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Oil-importing optimal decision considering country risk with extreme events: A multi-objective programming approach

COMPUTERS & OPERATIONS RESEARCH 2014年第Feb.期42卷 108-115页

作者： Li, Jianping Tang, Ling Sun, Xiaolei Wu, Dengsheng Chinese Acad Sci Inst Policy & Management Beijing 100190 Peoples R China Chinese Acad Sci Grad Univ Beijing 100049 Peoples R China

From perspective of energy security, this study focuses on oil-importing optimal decision based on multi-objective programming approach. Different from other models, country risk is considered as the main objective to minimize risk exposure of importing disruption. What is more, this model connects emergency management with programming, and optimal decisions are solved under different scenarios of emergency, where one given kind of extreme events break out and impact exporting regions to different degrees. Specifically, two main steps are involved in the proposed methodology, including impact analysis of the extreme events and optimization programming under scenarios of emergency. The first step is to statistically analyze whether and to what extent the given extreme events impact country risk of oil-exporting sources. Secondly, a multi-objective programming model is formulated, and optimal decision is simulated under different scenarios with extreme events. For illustration, China's oil-importing optimization is performed to verify the practicability of the novel methodology. The experimental results suggest that wars in Middle East may significantly enhance country risk of Middle East;and China's oil-importing optimal plan should be changed correspondingly. This further indicates that the proposed methodology can be utilized as an effective tool to adjust oil-importing plan according to certain extreme events. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： multi-objective programming Optimal decision Country risk Emergency management Oil-importing security

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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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Optimizing the industrial structure of a watershed in association with economic-environmental consideration: an inexact fuzzy multi-objective programming model

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JOURNAL OF CLEANER PRODUCTION 2013年 42卷 116-131页

作者： Zhou, M. Chen, Q. Cai, Y. L. Peking Univ Coll Urban & Environm Sci Beijing 100871 Peoples R China Qinghai Normal Univ Coll Life & Geog Sci Xining 810008 Qinghai Peoples R China

An inexact fuzzy multi-objective programming model (IFMOP) is developed in this study for dealing with industrial structure optimization problems under uncertainty. The IFMOP model is formulated based on integration of an inexact linear programming (ILP), fuzzy flexible optimization (FFO), and multi-objective programming (MOP). It improves upon the existing industrial structure optimization model with advantages in uncertainty reflection, model coupling, data availability and computational requirement. The model can deal with uncertainties expressed as discrete intervals and fuzzy sets. Therefore, it can effectively reflect dynamic, interactive complex, and uncertain characteristics of industrial system without unrealistic simplification. Moreover, the model can be used for supporting temporal and spatial optimization of industrial structure under a variety of environmental and socio-economic conditions. The developed model is first applied to a real case of planning industrial structure of South Four Lake watershed in Shandong province, China. Results demonstrated that the model could help decision makers generate stable and balanced industrial structure patterns, gain in-depth insights into effects of the uncertainties, and analyze trade-offs among economical objective, environmental protection and social demand. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： Inexact linear programming Fuzzy flexible programming multi-objective programming Hybrid uncertain model Industrial structure optimization

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Fuzzy goal programming algorithm for solving decentralized bi-level multi-objective programming problems

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FUZZY SETS AND SYSTEMS 2009年第18期160卷 2701-2713页

作者： Baky, Ibrahim A. Benha Univ Benha Higher Inst Technol Dept Basic Sci El Kalyoubia Egypt

This paper presents fuzzy goal programming (FGP) algorithm for solving decentralized bi-level multi-objective programming (DBL-MOP) problems with a single decision maker at the upper level and multiple decision makers at the lower level. A FGP algorithm for DBL-multi-objective linear programming (DBL-MOLP) problems is proposed. This algorithm is extended to solve bi-level multi-objective linear fractional programming (DBL-MOLFP) problems. In the proposed algorithm, the membership functions for the defined fuzzy goals of all objective functions at the two levels as well as the membership functions for vector of fuzzy goals of the decision variables controlled by ULDM are developed in the model formulation of the problem. Then FGP approach is used to achieve highest degree of each of the membership goals by minimizing their deviational variables and thereby obtaining the most satisfactory solution for all decision makers. Illustrative numerical examples are given to demonstrate the proposed algorithm. (C) 2009 Published by Elsevier B.V.

关键词： Decentralized bi-level programming multi-objective programming Linear fractional programming Goal programming Fuzzy mathematical programming Fuzzy goal programming

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A Comparison of Single- and multi-objective programming Approaches to Problems with multiple Design objectives

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JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY 2010年第1期61卷 39-50页

作者： Yaman, Sibel Lee, Chin-Hui Georgia Inst Technol Sch Elect & Comp Engn Atlanta GA 30332 USA

In this paper, we propose and compare single- and multi-objective programming ( MOP) approaches to the language model (LM) adaptation that require the optimization of a number of competing objectives. In LM adaptation, an adapted LM is found so that it is as close as possible to two independently trained LMs. The LM adaptation approach developed in this paper is based on reformulating the training objective of a maximum a posteriori ( MAP) method as an MOP problem. We extract the individual at least partially conflicting objective functions, which yields a problem with four objectives for a bigram LM: The first two objectives are concerned with the best fit to the adaptation data while the remaining two objectives are concerned with the best prior information obtained from a general domain corpus. Solving this problem in an iterative manner such that each objective is optimized one after another with constraints on the rest, we obtain a target LM that is a log-linear interpolation of the component LMs. The LM weights are found such that all the ( at least partially conflicting) objectives are optimized simultaneously. We compare the performance of the SOP- and MOP-based solutions. Our experimental results demonstrate that the ICO method achieves a better balance among the design objectives. Furthermore, the ICO method gives an improved system performance.

