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Research on a Wear-Law Model based on fuzzy programming

Research on a Wear-Law Model based on Fuzzy Programming

2009 IEEE 16th International Conference on Industrial Engineering and Engineering Management(IEEE第16届工业工程与工程管理国际学术会议)

作者： Y.F.Tang J.N.Wang X.K.Liu W.Shang Academy of Military Transportation TianjinChina Center for Forecasting Science Chinese Academy of Sciences.BeijingChina

ISBN: (纸本)9781424436712

The paper proposes a fuzzy programming based wear-law model. Theoretical foundations,technical instructions are elaborated. And an application of cylinder wear modeling is presented to test the feasibility and reliability of the proposed model. It is proved that the proposed wear-law model is sufficient to describe a product's wear law as a fuzzy variant. This research offers an innovative instrument for wear law analysis.

关键词： fuzzy programming Wear-Law Modeling Cylinder Wear-Law Models

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A Constraint-Softened Interval-fuzzy Linear programming Approach for Environmental Management Under Uncertainty

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ENVIRONMENTAL ENGINEERING SCIENCE 2009年第8期26卷 1335-1348页

作者： Li, Yongping Huang, Gordon Yang, Zhifeng Nie, Songlin Peking Univ Coll Urban & Environm Sci Beijing 100871 Peoples R China Univ Regina Fac Engn Environm Syst Engn Program Regina SK S4S 0A2 Canada Beijing Normal Univ Sch Environm State Key Lab Water Environm Simulat Beijing 100875 Peoples R China Beijing Univ Sci & Technol Coll Mech Engn & Appl Elect Technol Beijing 100083 Peoples R China

In this study, a constraint-softened interval-fuzzy linear programming (CS-IFLP) method is developed for violation analysis of environmental management systems under uncertainty. CS-IFLP can deal with uncertainties presented in terms of fuzzy sets and intervals. Moreover, a number of fuzzy relaxation levels for system constraints are allowed, such that the relevant decision space can be expanded. This can help generate a range of decision alternatives under various system conditions, and facilitate in-depth analyses of tradeoffs among economic objective, satisfaction degree, and constraint-violation risk. The developed method is applied to a case study of long-term municipal solid waste management planning. Results indicate that reasonable solutions for both binary and continuous variables have been generated. A higher relaxation level could result in a lower system cost and a higher satisfaction degree, but with a higher constraint-violation risk. Results of the sensitivity analyses demonstrate that violated system constraints have various effects on the system cost and satisfaction degree.

关键词： constraint-softened decision making environment fuzzy programming interval management optimization violation analysis uncertainty

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An interactive weighted fuzzy goal programming technique to solve multi-objective reliability optimization problem

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Journal of Industrial Engineering International 2019年第1-Sup期15卷 95-104页

作者： Kundu, Tanmay Islam, Sahidul Department of Mathematics University of Kalyani Kalyani 741235 West Bengal India

This paper presents an application of interactive fuzzy goal programming to the nonlinear multi-objective reliability optimization problem considering system reliability and cost of the system as objective functions. As the decision maker always have an intention to produce highly reliable system with minimum cost, therefore, we introduce the interactive method to design a high productivity system here. This method plays an important role to maximize the worst lower bound to obtain the preferred compromise solution which is close to the best upper bound of each objective functions. Until the preferred compromise solution is reached, new lower bounds corresponding to each objective functions will be determined based on the present solution to develop the updated membership functions as well as aspiration levels to resolve the proposed problem. Considering judgmental vagueness of decision maker, here we consider the resources as trapezoidal fuzzy numbers and apply total integral value of fuzzy number to transform into crisp one. To illustrate the methodology and performance of this approach, numerical examples are presented and evaluated by comparing with the other method at the end of this paper. © 2019, The Author(s).

关键词： fuzzy programming Goal programming Interactive methods Multi-objective programming Reliability

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A fuzzy Goal programming Technique for Quadratic Multiobjective Multilevel programming

A Fuzzy Goal Programming Technique for Quadratic Multiobject...

