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Solving multi-level multi-objective Fractional programming Problems with Fuzzy Demands via FGP Approach

International Journal of Applied and Computational Mathematics 2018年第1期4卷 1-24页

作者： Osman, M.S. Emam, O.E. El Sayed, M.A. Mathematics and Operations Research El Asher University El Asher City Egypt Department of Information Systems Faculty of Computers and Information Helwan University P.O. Box 11795 Greater Cairo Egypt Department of Basic Engineering Sciences Faculty of Engineering Benha University Benha ElQalyoubia Egypt

This paper presents a fuzzy goal programming approach for solving multi-level multi-objective fractional programming problem with fuzzy demands. It makes an extension work of Pal et al. (Fuzzy Sets Syst 139(2):395–405, 2003). Firstly, the concept of α-cut is applied to transform the fuzzy mathematical problem into a common deterministic one. Then, the membership functions for the defined fuzzy goals are developed. Also, in the proposed approach, linearization of membership goals of the objective functions is presented. Secondly, the highest degree of each of these membership goals is achieved by minimizing the sum of the negative deviational variables. Moreover, the final model is simplified by eliminating solution preferences by the decision makers at each level, thereby avoiding decision deadlock situations. Finally, an illustrative numerical examples and comparisons with the existing methods are used to demonstrate the applicability and performance of the proposed approach. © 2017, Springer (India) Private Ltd., part of Springer Nature.

关键词： Fractional programming Fuzzy goal programming Fuzzy sets multi-level programming multi-objective programming

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A multi objective programming Algorithm for Wireless Sensor Networks

A Multi Objective Programming Algorithm for Wireless Sensor ...

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International Conference on Communication Software and Networks

作者： Zhou, Guomin Zhejiang Police Coll Hangzhou Zhejiang Peoples R China

ISBN: (纸本)9780769535227

With multimedia technology rapid development and popular application in the wireless sensor networks (WSN), it become a facing problem necessarily that the wireless sensor network need to support quality of service (Qos) for all kinds of services. Accordingly, this paper builds a multi objective programming model and presents a Qos routing algorithm for WSN, which can also run efficiently with best-effort traffic. Simulations and comparisons with some typical route algorithms show that our algorithm is robust and effective.

关键词： wirelsee sensor networst multi-objective programming quality of service

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Dynamic virtual machines placement in a cloud environment by multi-objective programming approaches

Dynamic virtual machines placement in a cloud environment by...

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International Conference on Intelligent Informatics and Biomedical Sciences

作者： Han-Ying Kao Yu-Min Yang Chia-Hui Huang Dept. of Computer Science & Information Engineering National Dong Hwa University Dept. of Business Administration National Taipei University of Business

ISBN: (纸本)9781479985630

Recently, cloud services and cloud computing have revolutionized both academic research and industrial practices. A corresponding focus on how to improve the performance of cloud computing is growing apace. It is a significant approach to allocate virtual machines (VMs) on a set of physical machines. Computing resources can be utilized effectively with the optimal distribution of the virtual machines among the physical machines. This study aims to establish the dynamic placement model of VMs by multi-objective programming for (1) minimizing energy consumption, (2) maximizing effectiveness of physical machine, and (3) minimizing the task waiting time. Experiments are implemented to verify the effectiveness of the proposed methods.

关键词： Cloud computing multi-objective programming Dynamic Genetic algorithm Virtual machine placement

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A class of multi-objective mathematical programming problems in a rough environment

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SCIENTIA IRANICA 2016年第1期23卷 301-315页

作者： Hamzehee, A. Yaghoobi, M. A. Mashinchi, M. Shahid Bahonar Univ Kerman Fac Math & Comp Dept Math Kerman Iran Shahid Bahonar Univ Kerman Fac Math & Comp Dept Stat Kerman Iran Islamic Azad Univ Kerman Branch Fac Basic Sci Dept Math Kerman Iran

This paper presents a set of multi-objective programming problems in a rough environment. These problems are classified into five classes according to the location of the roughness in the objective functions or the feasible set. We study the class in which all of the objective functions are crisp and the feasible region is a rough set and, in particular, discuss the properties of the complete and efficient (Pareto optimal) solutions of rough multi-objective programming problems. In order to obtain these solutions, we need certain theorems, which we derive. Finally, we illustrate our results by examples. (C) 2016 Sharif University of Technology. All rights reserved.

