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A multi-objective programming method for solving network DEA

APPLIED SOFT COMPUTING 2014年第0期24卷 406-413页

作者： Kao, Han-Ying Chan, Chieh-Yu Wu, Dong-Jyun Natl Dong Hwa Univ Dept Comp Sci & Informat Engn Shoufeng 97401 Hualien Taiwan

This study proposes the multi-objective programming (MOP) method for solving network DEA (NDEA) models. In the proposed method, the divisional efficiencies (within an organization) and the overall efficiency of the organization are formulated as separate objective functions in the multi-objective programming model. Compared with conventional DEA where the intermediate processes and products are ignored, this work measures the organization's overall efficiency without neglecting the efficiencies of its subunits. Two case studies demonstrate the proposed NDEA-MOP's utility in measuring the efficiencies of an organization with concerning interactive internal process. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Network DEA multi-objective programming BCC CCR Divisional efficiency Case studies

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A fuzzy dependent-chance interval multi-objective stochastic expected value programming approach for irrigation water resources management under uncertainty

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DESALINATION AND WATER TREATMENT 2021年 212卷 17-30页

作者： Wang, Youzhi Li, Zhong Liu, Liu Guo, Ping China Agr Univ Ctr Agr Water Res China Beijing 100083 Peoples R China McMaster Univ Dept Civil Engn Hamilton ON L8S 4L8 Canada Minist Agr & Rural Affairs Wuwei Expt Stn Efficient Water Use Agr Wuwei 733000 Peoples R China

In this study, a fuzzy dependent-chance interval multi-objective stochastic expected value programming model is developed for irrigation water resources management under uncertainties. It incorporates fuzzy dependent-chance programming, stochastic expected value programming, interval programming into multi-objective programming. Compared with conventional programming methods, it can quantify the relationship between the expected values of stochastic variables and the fuzzy goals of expected values set by decision-makers through the satisfactory degrees, and trade-off the relationship amid multiple satisfactory degrees selected as objective functions. Besides, it can cope with uncertainties expressed as interval numbers, fuzzy numbers, and stochastic variables. Moreover, the fairness of water allocation constraints formulated by the GINI coefficient can achieve the interactions between fair water allocation and satisfactory degrees. The model is applied to a real case study of irrigation water resources management of different water types (i.e., surface water and groundwater) under different water flow levels (high, medium, and low flow levels) in the midstream region of the Heihe River basin, northwest China. The results reveal that: (1) maximum water demands of wheat and economic crop are satisfied while that of corn is not met under three flow levels;(2) the expected economic benefit and water shortages of crops have positive relationships with water allocation while the expected canal water loss has a negative relationship with water allocation;(3) the bigger expected economic benefit results in the higher satisfactory degree of the expected economic benefit while the lower expected water shortage and canal water loss lead to higher satisfactory degrees of expected water shortage and canal water loss. It shows that the developed model can overcome the disadvantages of the single-objective programming of putting attention to the satisfactory degree of a kind of ex

关键词： Irrigation water allocation Interval programming Stochastic expected value programming Fuzzy dependent-chance programming multi-objective programming Uncertainty

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A multi-objective programming model of dynamic adjusting flight traffic

A multi-objective programming model of dynamic adjusting fli...

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International Conference on Mechanical, Electronic and Engineering Technology (ICMEET)

作者： Zhang, Zhaoning Hao, Zhongzhou Gao, Zheng Civil Aviat Univ China Coll Air Traff Management Tianjin 300300 Peoples R China Tianjin Stn Air Traff Management Tianjin 300300 Peoples R China

ISBN: (纸本)9783038350491

To alleviate the conflicts between the current flight traffic demand and the resource constraints of airspace, we need to improve the restrictions of flow allocation caused by the static air traffic flow allocation mode. The author analyzes the optimal allocation problem of dynamic adjusting flight flow and draws the conclusion that the problem should satisfy multiple targets, such as low flight delays, low flight cost and balancing the load of the route. Then consider a variety of limiting factors, such as the capacity of the route, flight planning, emergency situations, etc. Then establish multi-objective programming model of dynamic adjusting flight traffic. The objective function is determined by the flight cost, the flight delays and the value of the load balance. And the value of the load balance was first proposed according to the idea of least squares method. Then solve the model based on linear weighted technique. Finally the numerical result shows that the model can satisfy the multiple objectives and dynamic adjust the flight traffic optimally, that proves the rationality and validity of the model and the algorithm.

