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10th International Conference on Computational Intelligence and Security CIS 2014

作者： Li, Xiangxou Zhang, Qingxiang Yanan Univ Coll Math & Comp Sci Yanan 716000 Shaanxi Peoples R China

ISBN: (纸本)9781479974344

In this paper, new classes of generalized invex functions called (h, phi) - rho invex functions, (h, phi) - rho quasi invex functions and (h, phi) - rho pseudo invex functions are introduced, multi-objective semi-infinite programming involving new generalized functions is researched, the sufficient optimality conditions are obtained under weaker convexity.

关键词： multi-objective programming (h, phi) - rho invex functions efficient solution optimality

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A cutting plane approach for multi-objective integer indefinite quadratic programming problem

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OPSEARCH 2015年第2期52卷 367-381页

作者： Arora, Ritu Arora, S. Univ Delhi Keshav Mahavidyalaya Dept Math Delhi India Univ Delhi Hansraj Coll Dept Math Delhi India

In this paper, an algorithm is developed to solve a multi-objective Integer Indefinite Quadratic programming Problem(IQMPP). The cutting plane technique finds all the non-dominated p-tuples of the (IQMPP) problem. Since the objective functions of (IQMPP) problem are quasi-monotone, the cutting plane truncates a portion of the feasible region and enables us to find all the non-dominated p-tuples at extreme points of the remaining feasible region. The algorithm is explained with the help of an example.

关键词： Indefinite quadratic programming problem multi-objective programming Integer programming Non-dominated solution Bounded variables

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multi-objective bilevel fuzzy probabilistic programming problem

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OPSEARCH 2017年第3期54卷 475-504页

作者： Ranarahu, N. Dash, J. K. Acharya, S. Siksha O Anusandhan Univ Inst Tech Educ & Res Dept Math Khandagiri Sq Bhubaneswar 751030 Odisha India KIIT Univ Sch Appl Sci Dept Math Bhubaneswar Orissa India

This paper presents an efficient method for solving a multi objective bilevel programming problem with multiple number of objective functions in both first level as well as in second level. The uncertain parameters are present in second level in form of fuzzy random variables. In this case the fuzzy random variables are assumed to be fuzzy normal random variables. First the fuzziness is removed by using alpha cut technique and randomness is removed by chance constrained method. Then multi objective bilevel programming problem is transformed into a single objective non-linear mathematical model by using fuzzy programming technique. This non-linear mathematical model is solved by existing methodology or software. A numerical example is presented to illustrate the efficiency and feasibility of the proposed method.

关键词： Stochastic programming multi-objective programming Fuzzy programming Fuzzy normal random variables Bilevel programming Optimization techniques

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multi-objective IT Professionals' Utilization Problems Using Fuzzy Goal programming 5th

Multi-objective IT Professionals' Utilization Problems Using...

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5th International Conference on Frontiers in Intelligent Computing - Theory and Applications (FICTA)

作者： Jana, R. K. Sanyal, Manas Kumar Chakrabarti, Saikat Indian Inst Social Welf & Business Management Kolkata 700073 WB India Univ Kalyani Kalyani 741235 WB India Inst Engn & Management Ashram Campus Kolkata India

ISBN: (纸本)9789811031564;9789811031557

This paper presents a fuzzy goal programming approach to solve IT professionals' utilization problems for software firms. These problems involve multiple objectives and binary decision variables. The fuzzy goal programming approach helps to quantify uncertainness of the objectives of the problem. With the help of membership functions, the problem is converted to its equivalent deterministic form. A case study demonstrates the effectiveness of the approach.