关键词： Rough set multi-objective programming Rough programming Complete-optimal solutions Efficient solutions

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Solving multi-objective multilevel programming problems using two-phase Intuitionistic Fuzzy Goal programming method

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JOURNAL OF COMPUTATIONAL SCIENCE 2022年第0期63卷

作者： Mollalign, Demmelash Mushi, Allen Guta, Berhanu Addis Ababa Univ Dept Appl Math Addis Ababa Ethiopia Univ Dares Salaam Dept Math Dar Es Salaam Tanzania

This paper presents a two-phase intuitionistic fuzzy goal programming (two-phase IFGP) algorithm to solve multi-objective multilevel programming (MO-MLP) problems. The coefficient of each objective and constraint function is assumed to be triangular intuitionistic fuzzy parameters and the crisp MO-MLP problems are obtained using the accuracy function method. To avoid decision lock, the top levels set tolerance limits for decision variables to control the lower levels. The problem is modeled in the intuitionistic fuzzy environment using membership and non-membership functions for each objective function at all levels and decision variables controlled by the top levels. Then, we proposed an IFGP algorithm to achieve the highest degree of each membership and non-membership goal by minimizing unwanted deviational variables and generating compensatory solutions for all decision-makers at all levels. Moreover, in the proposed approach, two-phase IFGP is modeled to yield a compromise solution that satisfies both the MN-Pareto optimal solution and the Pareto optimal solution at each level. Also, verification of the proposed method is discussed with numerical examples.

关键词： multi-objective programming multilevel programming Intuitionistic fuzzy goal programming Intuitionistic fuzzy decision set Two-phase model

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Collaborative energy management in a micro-grid by multi-objective mathematical programming

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ENERGY AND BUILDINGS 2019年 203卷 109432-000页

作者： Pisacane, Ornella Severini, Marco Fagiani, Marco Squartini, Stefano Univ Politecn Marche Dipartimento Ingn Informaz Ancona Italy

In micro-grids, distributed energy generation based on renewable sources allows reducing the fossil fuel emissions. In order to manage the limited availability of renewable sources and to meet users' requirements, a proper scheduling of both tasks and storage activities is needed. Moreover, the difficulty of storing energy on a large scale represents an opportunity for the micro-grid actors to collaborate for better balancing energy supply and demand. Collaboration may be achieved through the application of suitable energy management policies tackling the specific consumers' needs. We address the Energy Management Problem in a micro-grid with collaboration among users. Specifically, a building is considered where each apartment can use both Shared and Local energy resources, the former managed by a Building Manager (BM). The problem is formulated through Bi-objective Mixed Integer Linear programming, maximizing both the BM and the apartments' profits and solved through the Augmented epsilon-Constraint approach. Numerical results, obtained on a set of realistic scenarios, are compared to those of the Weighted Sum method and evaluated according to proper performance metrics. The approach flexibility, in terms of selected management policies, is also discussed. Finally, the superiority of the collaborative paradigm versus the non-collaborative one is experimentally proven. (C) 2019 Elsevier B.V. All rights reserved.