关键词： air traffic route flight traffic dynamic allocation model multi-objective programming

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Mixed duality of multi-objective programming

Mixed duality of multi-objective programming

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International Conference on Information Technology and Computer Application Engineering (ITCAE)

作者： Miao, Hong Mei Li, Xiang You Yanan Univ Coll Physis & Elect Informat Yanan Shaanxi Peoples R China Yanan Univ Coll Math & Comp Sci Yanan Shaanxi Peoples R China

In this paper, a class of multi-objective programming is considered, in which related functions are B - (p, r, a)-invex functions, mixed dual problem is researched, many duality theorems are proved under weaker convex... 详细信息

ISBN: (纸本)9781315813288;9781138000797

关键词： B - (p, r, a)-invex function multi-objective programming mixed duality

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Bi-level multi-objective programming problem with fuzzy demands: a fuzzy goal programming algorithm

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OPSEARCH 2014年第2期51卷 280-296页

作者： Baky, Ibrahim A. Eid, Mohamed H. El Sayed, Mohamed A. Benha Univ Fac Engn Dept Basic Sci Banha El Qalyoubia Egypt Benha Univ Fac Engn Shoubra Dept Engn Math & Phys Banha El Qalyoubia Egypt

In this paper, a fuzzy goal programming (FGP) algorithm for solving bi-level multi- objective programming problems with fuzzy demands is presented. These fuzzy demands reflect the experts' imprecise or fuzzy understandings of the nature of parameters in the problem formulation process are assumed to be characterized as fuzzy numbers. Using the level sets of fuzzy parameters, the corresponding non fuzzy bilevel programming problem is introduced. 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 the vector of decision variables controlled by FLDM are developed in the model formulation of the problem. Then FGP algorithm is used to achieve the 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 example is given to demonstrate the proposed algorithm.

关键词： Bi-level programming Fuzzy sets Fuzzy demands Goal programming Fuzzy goal programming multi-objective programming

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An interactive dynamic multi-objective programming model to support better land use planning

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LAND USE POLICY 2014年 36卷 13-22页

作者： Chang, Yang-Chi Ko, Tsung-Ting Natl Sun Yat Sen Univ Dept Marine Environm & Engn Kaohsiung 80424 Taiwan Helmholtz Zentrum Geesthacht Inst Coastal Res D-21502 Geesthacht Germany

This study develops a dynamic multi-objective programming (DMOP) approach to handle problems of optimization under conditions of uncertainty typified by multiple goals and dynamic subsystems. The proposed approach seamlessly integrates multi-objective programming, fuzzy set theory, and system dynamics tools to conduct optimal land use planning in dynamic and complex environmental systems. Based on the DMOP approach, this study constructs an interactive dynamic multi-objective programming model, investigates the connection between land use and future urban development, and incorporates the preferences of decision makers using a compromise index. A case study from Taiwan shows that the proposed modeling framework can accommodate more complete information, allowing improvements to be made in strategic planning for land use. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Land use planning multi-objective programming Fuzzy set theory System dynamics

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Uncertain programming model for designing multi-objective reverse logistics networks

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CLEANER LOGISTICS AND SUPPLY CHAIN 2024年 11卷

作者： Xia, Hanbing Chen, Zhiyuan Milisavljevic-Syed, Jelena Salonitis, Konstantinos Cranfield Univ Sustainable Mfg Syst Ctr Sch Aerosp Transport & Mfg Cranfield MK43 0AL England

Given the contradiction between the rapid growth of products and the modest recovery rate of end-of-life products, there is a pressing need to understand the societal significance of establishing a reverse logistics network for end-of-life products. This research constructs an open-loop five-tier reverse logistic network model encompassing customers, centres for collection, disassembly and inspection, remanufacturing, and disposal. A multi-objective mixed-integer nonlinear programming model under uncertainty has been developed. Unlike previous research, this model accounts for surrounding residents' disutility of facilities while simultaneously minimizing economic costs and environmental impact. Besides, uncertainty theory is introduced in solving the proposed model. More specifically, the formulated model converts all uncertain variables into uncertain distributions by implementing the uncertain multi-objective programming method. Furthermore, a customised non- dominated sorting genetic algorithm III (NSGA-III) is proposed and is employed for the first time to address facility selection and recycling volume distribution within the network. The model is then validated using a real- life case study focusing on end-of-life vehicles in Changchun, China. This research could assist decision-makers in both governmental and private sectors in achieving a balanced approach to the interests of the economy, environment, and local communities comprehensively when designing reverse supply chains.

