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Deterministic approach for solving multi-objective non-smooth Environmental and Economic dispatch problem

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2019年第Jan.期104卷 880-897页

作者： Goncalves, Elis Balbo, Antonio Roberto da Silva, Diego Nunes Nepomuceno, Leonardo Baptista, Edrnea Cassia Soler, Edilaine Martins Unesp Univ Estadual Paulista Fac Engn FEB Dept Elect Engn BR-17033360 Bauru SP Brazil Unesp Univ Estadual Paulista FC Dept Math BR-17033360 Bauru SP Brazil Univ Sao Paulo Sao Carlos Sch Engn EESC Dept Elect Engn BR-13566590 Sao Carlos SP Brazil

The Environmental and Economic Dispatch Problem with Valve-Point loading effect representation (EEDP-VP) is a multi-objective, nonconvex and non-differentiable optimization problem. Due to these difficulties, it has been solved in the literature mainly by heuristic approaches, while deterministic approaches are scarce. Therefore, the main objectives of this paper are to propose a deterministic approach for solving this problem and compare its solutions with the ones obtained by some heuristic and deterministic approaches. The deterministic approach proposed has the following features: the multi-objective nature of the problem is handled by the Progressive Bounded Constraints (PBC) strategy, while the modified logarithmic barrier function method is used to solve the subproblems resulting from the PBC strategy;a smoothing technique is used to handle non-differentiability issues, while the inertia correction strategy is used so that only descent directions are generated. The methodology is applied to five generation systems and the results show that the Pareto-curve is obtained more efficiently when compared to other heuristic and deterministic optimization approaches.

关键词： Economic/environmental dispatch multi-objective programming Modified logarithmic barrier function Interior/exterior-point Smoothing functions methods

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ORDER ALLOCATION MODEL IN LOGISTICS SERVICE SUPPLY CHAIN WITH DEMAND UPDATING AND INEQUITY AVERSION: A PERSPECTIVE OF TWO OPTION CONTRACTS COMPARISON

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JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION 2021年第6期17卷 3269-3295页

作者： Liu, Weihua Shen, Xinran Wang, Di Wang, Jingkun Tianjin Univ Coll Management & Econ 92 Weijin Rd Tianjin 300072 Peoples R China

This paper considers an logistics service supply chain consisting of a logistics service integrator (LSI) and a number of functional logistics ser-vice providers (FLSPs). In the environment of demand updating, we focus on the inequity aversion among the FLSPs and introduce two option contracts (the reservation option contract and the option guarantee contract), build the multi-objective programming models, to explore effects of the inequity aver-sion behavior on the order allocation, and whether the two option contracts can mitigate the impact of inequity aversion on order allocation. Three im-portant conclusions are obtained after two option contracts comparisons: first, there is an optimal update time, at which point, the order allocation results reach the optimal value and tend to be stable. Second, two option contracts both can not only increase the total performance of the supply chain, but also mitigate the impact of inequity aversion on the allocation under certain condi-tions. Third, when demand decreases, the reservation option contract is better than option guarantee contract, in contrast, when demand increases, option guarantee contract is better.

关键词： Order allocation model demand updating option contract inequity aversion multi-objective programming

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A visual interactive approach for scenario-based stochastic multi-objective problems and an application

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JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY 2012年第12期63卷 1773-1787页

作者： Balibek, E. Koksalan, M. Middle E Tech Univ Dept Ind Engn TR-06531 Ankara Turkey Turkish Treasury Ankara Turkey

In many practical applications of stochastic programming, discretization of continuous random variables in the form of a scenario tree is required. In this paper, we deal with the randomness in scenario generation and present a visual interactive method for scenario-based stochastic multi-objective problems. The method relies on multi-variate statistical analysis of solutions obtained from a multi-objective stochastic problem to construct joint confidence regions for the objective function values. The decision maker (DM) explores desirable parts of the efficient frontier using a visual representation that depicts the trajectories of the objective function values within confidence bands. In this way, we communicate the effects of randomness inherent in the problem to the DM to help her understand the trade-offs and the levels of risk associated with each objective. Journal of the Operational Research Society (2012) 63, 1773-1787. doi:10.1057/jors.2012.25 Published online 11 April 2012

关键词： multi-objective programming interactive methods stochastic programming public debt management

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The "weak-link" approach to network DEA for two-stage processes

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2016年第2期254卷 481-492页

作者： Despotis, Dimitris K. Koronakos, Gregory Sotiros, Dimitris Univ Piraeus Dept Informat 80 Karaoli & Dimitriou Piraeus 18534 Greece

We introduce in this paper a new definition for the overall system efficiency in network DEA, which is inspired by the "weak link" notion in supply chains and the maximum-flow/minimum- cut problem in networks. We use a two-phase max-min optimization technique in a multi-objective programming framework to estimate the individual stage efficiencies and the overall system efficiency in two-stage processes of varying complexity. This enables us to estimate unique and unbiased efficiency scores and, if required, to drive the efficiency assessments effectively in line with specific priorities given to the stages. A comparison with the multiplicative decomposition approach on data drawn from the literature brings into light the advantages of our method. (C) 2016 Elsevier B.V. All rights reserved.

