosnia & Herceg

This paper deals with the modeling and optimization of a bi-level multi-objective production planning problem, where some of the coefficients of objective functions and parameters of constraints are multi-choice. A general transformation technique based on a binary variable has been used to transform the multi-choices parameters of the problem into their equivalent deterministic form. Finally, two different types of secularization technique have been used to achieve the maximum degree of individually membership goals by minimizing their deviational variables and obtained the most satisfactory solution of the formulated problem. An illustrative real case study of production planning has been discussed and, also compared to validate the efficiency and usefulness of the proposed work.

关键词： production planning bi-level programming multi-objective programming fuzzy goal programming multi-choice parameter

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An extended multi-objective mixed integer programming for water resources management through possibility theory

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ECOLOGICAL INFORMATICS 2019年 54卷 100992-000页

作者： Nematian, Javad Movahhed, Sevda Rezazadeh Univ Tabriz Fac Mech Engn Dept Ind Engn POB 51666-14766 Tabriz Iran

In this study, we develop an extended multi-objective mixed integer programming (EMOMIP) approach for water resources management under uncertainty, in which the parameters are fuzzy random variables while the decision variables are interval variables. Furthermore, some alternatives are considered to retrieve the difference between the quantities of promised water-allocation targets and the actual allocated water. Then, the proposed EMOMIP for the problem is solved by a new method using fuzzy random chance-constrained programming based on the idea of possibility theory. This method can satisfy both optimistic and pessimistic decision makers simultaneously. Finally, a real example is given to explain the proposed method.

关键词： Water resources management multi-objective programming Mixed integer programming Possibility theory

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Solving the multi-objective stochastic interval-valued linear fractional integer programming problem

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ASIAN-EUROPEAN JOURNAL OF MATHEMATICS 2022年第2期15卷

作者： Younsi-Abbaci, Leila Moulai, Mustapha USTHB Univ Fac Math LaROMaD Lab BP 32 Bab Ezzouar El Alia 16111 Algiers Algeria

In this paper, we consider a multi-objective Stochastic Interval-Valued Linear Fractional Integer programming problem (MOSIVLFIP). We especially deal with a multi-objective stochastic fractional problem involving an inequality type of constraints, where all quantities on the right side are log-normal random variables, and the objective functions coefficients are fractional intervals. The proposed solving procedure is divided in three steps. In the first one, the probabilistic constraints are converted into deterministic ones by using the chance constrained programming technique. Then, the second step consists of transforming the studied problem objectives on an optimization problem with an interval-valued objective functions. Finally, by introducing the concept of weighted sum method, the equivalent converted problem obtained from the two first steps is transformed into a single objective deterministic fractional problem. The effectiveness of the proposed procedure is illustrated through a numerical example.

关键词： Interval-valued function multi-objective programming log-normal random variable interval-valued linear fractional programming

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Solving stochastic programming problems using new approach to Differential Evolution algorithm

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EGYPTIAN INFORMATICS JOURNAL 2017年第2期18卷 75-86页

作者： Mohamed, Ali Wagdy Cairo Univ Inst Stat Studies & Res Operat Res Dept Giza 12613 Egypt

This paper presents a new approach to Differential Evolution algorithm for solving stochastic programming problems, named DESP. The proposed algorithm introduces a new triangular mutation rule based on the convex combination vector of the triangle and the difference vector between the best and the worst individuals among the three randomly selected vectors. The proposed novel approach to mutation operator is shown to enhance the global and local search capabilities and to increase the convergence speed of the new algorithm compared with conventional DE. DESP uses Deb's constraint handling technique based on feasibility and the sum of constraint violations without any additional parameters. Besides, a new dynamic tolerance technique to handle equality constraints is also adopted. Two models of stochastic programming (SP) problems are considered: Linear Stochastic Fractional programming Problems and multi-objective Stochastic Linear programming Problems. The comparison results between the DESP and basic DE, basic particle swarm optimization (PSO), Genetic Algorithm (GA) and the available results from where it is indicated that the proposed DESP algorithm is competitive with, and in some cases superior to, other algorithms in terms of final solution quality, efficiency and robustness of the considered problems in comparison with the quoted results in the literature. (C) 2016 Production and hosting by Elsevier B.V. on behalf of Faculty of Computers and Information, Cairo University.