关键词： multi-objective programming Fuzzy goal programming Human resource planning Information technology

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A Recourse Stochastic Goal programming Approach for the multi-objective Stochastic Vehicle Routing Problem

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JOURNAL OF multi-CRITERIA DECISION ANALYSIS 2016年第1-2期23卷 3-14页

作者： Masri, Hatem Ben Abdelaziz, Fouad Alaya, Houda Univ Bahrain Coll Business Adm POB 32038 Sakhir Bahrain NEOMA Business Sch Mont St Aignan France Univ Tunis Inst Super Gest Le Bardo Tunisia

This paper addresses a multi-objective stochastic vehicle routing problem where several conflicting objectives such as the travel time, the number of vehicles in use and the probability of an accident are simultaneously minimized. We suppose that demands and travel durations are of a stochastic nature. In order to build a certainty equivalent program to the multi-objective stochastic vehicle routing problem, we propose a solution strategy based on a recourse approach, a chance-constrained approach and a goal-programming approach. The resulting certainty equivalent program is solved to optimality using CPLEX. Copyright (C) 2016 John Wiley & Sons, Ltd.

关键词： vehicle routing problem multi-objective programming goal programming stochastic programming

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multi-objective Compromise Allocation in multivariate Stratified Sampling Using Extended Lexicographic Goal programming with Gamma Cost Function

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Journal of Mathematical Modelling and Algorithms in Operations Research 2015年第3期14卷 255-265页

作者： Muhammad, Yousaf Shad Shabbir, Javid Husain, Ijaz Abd-el.Moemen, Mitwali Department of Statistics Quaid-i-Azam University Islamabad Pakistan College of Law and Political Science King Saud University Riyadh Saudi Arabia

In the present paper, a new Gamma cost function is proposed for an optimum allocation in multivariate stratified random sampling with linear regression estimator. Extended lexicographic goal programming is used for solution of multi-objective non-linear integer allocation problem. A real data set is used to illustrate the application. © 2014, Springer Science+Business Media Dordrecht.

关键词： Compromise allocation Lexicographic goal programming multi-objective programming multivariate stratified sampling Nonlinear cost function

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Efficient Fuzzy Goal programming Model for multi-objective Production Distribution Problem

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International Journal of Applied and Computational Mathematics 2018年第2期4卷 1-19页

作者： Gupta, Srikant Ali, Irfan Ahmed, Aquil Department of Statistics and Operations Research Aligarh Muslim University Aligarh UP India

This paper comprises of modelling and optimization of a production–distribution problem with the multi-product. The proposed model combined three well-known approaches, fuzzy programming, goal programming and interactive programming to develop an efficient fuzzy goal programming (EFGP) model for multi-objective production distribution problem (MOPDP). In this approach decision maker (DM) decide the goals and constructed membership functions for each objective, and they changed according to the iterative decision taken by the DM. The proposed EFGP model for MOPDP attempts to simultaneously minimize total transportation costs and total delivery time concerning inventory levels, available initial stock at each source, as well as market demand and available warehouse space at each destination, and the constraint on the total budget. The main aid of the proposed model is that its offerings an organized outline that enables fuzzy goal decision-making for solving the MOPDP under an uncertain environment. © 2018, Springer (India) Private Ltd., part of Springer Nature.

关键词： Fuzzy goal programming Interactive programming multi-objective programming Production–distribution problem

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A Novel Approach to Solve multi-objective Fuzzy Stochastic Bilevel programming Using Genetic Algorithm

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Operations Research Forum 2024年第1期5卷 11页

作者： Dutta, S. Acharya, S. Department of Advanced Computing St. Joseph’s University Bengaluru India Department of Mathematics School of Applied Sciences KIIT University Bhubaneswar India

A bilevel programming is a two-level optimization problem, namely, the upper level (leaders) and the lower level (followers). The two level’s decision variables are entwined with each other which increases the complexity to obtain the global solution for both the optimization problems. Each level aims to optimize their own objective function under the given constraints at both the levels. To reduce the complexity partial cooperation between the two levels has been exploited in obtaining the Pareto solution. A novel solution procedure is proposed for a multi-objective fuzzy stochastic bilevel programming (MOFSBLP) problem is studied and solved using genetic algorithm. In this paper, previous information of the lower level is used as a fuzzy stochastic constraints in the upper level along with its constraints. Then with the solution of the combine constraints, the lower level solution is evaluated. The proposed solution procedure is illustrated by a numerical example taken from Zheng et al., and results are compared. A simpler version is solved using GAMs software to analyze the result of the numerical example. The proposed method highlights the importance of partial cooperation in solving bilevel programming problem. The advantage of the proposed solution method is that it creates common constraint space which helps in convergence of the algorithm. © 2024, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