关键词： Network DEA Two-stage processes Weak link multi-objective programming

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Water quality management in a wetland system using an inexact left-hand-side chance-constrained fuzzy multi-objective approach

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STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT 2016年第2期30卷 621-633页

作者： Ji, Yao Huang, Guohe Sun, Wei Li, Yanfeng North China Elect Power Univ SC Resources & Environm Res Acad MOE Key Lab Reg Energy & Environm Syst Optimizat Beijing 102206 Peoples R China Univ Regina Inst Energy Environm & Sustainable Commun Regina SK S4S 0A2 Canada

Water quality management is a significant item in the sustainable development of wetland system, since the environmental influences from the economic development are becoming more and more obvious. In this study, an inexact left-hand-side chance-constrained fuzzy multi-objective programming (ILCFMOP) approach was proposed and applied to water quality management in a wetland system to analyze the tradeoffs among multiple objectives of total net benefit, water quality, water resource utilization and water treatment cost. The ILCFMOP integrates interval programming, left-hand-side chance-constrained programming, and fuzzy multi-objective programming within an optimization framework. It can both handle multiple objectives and quantify multiple uncertainties, including fuzziness (aspiration level of objectives), randomness (pollutant release limitation), and interval parameters (e. g. water resources, and wastewater treatment costs). A representative water pollution control case study in a wetland system is employed for demonstration. The optimal schemes were analyzed under scenarios at different probabilities (pi, denotes the admissible probability of violating the constraint i). The optimal solutions indicated that, most of the objectives would decrease with increasing probability levels from scenarios 1 to 3, since a higher constraint satisfaction probability would lead to stricter decision scopes. This study is the first application of the ILCFMOP model to water quality management in a wetland system, which indicates that it is applicable to other environmental problems under uncertainties.

关键词： Inexact chance-constrained programming multi-objective programming Water quality Wetland Uncertainty

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Bi-level multi-objective traffic network optimisation with sustainability perspective

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EXPERT SYSTEMS WITH APPLICATIONS 2018年 104卷 294-306页

作者： Kolak, Orhan Ilker Feyzioglu, Orhan Noyan, Nilay Galatasaray Univ TR-34349 Istanbul Turkey Sabanci Univ TR-34956 Istanbul Turkey

Recent technological advancements provide a level of mobility never seen before to modern societies. Sustaining today's economy and societies depend on maintaining this mobility. However, this mobility also causes undesirable effects, especially in high urban population areas. Even though, higher priority is given to public transport in metropolitan areas, road network is still an important part of everyday commute and should be planned and managed with great care. In this study, we propose an optimisation methodology that would help the traffic authorities to better predict the results of strategic management decisions in a realistic traffic model. We formulate a bi-level multi-objective traffic optimisation model with a sustainability perspective. The upper level of the proposed model considers the traffic authority's management strategies while the lower level considers the traffic users' decisions. The lower level is modelled using the Stochastic User Equilibrium since it allows more realistic results than the deterministic one. A case study is provided to illustrate the proposed model. The proposed methodology provides an avenue for understanding the trade-offs among conflicting objectives and for designing an environmentally and socially sustainable transportation system. More importantly, it builds the foundation for an intelligent traffic management decision support system. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Traffic network multi-objective programming Bi-level optimisation Sustainability Stochastic User Equilibrium

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Group fuzzy comprehensive evaluation method under ignorance

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EXPERT SYSTEMS WITH APPLICATIONS 2019年 126卷 92-111页

作者： Du, Yuan-Wei Wang, Su-Su Wang, Ying-Ming Ocean Univ China Management Coll Qingdao 266100 Shandong Peoples R China Fuzhou Univ Decis Sci Inst Fuzhou 350116 Fujian Peoples R China Minist Educ Marine Dev Studies Inst OUC Key Res Inst Humanities & Social Sci Univ Qingdao 266100 Shandong Peoples R China

This paper aims at solving such a group fuzzy comprehensive evaluation (FCE) problem that the global or local ignorance may exist in judgments made by experts and the importance degrees of experts are different. The basic probability assignment (BPA) function is used to extract the expert's judgment information and the super fuzzy relationship matrices consisting of the individual type and the general type are constructed by Shafer's discounting and Dempster's rule. Then each type of super fuzzy relationship matrix is combined with factor weight set via a specified fuzzy operator and the comprehensive evaluation result that is a belief distribution on the power set of grade levels is obtained. A multi-objective programming model is established to compute the optimal belief distribution on each grade level and an algorithm is summarized to derive the final grade level that the evaluated alternative belongs to. Moreover, the numerical comparisons between the proposed method and relevant existing methods are given to clarify the advantages of the proposed method. Finally, an illustrative example is provided to demonstrate the applicability of the proposed method and algorithm. It is worth noting that the proposed method can be easily converted into a core algorithm, which is benefit for developing fuzzy expert system from the perspective of ignorance, and thus it has an important impact and significance on expert and intelligent systems. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Fuzzy comprehensive evaluation Group decision making Shafer's discounting Dempster's rule Super fuzzy relationship matrix multi-objective programming