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IEEE International Conference on fuzzy Systems (FUZZ)

作者： Biswas, Animesh Bose, Koushik Univ Kalyani Dept Math Kalyani 741235 W Bengal India

ISBN: (纸本)9781479900206

The purpose of this paper is to develop a fuzzy goal programming methodology for solving quadratic multiobjective multilevel programming problems in a hierarchical decision making environment. In the proposed procedure, the tolerance membership functions in fuzzy set theory are defined first for measuring the degree of satisfactions of the objectives of each decision maker at each level. Then a nonlinear fuzzy goal programming model is formulated to achieve highest degree of each of the defined membership goals at each level to the extent possible on the basis of priorities of importance of optimizing the objectives. Afterwards the nonlinear fuzzy goals are converted into linear forms by applying a linear approximation technique. The model is then solved for measuring the degree of satisfaction of the objectives of decision makers at each level by arriving at a compromise decision regarding the optimality of the sets of decision variables controlled individually by each of them. To illustrate the proposed methodology a numerical example is solved and compared the solution with existing approaches.

关键词： Multilevel programming Quadratic programming Goal programming fuzzy programming fuzzy Goal programming Linear Approximation Technique

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A fuzzy goal programming approach for solving fuzzy multi-objective stochastic linear programming problem

A fuzzy goal programming approach for solving fuzzy multi-ob...

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International Conference on Industrial Engineering and Systems Management (IESM)

作者： Masoud, Mahmoud Khalifa, H. A. Liu, Shi Qiang Elhenawy, Mohammed Wu, Peng Queensland Univ Technol Fac Sci & Engn CAARS Q Brisbane Qld 4001 Australia Queensland Univ Technol Fac Sci & Engn Sch Math Sci Brisbane Qld 4001 Australia Cairo Univ Inst Stat Studies & Res Operat Res Dept Giza Egypt Qassim Univ Coll Arts & Sci Dept Math Al Badaya Saudi Arabia Fuzhou Univ Sch Econ & Management Fuzhou 350116 Peoples R China Queensland Univ Technol Fac Hlth Ctr Accid Res & Rd Safety Brisbane Qld Australia

ISBN: (纸本)9781728115665

This paper deals with the multi-objective chance constrained programming, where the right hand side of the constraints are normally distributed and the objective functions with fuzzy numbers coefficients. A fuzzy goal programming approach is developed for the corresponding deterministic problem by defining membership values and aspiration levels. The advantage of the proposed approach is the decision-maker's role only in estimating the efficient solution to avoid or atleast limit the influences of his/her knowledge incomplete about the studied problem. A numerical example is given in the utility of the paper to illustrate the applied and the efficiency of the approach.

关键词： Chance constrained programming Normal distribution Joint probability distribution fuzzy numbers fuzzy programming Goal programming Optimal compromise solution

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Using Genetic Algorithm for Solving Linear Multilevel programming Problems via fuzzy Goal programming

Using Genetic Algorithm for Solving Linear Multilevel Progra...

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1st International Conference on Logic, Information, Control and Computation

作者： Pal, Bijay Baran Chakraborti, Debjani Biswas, Papun Univ Kalyani Dept Math Kalyani 741235 W Bengal India Narula Inst Technol Dept Math Kolkata 700109 W Bengal India JIS Coll Engn Dept Elect Engn Kalyani 741235 W Bengal India

ISBN: (纸本)9783642192623

This article presents a fuzzy goal programming (FGP) procedure for modeling and solving multilevel programming (MLP) problems by using genetic algorithm (GA) in a large hierarchical decision making system. In the proposed approach, an GA scheme is introduced first for searching of solutions at different stages and thereby solving the problem and making decision in the order of hierarchy of execution of decision powers of the decision makers (DMs) located at different hierarchical levels. In the proposed GA scheme, Roulette-wheel selection scheme, single point crossover and random mutation are adopted to search a satisfactory solution in the hierarchical decision system. To illustrate the potential use of the approach, a numerical example is solved.