关键词： Bilevel programming problem Fuzzy stochastic programming Genetic algorithm multi-objective programming

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A bi-level multi-objective linear fractional programming for water consumption structure optimization based on water shortage risk

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JOURNAL OF CLEANER PRODUCTION 2019年 237卷 117829-000页

作者： Wang, Youzhi Liu, Liu Guo, Shanshan Yue, Qiong Guo, Ping China Agr Univ Ctr Agr Water Res China Beijing 100083 Peoples R China

In this study, a framework of a bi-level multi-objective linear fractional programming (BMLFP) approach is developed for the optimization of water consumption structure based on water shortage risk. It incorporates linear fractional programming (LFP), multi-objective programming (MOP) into bi-level programming (BP). The model considers the water shortage risk measured by interior-outer-set risk assessment method, and integrates it into inexact water resources optimization model. The complicated model not only can enhance the conventional programming method through the interactive influence and mutual restriction between the upper- and lower-level decision processes, and multiple objectives, but also improve the robustness of conventional programming methods by integrating the water shortage risk. Besides, the model could achieve the tradeoff between equality and economic benefit of system and figure out the interaction amid water shortage risk, water allocation and objectives. It is applied to a case study to conduct water resources management among different water users including agricultural, industrial, domestic, and ecological sectors in the middle reaches of Heihe River Basin, northwest China. The water allocation schemes with ten water-shortage risk scenarios is formed to compare the influence of water shortage degree on water allocation and figure out the optimal water allocation schemes. Besides, the performance of the developed model is enhanced by comparing with the two-level linear fractional water management (TLFWM) model and actual condition. The results indicate that the water shortage belongs to general risk area, and the water-shortage risk has obvious effect on agricultural water allocations while has insensitive influence on that of the industrial, domestic and ecological sectors. Compared with the TLFWM model and actual condition, the developed BMLFP model could improve the equality and benefit of system and lessen the water allocation. The decisi

关键词： Water shortage risk Bi-level programming Linear fractional programming multi-objective programming Equality Efficiency

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Fuzzy goal programming technique for multi-objective indefinite quadratic bilevel programming problem

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ARCHIVES OF CONTROL SCIENCES 2020年第4期30卷 683-699页

作者： Arora, R. Gupta, K. Univ Delhi Dept Math Keshav Mahavidyalaya Delhi India Univ Delhi Kirori Mal Coll Dept Math Delhi India

Bilevel programming problem is a non-convex two stage decision making process in which the constraint region of upper level is determined by the lower level problem. In this paper, a multi-objective indefinite quadratic bilevel programming problem (MOIQBP) is presented. The defined problem (MOIQBP) has multi-objective functions at both the levels. The followers are independent at the lower level. A fuzzy goal programming methodology is employed which minimizes the sum of the negative deviational variables of both the levels to obtain highest membership value of each of the fuzzy goal. The membership function for the objective functions at each level is defined. As these membership functions are quadratic they are linearized by Taylor series approximation. The membership function for the decision variables at both levels is also determined. The individual optimal solution of objective functions at each level is used for formulating an integrated pay-off matrix. The aspiration levels for the decision makers are ascertained from this matrix. An algorithm is developed to obtain a compromise optimal solution for (MOIQBP). A numerical example is exhibited to evince the algorithm. The computing software LINGO 17.0 has been used for solving this problem.

关键词： bilevel programming indefinite quadratic programming multi-objective programming pay-off matrix Taylor series approximation LINGO 17.0

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