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A Two-Stage multi-objective programming Model to Improve the Reliability of Solution

INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS 2020年第1期13卷 433-443页

作者： Jin, Chenxia Li, Fachao Feng, Kaixin Guo, Yunfeng Hebei Normal Univ Sch Math Sci Shijiazhuang 050024 Hebei Peoples R China Hebei Univ Sci & Technol Sch Econ & Management Shijiazhuang 050018 Hebei Peoples R China

Randomness is a common uncertainty encountered in practical multi-objectives decision-making. But it is always a challenge for decision-makers to process randomness in multi-objective programming problems. This paper takes the decision-making objectives as fuzzy events and aims to solve numerical multi-objective programming problems under random environment. We first analyze the effects of randomness on multi-objective decision-making results. With the expectation value and the probability of fuzzy events as quantitative index of randomness, we then establish a two-stage random multi-objective programming model based on reliability (i.e., TS-MOPM). Specifically, we give several probability calculation methods of fuzzy events with common distributions, and further present the corresponding calculation procedures for solving TS-MOPM. Finally, a case study is implemented to test the proposed model TS-MOPM. Theoretical analysis and case study indicate that our model has better interpretability and operability. The research results enrich the existing random multi-objective programming methods to some extent. (C) 2020 The Authors. Published by Atlantis Press SARL.

关键词： multi-objective programming Randomness Expectation value Fuzzy events Reliability

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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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Use of a genetic algorithm and multi-objective programming for calibration of a hydrologic model

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TRANSACTIONS OF THE ASAE 1998年第3期41卷 615-619页

作者： Balascio, CC Palmeri, DJ Gao, H Univ Delaware Dept Bioresource Engn Newark DE 19717 USA

A genetic algorithm was used to calibrate the RUNOFF component of the EPA storm-water management model, SWMM. A multi-objective function was developed which attached user-specified weights to error terms for estimates of peak flow rate, runoff volume, and time of peak. The genetic algorithm proved to be a valuable tool for isolating the neighborhood of the optimal parameter set. A conventional calibration scheme was used whereby the model was first fitted to a low intensity storm which produced runoff from impervious al eas only After parameters for the impervious cover were found, a larger storm was used to determine the variables for pervious land use. The calibrated model was used to simulate Two additional storms with good accuracy.

关键词： hydrologic models calibration genetic algorithm multi-objective programming SWMM

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An application of a multi-objective programming technique to construction accuracy control of cable-stayed bridges

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 1995年第3期87卷 731-738页

作者： Nakayama, H Kaneshige, K Takemoto, S Watada, Y UBE IND LTD DEPT BRIDGE & STEEL STRUCT UBE YAMAGUCHI 755 JAPAN

Cable-stayed bridges are gaining much popularity in Japan due to their beautiful shape. During and after construction, this kind of bridge needs to have the cable length adjusted in order to attain errors of cable tension and camber within some allowable range. This problem becomes a multi-objective optimization, and has been tried to be solved by traditional goal programming with a squared sum of objective functions as a scalarization function. Several authors, including one of the authors of this paper, reported, however, that it is not so easy to obtain a desirable solution by adjusting weights as in goal programming, On the other hand, the aspiration level approach to multi-objective programming problems is now widely recognized to be effective in many practical fields, because it is very simple and easy to implement, and does not require any mathematical consistency for the judgment of decision makers, and moreover uses the aspiration level of decision makers as a probe rather than weights for objective functions. The authors developed a user-friendly software for construction accuracy control of cable-stayed bridges using a multi objective programming technique, called the satisficing trade-off method, and applied it to some real bridges, In this paper, we report our experiences of real applications of the multi-objective programming technique to construction accuracy control of cable-stayed bridges.

关键词： multi-objective programming aspiration level approach construction accuracy control cable stayed bridges

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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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A dietary management recommendation model based on analytic hierarchy process and multi-objective programming for regular out-diners in Taiwan

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SERVICE ORIENTED COMPUTING AND APPLICATIONS 2024年第2期18卷 153-162页

作者： Li, Jung-Bin Fu Jen Catholic Univ Dept Stat & Informat Sci New Taipei Taiwan

This academic paper delves into the intricacies of dining out and dietary management, aiming to provide an effective solution to the multifaceted challenges faced by regular out-diners in Taiwan. The research centers on the development and application of an innovative hybrid model that combines the analytic hierarchy process (AHP) and multi-objective programming (MOP) to facilitate dietary planning, thereby accommodating individual preferences, expert insights, and the recommended daily intake levels for six categories of essential nutrients. The model is designed to enable a dynamic adjustment of preference coefficients when decision-makers provide their preferences, resulting in personalized dietary recommendations. However, it is noted that solutions adhering to predefined budget constraints may sometimes fall short of identifying entirely satisfactory dietary combinations. Furthermore, a significant challenge identified in this study pertains to the availability of food products at chain restaurants and stores. These products often exhibit deficiencies in essential nutrients while offering an excess of dietary energy. The research reveals that when individuals adhere to recommended dietary combinations, they can attain nutrient intake levels that closely approximate suggested values. In this study, the AHP-MOP model demonstrates enhanced stability and superior adherence to the principles of healthy dietary planning, ultimately yielding dietary combinations associated with a higher perceived value within the same budgetary constraints than the MOP-only model. With the regional limitation of model, the study underscores the potential for enhancing the model's practicality by expanding the product database, thereby contributing to the improved dietary well-being of regular out-diners.