关键词： Differential evolution Stochastic programming Fractional programming multi-objective programming

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Uncertain programming model for multi-item solid transportation problem

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INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS 2018年第4期9卷 559-567页

作者： Dalman, Hasan Yildiz Tech Univ Deparment Math Engn TR-34210 Esenler Turkey

In this paper, an uncertain multi-objective multi-item Solid Transportation Problem (MMSTP) based on uncertainty theory is presented. In the model, transportation costs, supplies, demands and conveyances parameters are taken to be uncertain parameters. There are restrictions on some items and conveyances of the model. Therefore, some particular items cannot be transported by some exceptional conveyances. Using the advantage of uncertainty theory, the MMSTP is first converted into an equivalent deterministic MMSTP. By applying convex combination method and minimizing distance function method, the deterministic MMSTP is reduced into single objective programming problems. Thus, both single objective programming problems are solved using Maple 18.02 optimization toolbox. Finally, a numerical example is given to illustrate the performance of the models.

关键词： multi-objective programming Solid transportation problem multi-item transportation problem Uncertain programming Uncertainty theory

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Distributed power generation programming with waste incineration generation and hybrid energy storage equipment

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2017年第4期33卷 2269-2279页

作者： Song, Zongyun Xiao, Xinli Niu, Dongxiao North China Elect Power Univ Sch Econ & Management Beinong St 2 Beijing 102206 Peoples R China

Under the current situation, distributed power generation becomes key solutions to the problems of environmental pollution and resources shortage that the electricity industry is facing. Rational power generation programming schemes will reduce energy consumption, and optimize energy structure on the premise of meeting the increasing requirements for electric energy. The multi-objective programming model was established to optimize economical and technical objectives of distributed generation system (DGS) containing waste incineration generation (WIG) and hybrid energy storage equipment (HESE), and then memorized-firefly algorithm (M-FA) is introduced to determine the model and installed capacity of various power generation units in distributed generation system. The case study demonstrated that the proposed programming model can obtain rational solutions with taking various objectives and constraints into consideration, and the M-FA shows the abilities of global search and better convergence in solving power generation programming problems, which will provide theoretic and practical references for the multi-objective programming problems of distributed generation system.

关键词： Distributed generation system multi-objective programming waste incineration generation hybrid energy storage equipment memorized-firefly algorithm

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Optimality for (h,φ)-multiobjective programming involving generalized type-I functions

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JOURNAL OF GLOBAL OPTIMIZATION 2008年第1期41卷 147-161页

作者： Yu, Guolin Liu, Sanyang N Natl Univ Res Inst Informat & Syst Computat Sci Yinchuan 750021 Peoples R China Xidian Univ Dept Appl Math Xian Peoples R China

Based upon Ben-Tal's generalized algebraic operations, new classes of functions, namely (h,phi)-type-I, quasi (h,phi)-type-I, and pseudo (h,phi)-type-I, are defined for a multi-objective programming problem. Sufficient optimality conditions are obtained for a feasible solution to be a Pareto efficient solution for this problem. Some duality results are established by utilizing the above defined classes of functions, considering the concept of a Pareto efficient solution.

关键词： multi-objective programming Pareto efficient solution (h,phi)-type-I functions Duality

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multi-choice goal programming formulation based on the conic scalarizing function

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APPLIED MATHEMATICAL MODELLING 2012年第3期36卷 974-988页

作者： Ustun, Ozden Dumlupinar Univ Fac Engn Dept Ind Engn TR-43100 Kutahya Turkey

The multi-choice goal programming allows the decision maker to set multi-choice aspiration levels for each goal to avoid underestimation of the decision. In this paper, we propose an alternative multi-choice goal programming formulation based on the conic scalarizing function with three contributions: (1) the alternative formulation allows the decision maker to set multi-choice aspiration levels for each goal to obtain an efficient solution in the global region, (2) the proposed formulation reduces auxiliary constraints and additional variables, and (3) the proposed model guarantees to obtain a properly efficient (in the sense of Benson) point. Finally, to demonstrate the usefulness of the proposed formulation, illustrative examples and test problems are included. (C) 2011 Elsevier Inc. All rights reserved.

关键词： multi-objective programming Goal programming multi-choice goal programming Conic scalarization

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Extensions of Pareto efficiency analysis to integer goal programming

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OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE 1999年第2期27卷 179-188页

作者： Tamiz, M Mirrazavi, SK Jones, DF Univ Portsmouth Portsmouth PO1 2UP Hants England

This paper focuses on the design, development and implementation of new Pareto efficiency detection and restoration techniques for integer goal programming. The design of the algorithms and their implementation issues within (an otherwise continuous) goal programming system are detailed. The differences between continuous and integer goal programming regarding Pareto efficiency detection and restoration analysis are described. The integer Pareto efficiency techniques have been applied to a selection of problems from different industrial contexts in order to assess their computational performance. Finally, Pareto restoration and detection techniques are applied to an integer goal programming problem to illustrate the methodology. (C) 1999 Elsevier Science Ltd. All rights reserved.

关键词： multi-objective programming integer goal programming Pareto efficiency intelligent analysis tools

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