关键词： Multilevel programming fuzzy programming fuzzy Goal programming Goal programming Genetic Algorithm Membership Function

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A fuzzy Goal programming Approach for fuzzy Multiobjective Stochastic programming through Expectation Model

A Fuzzy Goal Programming Approach for Fuzzy Multiobjective S...

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2nd International Conference of Mathematical Modelling and Scientific Computation (ICMMSC 2012)

作者： Biswas, Animesh Modak, Nilkanta Univ Kalyani Dept Math Kalyani 741235 W Bengal India

ISBN: (纸本)9783642289255

In this paper a fuzzy goal programming method for modeling and solving multiobjective stochastic decision making problem involving fuzzy random variables associated with the parameters of the objectives as well as system constraints is developed. In the proposed approach. an expectation model is generated on the basis of the mean of the fuzzy random variables involved with the objectives of the problem. Then the problem is converted into an equivalent fuzzy programming model by considering the fuzzily defined chance constraints. Afterwards, the model is decomposed on the basis of the tolerance ranges of the fuzzy numbers associated with the fuzzy parameters of the problem. Now to construct the membership goals of the decomposed objectives under the extended feasible region defined by the decomposed system constraints, the individual optimal values of each objective is calculated in isolation. Then the membership functions are constructed to measure the degree of satisfaction of each decomposed objectives in the decision making environment. The membership functions are then converted into membership goals by assigning unity as the aspiration level of the membership goals. Then a fuzzy goal programming model is developed by minimizing the under deviational variables and thereby obtaining the optimal solution in the decision making environment.

关键词： Stochastic programming Chance constrained programming Expectation model fuzzy random variables fuzzy numbers fuzzy programming fuzzy goal programming

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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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fuzzy Geometric programming Approach in Multivariate Stratified Sample Surveys Under Two Stage Randomized Response Model

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Journal of Mathematical Modelling and Algorithms in Operations Research 2015年第4期14卷 407-424页

作者： Ullah, Shafi Ali, Irfan Bari, Abdul Department of Statistics & Operations Research Aligarh Muslim University Aligarh India

This paper provide a profound study on optimum allocation of two stage multivariate stratified Warner’s randomized response (RR) model with linear and non linear cost function. The multi-objective problem is formulated as a Geometric programming Problem (GPP). The fuzzy programming approach is adopted to solve the formulated problem. A numerical example is given to illustrate the computational details of the suggested method. © 2015, Springer Science+Business Media Dordrecht.

关键词： fuzzy programming Geometric programming Multiple sensitive questions Multivariate stratified sampling Optimum allocation Two-stage randomized response technique

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A fuzzy Goal programming Approach for Solving Multiobjective fuzzy Stochastic programming Problems

A Fuzzy Goal Programming Approach for Solving Multiobjective...

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International Conference on Industrial and Information Systems

作者： Pal, Bijay Baran Sen, Shyamal Kumar, Mousumi Univ Kalyani Dept Math Kalyani 741235 W Bengal India BKC Coll Dept Math Kolkata 700108 W Bengal India Alipurduar Coll Dept Math Alipurduar 736122 W Bengal India

ISBN: (纸本)9781424448364

This article presents a fuzzy goal programming (FGP) procedure for solving a stochastic multiobjective decision making (MODM) problem having the finite probabilistic aspiration levels for achievement of the chance constrained goals. In the proposed approach, the different chance parameters involved with the stochastically defined goal constraints are considered continuously distributed independent random variables. In the model formulation, first the membership functions of the fuzzy probablistic goals are constructed by defining the tolerance limits for achievement of the goals in the decision situation. Then, the defined membership functions are converted into their deterministic equivalent according to the prescribed distribution function of the random parameters. In the solution process, achievement of the membership goals defined for the deterministic membership functions to the highest value (unity) to the extent possible on the basis of the weights of importance of achieving the goals is considered. Two numerical examples are solved to illustrate the approach.

关键词： Chance Constrained programming fuzzy programming fuzzy Goal programming Goal programming Stochastic programming

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