关键词： multi-objective programming Analytic hierarchy process Dietary control Dietary reference intake

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Isolated efficiency in nonsmooth semi-infinite multi-objective programming

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OPTIMIZATION 2018年第11期67卷 1923-1947页

作者： Rahimi, Morteza Soleimani-damaneh, Majid Univ Tehran Coll Sci Sch Math Stat & Comp Sci Tehran Iran

In this paper, isolated efficient solutions of a given nonsmooth multi-objective Semi-Infinite programming problem (MOSIP) are studied. Two new Data Qualifications (DQs) are introduced and it is shown that these DQs are, to a large extent, weaker than already known Constraint Qualifications (CQs). The relationships between isolated efficiency and some relevant notions existing in the literature, including robustness, are established. Various necessary and sufficient conditions for characterizing isolated efficient solutions of a general problem are derived. It is done invoking the tangent cones, the normal cones, the generalized directional derivatives, and some gap functions. Using these characterizations, the (strongly) perturbed Karush-Kuhn-Tucker (KKT) optimality conditions for MOSIP are analyzed. Furthermore, it is shown that each isolated efficient solution is a Geoffrion properly efficient solution under appropriate assumptions. Moreover, Kuhn-Tucker (KT) and Klinger properly efficient solutions for a nonsmooth MOSIP are defined and it is proved that each isolated efficient solution is a KT properly efficient solution in general, and a Klinger properly efficient solution under a DQ. Finally, in the last section, the largest isolated efficiency constant for a given isolated efficient solution is determined.

关键词： multi-objective programming semi-infinite programming nonsmooth optimization isolated efficient solution robustness gap function

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Finite coverings by cones and an application in multi-objective programming

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POSITIVITY 2003年第1-2期7卷 61-72页

作者： Tijs, S Reijnierse, H Tilburg Univ Dept Econometr NL-5000 LE Tilburg Netherlands Tilburg Univ CentER NL-5000 LE Tilburg Netherlands

This paper considers analogues of statements concerning compactness and finite coverings, in which the roles of spheres are replaced by cones. Furthermore, one of the finite covering results provides an application in... 详细信息

关键词： cones epsilon-domination finite covering multi-objective programming

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Artificial immune system based neural networks for solving multi-objective programming problems

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EGYPTIAN INFORMATICS JOURNAL 2010年第2期11卷 59-65页

作者： El-Wahed, Waiel F. Abd Zaki, Elsayed M. El-Refaey, Adel M. Menoufia Univ Fac Comp & Informat Shibin Al Kawm Egypt Menoufia Univ Fac Engn Dept Basic Engn Sci Shibin Al Kawm Egypt

In this paper, a hybrid artificial intelligent approach based on the clonal selection principle of artificial immune system (AIS) and neural networks is proposed to solve multi-objective programming problems. Due to the sensitivity to the initial values of initial population of antibodies (Ab's), neural networks is used to initialize the boundary of the antibodies for AIS to guarantee that all the initial population of Ab's is feasible. The proposed approach uses dominance principle and feasibility to identify solutions that deserve to be cloned, and uses two types of mutation: uniform mutation is applied to the clones produced and non-uniform mutation is applied to the "not so good" antibodies. A secondary (or external) population that stores the nondominated solutions found along the search process is used. Such secondary population constitutes the elitist mechanism of our approach and it allows it to move towards the Pareto front. (C) 2010 Faculty of Computers and Information, Cairo University. Production and hosting by Elsevier B.V. All rights reserved.

关键词： Artificial immune system Neural networks Nonlinear programming multi-objective programming Clonal selection

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Study on Location-selection of Shared Bicycle Parking Sites Based on multi-objective programming 7

Study on Location-selection of Shared Bicycle Parking Sites ...

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7th International Conference on Traffic Engineering and Transportation System (ICTETS)

作者： Chen, Yuan Hu, Hang Wuhan Text Univ Sch Math & Phys Sci Wuhan 430073 Peoples R China

ISBN: (纸本)9781510674479

With the rapid development of shared bicycles in recent years, it not only facilitates urban residents, but also brings several problems to urban traffic, mainly in disorderly parking. In order to solve the disorderly parking of shared bicycles, this paper takes the Yangguang Campus of Wuhan Textile University for example and considers the trip demand of teachers and students. We choose the cosine distribution time satisfactory function as the service quality level function to quantify the quality of service, which can reflect the distance between demanding points and parking sites to users' satisfaction. Then we establish a multi- objective integer planning location-selection model based on gradual coverage method, which aims at maximizing service quality and minimizing the number of parking sites. We use LINGO to calculate the model with actual survey data. The results show that the solution of the location-selection model is close to the reality and of certain practical significance.

关键词： location selection shared bicycle gradual coverage multi-objective programming

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