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Optimization and Evaluation of Environmental Operations for Three Gorges Reservoir

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WATER RESOURCES MANAGEMENT 2016年第10期30卷 3553-3576页

作者： Hu, Ming Huang, Guo H. Sun, Wei Ding, Xiaowen Li, Yongping Fan, Bin Chinese Acad Sci Res Ctr Ecoenvironm Sci State Key Lab Environm Aquat Chem Beijing 100085 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China North China Elect Power Univ SC Resources & Environm Res Acad MOE Key Lab Reg Energy & Environm Syst Optimizat Beijing 102206 Peoples R China Univ Regina Fac Engn & Appl Sci Environm Syst Engn Program Regina SK S4S 0A2 Canada Univ Regina Inst Energy Environm & Sustainable Commun Regina SK S4S 7H9 Canada

This study proposed a multi-objective environmental reservoir operation methodology (MOEROM) and applied the new methodology to the Three Gorges Reservoir (TGR) in China. The MOEROM directly incorporated the statistical water quality models in the objective functions to reflect the response relationships between reservoir operations and water quality in three tributaries (the Xiangxi River, the Daning River and the Xiaojing River). A real-coded genetic algorithm with self-adaptive crossover operators was employed to solve the environmental reservoir operation model. And four different MCDA approaches (AHP, TOPSIS, Fuzzy AHP, and Fuzzy TOPSIS) were proposed to evaluate the optimal operational schemes. The results showed that TOPSIS and AHP were more suitable for selecting the schemes than the others because of the larger fluctuations. To demonstrate the advantage of MOEROM, the environmental operation schemes were compared with traditional and practical operation schemes in 2013. The advantages of the environmental operation scheme over the others were that it would help reach a compromise between economic benefit, flood control and water quality improvement. In the future, more water quality indices, uncertainties in water environmental information, and more efficient algorithms would be further considered and researched.

关键词： multi-objective programming Environmental operation Genetic algorithm MCDA Three Gorges Reservoir

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Evaluation of multi-objective optimization approaches for solving green supply chain design problems

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OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE 2017年 68卷 168-184页

作者： Kadzinski, Milosz Tervonen, Tommi Tomczyk, Michaf K. Dekker, Rommert Poznan Univ Tech Inst Comp Sci Piotrowo 2 PL-60965 Poznan Poland Evidera Ltd London England Erasmus Univ Erasmus Sch Econ Econometr Inst NL-3000 DR Rotterdam Netherlands

This paper evaluates the applicability of different multi-objective optimization methods for environmentally conscious supply chain design. We analyze a case study with three objectives: costs, CO2 and fine dust (also known as PM - Particulate Matters) emissions. We approximate the Pareto front using the weighted sum and epsilon constraint scalarization methods with pre-defined or adaptively selected parameters, two popular evolutionary algorithms, SPEA2 and NSGA-II, with different selection strategies, and their interactive counterparts that incorporate Decision Maker's (DM's) indirect preferences into the search process. Within this case study, the CO2 emissions could be lowered significantly by accepting a marginal increase of costs over their global minimum. NSGA-II and SPEA2 enabled faster estimation of the Pareto front, but produced significantly worse solutions than the exact optimization methods. The interactive methods outperformed their a posteriori counterparts, and could discover solutions corresponding better to the DM preferences. In addition, by adjusting appropriately the elicitation interval and starting generation of the elicitation, the number of pairwise comparisons needed by the interactive evolutionary methods to construct a satisfactory solution could be decreased. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Supply chain management Green logistics multi-objective programming Indirect preference information Evolutionary algorithms Interactive evolutionary multi-objective optimization

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Designing and evaluating sustainable logistics networks

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2008年第2期111卷 195-208页

作者： Frota Neto, J. Quariguasi Bloemhof-Ruwaard, J. M. van Nunen, J. A. E. E. van Heck, E. Erasmus Univ RSM NL-3000 DR Rotterdam Netherlands

Consumers and legislation have pushed companies to re-design their logistic networks in order to mitigate negative environmental impacts. The objective in the design of logistic networks has changed, therefore, from cost minimization only, to cost and environmental impact minimization. The objective of this paper is to develop a framework for the design and evaluation of sustainable logistic networks, in which profitability and environmental impacts are balanced. In this paper, we review the main activities affecting environmental performance and cost efficiency in logistic networks, we show the advantages of using multi-objective programming (MOP) to design sustainable networks, we present the expected computational difficulties of using the MOP approach in the design of sustainable networks, and we introduce a technique, based on the commonalities between data envelopment analysis (DEA) and MOP, to evaluate the efficiency of existing logistic networks. The European pulp and paper industry will be used to illustrate our findings. (c) 2007 Elsevier B.V. All rights reserved.

关键词： supply chain design sustainable supply chain eco-efficiency multi-objective programming data envelopment analysis

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