32,098 research outputs found
Metode Mehar Untuk Solusi Optimal Fuzzy Dan Analisa Sensitivitas Program Linier Dengan Variabel Fuzzy Bilangan Triangular
. Fuzzy linear programming problems containing closely with uncertainty about the parameters. Changes in the value of the parameters without changing the optimal solution or change the optimal solution is called sensitivity analysis. Sensitivity analysis is a basic for studying the effect of the changes that occur to the optimal solution. Linear programming with fuzzy variable is a form of fuzzy linear program is not fully because there are objective function coefficients and coefficients of constraints that are crisp numbers. Resolving the problem of linear programming with fuzzy variables by using mehar method will get solutions and optimal fuzzy value and solutions and optimal crisp value. To solve the problem of linear program with fuzzy variable is using mehar, must be converted beforehand in the form of crisp linear programming. This thesis explores mehar method to solve linear programming problems with fuzzy variables with triangular number and a sensitivity analysis on the optimum solution FVLP so that when there is a change of data of the problem, new solution will remain optimal
(R1976) A Novel Approach to Solve Fuzzy Rough Matrix Game with Two Players
This paper proposes a new method for solving a two-person zero-sum fuzzy matrix game with goals, payoffs, and decision variables represented as triangular fuzzy rough numbers. We created a pair of fully fuzzy rough linear programming problems for players. Triangular fuzzy rough numbers can be used to formulate two fuzzy linear programming problems for the first player in the form of upper approximation intervals and lower approximation intervals. Two problems for the second player can be created in the same way. These problems have been split into five sub-crisp problems for the player first and five sub-crisp problems for the player second. The solution to the game can be obtained by solving these ten fuzzy linear programming problems. To demonstrate the method, a numerical example is provided. Using Wolfram Cloud, optimal strategies and game values are calculated for various parameters. Sensitivity analysis is carried out by altering the values of parameters
Mehar Methods for Fuzzy Optimal Solution and Sensitivity Analysis of Fuzzy Linear Programming with Symmetric Trapezoidal Fuzzy Numbers
The drawbacks of the existing methods to obtain the fuzzy optimal solution of such linear programming problems, in which coefficients of the constraints are represented by real numbers and all the other parameters as well as variables are represented by symmetric trapezoidal fuzzy numbers, are pointed out, and to resolve these drawbacks, a new method (named as Mehar method) is proposed for the same linear programming problems. Also, with the help of proposed Mehar method, a new method, much easy as compared to the existing methods, is proposed to deal with the sensitivity analysis of the same type of linear programming problems
Fixed-Charge Solid Transportation Problem with Budget Constraints Based on Carbon Emission in Neutrosophic Environment
This paper is to integrate among solid transportation
problem, budget constraints and carbon emission with
probable maximum profit. The limits of air pollution and
climate variation are solely dependent by exerting CO2 gas
and rest greenhouse gases due to myriad transportation system.
Henceforth, it is our apt mission to minimize carbon
emission for pollution free environment. Again transportation
system with single objective is hardly applicable to the
situation with more than one criterion. Therefore multi- objective
decision making is incorporated for designing reallife
transportation problem. Due to time pressure, data limitation,
lack of information or measurement errors in practical
problems, there exist some hesitations or suspicions.
Based on the fact, decision maker considers indeterminacy
in the designed problems. To overcome the restriction on
occurrence and non-occurrence of fuzzy and intuitionistic
fuzzy, neutrosophic set is very important and suitable to accommodate
such general structure of problems. Therefore
neutrosophic environment with neutrosophic linear programming,
fuzzy programming and global criterion method are
profiled to search the compromise solution of the multi- objective
transportation problem (MOTP). Thereafter, the performance
of the considered model is useful by evaluating
a numerical example; and then the derived results are compared.
Finally sensitivity analysis and conclusions with upcoming
works of this research are stated hereafter.PID2020-112754GB-I0
B-TIC-640-UGR2
Fuzzy linear programs with optimal tolerance levels
It is usually supposed that tolerance levels are determined by the decision maker a priori
in a fuzzy linear program (FLP). In this paper we shall suppose that the decision maker
does not care about the particular values of tolerance levels, but he wishes to minimize
their weighted sum. This is a new statement of FLP, because here the tolerance levels are
also treated as variables
Weighted Constraints in Fuzzy Optimization
Many practical optimization problems are characterized by someflexibility in the problem constraints, where this flexibility canbe exploited for additional trade-off between improving theobjective function and satisfying the constraints. Especially indecision making, this type of flexibility could lead to workablesolutions, where the goals and the constraints specified bydifferent parties involved in the decision making are traded offagainst one another and satisfied to various degrees. Fuzzy setshave proven to be a suitable representation for modeling this typeof soft constraints. Conventionally, the fuzzy optimizationproblem in such a setting is defined as the simultaneoussatisfaction of the constraints and the goals. No additionaldistinction is assumed to exist amongst the constraints and thegoals. This report proposes an extension of this model forsatisfying the problem constraints and the goals, where preferencefor different constraints and goals can be specified by thedecision-maker. The difference in the preference for theconstraints is represented by a set of associated weight factors,which influence the nature of trade-off between improving theoptimization objectives and satisfying various constraints.Simultaneous weighted satisfaction of various criteria is modeledby using the recently proposed weighted extensions of(Archimedean) fuzzy t-norms. The weighted satisfaction of theproblem constraints and goals are demonstrated by using a simplefuzzy linear programming problem. The framework, however, is moregeneral, and it can also be applied to fuzzy mathematicalprogramming problems and multi-objective fuzzy optimization.wiskundige programmering;fuzzy sets;optimalisatie
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Linear, integer separable and fuzzy programming problems: a united approach towards automatic reformulation
For mathematical programming (MP) to have greater impact as a
decision tool, MP software systems must offer suitable support in
terms of model communication and modelling techniques. In this
paper modelling techniques that allow logical restrictions to be
modelled in integer programming terms are described and their
implications discussed. In addition it is demonstrated that many
classes of non-linearities which are not variable separable may be
after suitable algebraic manipulation put in a variable separable
form. The methods of reformulating the fuzzy linear programming
problem as a Max-Min problem is also introduced. It is shown that
analysis of bounds plays a key role in the following four important
contexts: model reduction, reformulation of logical restrictions
as 0-1 mixed integer programs, reformulation of nonlinear programs
as variable separable programs and reformulation of fuzzy linear
programs. It is observed that as well as incorporating an
interface between the modeller and the optimiser there is a need to
make available to the modeller software facilities which support the
model reformulation techniques described here
Project scheduling under undertainty – survey and research potentials.
The vast majority of the research efforts in project scheduling assume complete information about the scheduling problem to be solved and a static deterministic environment within which the pre-computed baseline schedule will be executed. However, in the real world, project activities are subject to considerable uncertainty, that is gradually resolved during project execution. In this survey we review the fundamental approaches for scheduling under uncertainty: reactive scheduling, stochastic project scheduling, stochastic GERT network scheduling, fuzzy project scheduling, robust (proactive) scheduling and sensitivity analysis. We discuss the potentials of these approaches for scheduling projects under uncertainty.Management; Project management; Robustness; Scheduling; Stability;
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