关键词： multi-objective programming Statistical language modeling Automatic speech recognition

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A multi-objective programming approach to feed ration balancing and nutrient management

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AGRICULTURAL SYSTEMS 2001年第3期67卷 201-215页

作者： Tozer, PR Stokes, JR Penn State Univ University Pk PA 16802 USA

This paper examines the potential to use multiple objective programming to reduce nutrient excretion from dairy cows through incorporation of nutrient excretion functions into a ration formulation framework. In a typical ration formulation model, a ration is formulated to minimize cost while providing sufficient nutrients to meet the needs of the animal type being fed. To reduce the nutrient loading, rations can be formulated to minimize cost, and nitrogen and phosphorus excretion using multiple objective programming. Rations were initially formulated to minimize cost, nitrogen excretion and phosphorus excretion. Compromise programming was then utilized to examine the impacts on ration formulation of combining the three individual objectives. The multiple objective ration formulation reduced phosphorus excretion by 5% and marginally reduced nitrogen excretion with a small increase in ration cost compared to the single objective minimum cost ration. multiple objective programming does have the potential to reduce nutrient excretion. (C) 2001 Elsevier Science Ltd. All rights reserved.

关键词： MINIMAX multi-objective programming nitrogen phosphorous rations dairy cows

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PREEMPTIVE AND NON-PREEMPTIVE multi-objective programming - RELATIONSHIPS AND COUNTEREXAMPLES

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JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS 1983年第2期39卷 173-186页

作者： SHERALI, HD SOYSTER, AL Assistant Professor Department of Industrial Engineering and Operations Research Virginia Polytechnic Institute and State University Blacksburg Virginia Professor Department of Industrial Engineering and Operaions Research Virginia Polytechnic Institute and State University Blacksburg Virginia

In this paper, we formally establish connections between two standard approaches proposed for resolving multi-objective programs, namely, the nonpreemptive and the preemptive methods. We demonstrate in the linear case that, if the preemptive problem has an optimal solution, then there exists a set of weights for the nonpreemptive problem, such that any optimal solution to the nonpreemptive problem is optimal to the preemptive problem. Conversely, and more importantly, any optimal solution to the preemptive problem is optimal to the nonpreemptive problem. A similar result is established for arbitrary multi-objective functions being optimized over a finite discrete set. Thus, the preemptive problem is subsumed within the nonpreemptive problem in these cases. Although we actually construct a set of equivalent weights, we do not advocate our technique as a computational device for solving the preemptive problem. However, a previous attempt (Ref. 1), which does prescribe a set of equivalent weights to solve a preemptive problem as a linear program, is shown to be erroneous. Moreover, our constructive proof exhibits the features of the problem which govern the determination of such equivalent weights.

关键词： multi-objective programming goal programming preemptive priority lexicographic ordering

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Risk integration and optimization of oil-importing maritime system: a multi-objective programming approach

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ANNALS OF OPERATIONS RESEARCH 2015年第1期234卷 57-76页

作者： Li, Jianping Sun, Xiaolei Wang, Fei Wu, Dengsheng Chinese Acad Sci Inst Policy & Management Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China

Optimization of oil-imports portfolio has attracted considerable attention from corporate operators as well as government and its strategic planners. This paper proposes a methodology of oil-importing portfolio optimization based on the fundamental process of intelligent knowledge management (IKM). Centering on the maritime system, optimal solutions are derived for different risk scenarios. Specifically, three main steps are involved: formulating a multi-objective programming (MOP) model, integrating the composite risk exposure with domain knowledge, as well as knowledge acquisition on risk scenarios and influence of transportation risk. For illustration, optimization of the maritime structure of China's oil imports is performed to verify the practicability of the novel methodology. Experimental results suggest that the risk-adjusted factors' augmentation can spread the risk wider and eventually enhance risk optimization capability in the MOP model. With a given risk-adjusted factor, the influence of transportation risk on an optimal plan is simulated and analyzed. The paper uses the fundamental IKM process for transforming the data (rough knowledge) into intelligent knowledge (transformation from T1 to T2) in the empirical study on risk integration and optimization of oil-importing maritime system. It is helpful to explore hidden patterns. What's more, results suggest that it is necessary to highlight the influence of transportation risk in order to support decision makers from different domains to obtain more reasonable optimal solutions.

关键词： Risk integration Country risk Transportation risk Intelligent knowledge management multi-objective programming

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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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A multi-objective programming approach, integrated into the TOPSIS method, in order to optimize product design;in three-dimensional concurrent engineering

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COMPUTERS & INDUSTRIAL ENGINEERING 2013年第4期64卷 875-885页

作者： Shidpour, H. Shahrokhi, M. Bernard, A. Univ Kurdistan Dept Engn Sanandaj Iran Ecole Cent Nantes F-44321 Nantes 3 France

This paper proposes a new method to address a three-dimensional concurrent engineering (3D-CE) approach. It uses a multi-objective Linear programming (MOLP) model integrated to the TOPSIS method in order to determine the best configuration product design, assembly process and suppliers of components. This method is able to involve various supply chain strategies by considering qualitative and quantitative criteria in the early stages of the new product development (NPD) process. It also applies the Fuzzy Analytic Hierarchy Process (FAHP) method to determine the relative importance of criteria defined to evaluate configurations of design alternatives, assembly processes and suppliers of components. A sensitivity analysis from different parameters in the model that affect the selection of the best design alternative is performed by creating a computer program using visual studio. A numerical example is used to demonstrate method efficacy and finally, the paper suggests some areas for future research. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： New product development TOPSIS 3D-CE Qualitative and quantitative parameters multi-objective programming FAHP

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