关键词： Reverse logistics network multi-objective programming Uncertainty theory End-of-life products Non-dominated sorting genetic algorithm III

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multi-choice conic goal programming model-based network data envelopment analysis

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RAIRO-OPERATIONS RESEARCH 2024年第4期58卷 3391-3416页

作者： Deliktas, Derya Ustun, Ozden Demirtas, Ezgi Aktar Arapoglu, Rifat Aykut Kutahya Dumlupinar Univ Fac Engn Dept Ind Engn Kutahya Turkiye Aksaray Univ Fac Engn Dept Ind Engn Aksaray Turkiye Eskisehir Osmangazi Univ Fac Engn Dept Ind Engn Eskisehir Turkiye

In multi-stage processes, classical Data Envelopment Analysis (DEA) acts like a black box and measures the efficiency of decision-making units (DMUs) without considering the internal structure of the system. Unlike classical DEA, recent studies have shown that the overall system efficiency scores are more meaningful if researched using the Network DEA (NDEA) methodology. NDEA performs simultaneous efficiency evaluations of sub-processes and the entire system. Recently, the composition method integrated with multi-objective programming (MOP) has been preferred by many authors to alleviate the drawbacks of earlier methods such as decomposition, slack-based measure (SBM) and the system-centric approach. This study proposes a novel approach incorporating multi-Choice Conic Goal programming into the NDEA (MCCGP-NDEA). It provides a more accurate representation of the Pareto front by revealing potential Pareto optimal solutions which are overlooked by the composition methods. Due to its ability to modify stage weights based on the decision makers' (DMs) preferences, it is likely to gather more samples from the Pareto surface. Computational results on available benchmark problems confirm that the proposed MCCGP-NDEA is a viable alternative to existing methods.

关键词： Data envelopment analysis network DEA multi-choice conic goal programming multi-objective programming

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Optimization of a quadratic programming problem over an integer efficient set

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JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS 2024年 441卷

作者： Prerna Sharma, Vikas TIET Sch Math Patiala Punjab India

multi-objective programming problem often contains numerous efficient solutions, which con-fuses the decision-maker. To assist in selecting the most desirable solution, optimizing a function over the efficient set becomes crucial. In this paper, we present a novel method for optimizing a general quadratic function over the efficient set of a multi-objective integer linear programming problem. To solve this problem, a ranking approach and efficiency test is utilized. The proposed methodology obtains a globally optimal solution by systematically scanning ranked solutions of an integer quadratic programming problem until the efficiency condition is satisfied. For generating ranked solutions, we construct a related integer linear programming problem. Then, ranked solutions of the integer linear programming problem are used for enumerating ranked solutions of the integer quadratic programming problem. The convergence of our algorithm is established theoretically, and its steps are illustrated using a numerical example. Aparticular case of the proposed method for optimizing a linear function over the efficient set of a multi-objective integer linear programming problem is also discussed. Further, extensive computational results demonstrate the effectiveness of our method for solving problems with large number of constraints, variables, and objective functions. Moreover, comparative analysis shows that the developed algorithm came out to be computationally more efficient as compared to the existing state-of-the-art algorithms.

关键词： Efficient set multi-objective programming Quadratic programming Integer programming

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Mathematical programming models to assist the evaluation of shipbrokers

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INTELLIGENT DECISION TECHNOLOGIES-NETHERLANDS 2024年第1期18卷 407-416页

作者： Koronakos, Gregory Smirlis, Yiannis Plitsos, Stathis Univ Piraeus Dept Informat Piraeus Greece Univ Pireaus Sch Econ Business & Int Studies Piraeus Greece Univ Piraeus Dept Ind Management & Technol Piraeus Greece

Shipbrokers play a key role in maritime industry by acting as intermediates between shipping companies and the market. They undertake various chartering, buying or selling operations. In this paper, we propose a mathematical programming approach for the evaluation and selection of shipbrokers. Specifically, the score of each ship broker is a composite measure that is derived by aggregating a set of performance criteria, e.g., reputation, etc. The developed mathematical programming models enable the aggregation and weighting of the criteria. We employ three optimization models to explore the effect of different weighting schemes on the scores and ranking of the shipbrokers. The models that provide a common set of weights for all the shipbrokers establish the appropriate ground for comparisons among them. Also, our models facilitate the incorporation of user priorities over the criteria in the form of weight restrictions. The proposed approach is illustrated by assessing seven shipbroker offers for selling a dry-bulk ship using four criteria, namely revenue, brokerage fee, brokerage time and terms & conditions.

关键词： Shipbrokers maritime industry mathematical programming multi-objective programming

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