关键词： Energy management Smart grid multi-objective programming Transactive energy

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Interactive Approach for multi-Level multi-objective Fractional programming Problems with Fuzzy Parameters

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Beni-Suef University Journal of Basic and Applied Sciences 2018年第1期7卷 139-149页

作者： M.S. Osman O.E. Emam M.A. Elsayed Professor of Mathematics and Operations Research Vicepresedent of ElAsher University Egypt Department of Information Systems Faculty of Computers and Information Helwan University P.O.Box 11795 Egypt Department of Basic Engineering Sciences Faculty of Engineering Benha University ElQalyoubia Egypt

In this paper, an interactive approach for solving multi-level multi-objective fractional programming (ML-MOFP) problems with fuzzy parameters is presented. The proposed interactive approach makes an extended work of Shi and Xia (1997). In the first phase, the numerical crisp model of the ML-MOFP problem has been developed at a confidence level without changing the fuzzy gist of the problem. Then, the linear model for the ML-MOFP problem is formulated. In the second phase, the interactive approach simplifies the linear multi-level multi-objective model by converting it into separate multi-objective programming problems. Also, each separate multi-objective programming problem of the linear model is solved by the ∊ -constraint method and the concept of satisfactoriness. Finally, illustrative examples and comparisons with the previous approaches are utilized to evince the feasibility of the proposed approach.

关键词： multi-level programming multi-objective programming Fractional programming Fuzzy parameters

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The influence of multi objective programming on Aerobics Teaching

The influence of multi objective programming on Aerobics Tea...

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2017 International Conference on Advanced Education,Psychology and Sports Science(AEPSS 2017)

作者： Yali Xu Kaihua Xu School of Physical Education Jiangxi University Of Traditional Chinese Medicine Police Training Management Department Jiangxi People's Police College

This paper explore application method of multi-objective programming and discussed its effect in aerobics teaching, through the analysis of the summary of multi-objective programming, studies the principles that need ... 详细信息

关键词： multi-objective programming Aerobics Teaching Impact

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A multi-objective Fuzzy programming Model for Coordinate Operations of a Supply Chain with Uncertain Demands

A Multi-objective Fuzzy Programming Model for Coordinate Ope...

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2012 IEEE 19th International Conference on Industrial Engineering and Engineering Management(IE&EM 2012)

作者： Jia-wang Xu Yi Zhang Li-qiang Zhao College of Economics and Management Shenyang Aerospace University Shenyang Institute of Automation Chinese Academy of Sciences

The coordinate operating process of a supply chain is considered. The supply chain is consisting of a manufacturer, a supplier and several customers, the semi- finished products of the supplier are raw materials of the manufacturer, demands of customers are uncertain, and the uncertainties of demands are described as fuzzy sets. A multi-objective fuzzy programming model for coordinate operations of the supply chain is constructed and a numerical example is proposed. The results of the numerical example shows that decision makers can obtain an optimal operations strategy by using the model proposed in this paper according to the level of uncertainties of demands, and the operation strategy possesses robustness in same ways.

关键词： Coordinate Operations Fuzzy programming multi-objective programming supply chain uncertainty

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Development of the novelty order allocation model based on supplier's willingness – Combination of a Bayesian network and a stochastic multi-objective linear programming 22

Development of the novelty order allocation model based on s...

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Proceedings of the 2022 4th International Conference on E-Business and E-Commerce Engineering

作者： Qiu-Rui He Ping-Kuo Chen Shantou University China Great Bay University China

ISBN: (纸本)9798400700071

The aim of this study is to develop a novelty order allocation through combination of a Bayesian network and a stochastic multi-objective linear programming model to help manufacturers with order allocation decisions under the uncertainty of supplier's willingness to cooperate. In this paper, we deal with the uncertainty of the willingness to cooperate through several phases. The first phase presents the determination of the factors influencing willingness to cooperate. Then Bayesian network theory is used to deal with the uncertainty of willingness to cooperate and transformation into scenarios. Finally, a stochastic multi-objective linear programming model is developed, and the weighted-sum method is utilized to solve the model. The results demonstrate the feasibility of the approaches. The order allocation model based on supplier's willingness to cooperate proposed in this paper expands the research field and reduces the carbon emission management risk of manufacturers due to the change of supplier's willingness to cooperate.

关键词： Bayesian network Order allocation multi-objective programming willingness to cooperate

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