1,162 research outputs found
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
An integrated model for solving production planning and production capacity problems using an improved fuzzy model for multiple linear programming according to Angelov's method
Decision making has become a part of our everyday lives. The main apprehension is that almost all decision difficulties include certain criteria, which usually can be multiple or conflicting. Certainly, the production planning and production capacity development includes several parameters uncertainty such as fuzzy resource capacity, fuzzy demand and fuzzy production rate. This situation makes decision maker challenging to describe the objective crisply and at the end the real optimum solution cannot attained correctly. The Fuzzy model for multi-objective linear programming should be an suitable approach for dealing with the production planning and production capacity (PP& PC) problems. The PP& PC problem based on the fuzzy environment becomes even more sophisticated as decision makers try to consider multi-objectives, Therefore, this study attempts to propose a novel scheme which is capable of dealing with these obstacles in PP& PC problem. Intuitionistic Fuzzy Optimization (1FO) by implementing the optimization problem in an Intuitionistic Fuzzy Set (IFS) environment and considered the degrees of rejection of objective(s) and of constraints as the complement of satisfaction degrees. The aim of the research is to propose a new method capable of dealing with these obstacles in the PP & PC problem. It takes into account uncertainty and makes trade-offs between multiple conflicting goals simultaneously. To verify the validity of the proposed method, a case study of the fuzzy multi-objective model of the PP&PC is used. This research takes into account uncertainty and makes a comparison between multiple conflicting goals at the same time. Therefore, this study attempts to propose a new scheme which is the modified Angelov’s approach
NEUTROSOPHIC MULTI-OBJECTIVE LINEAR PROGRAMMING
For modeling imprecise and indeterminate data for multi-objective decision making, two different methods: neutrosophic multi-objective linear/non-linear programming neutrosophic goal programming, which have been very recently proposed in the literatuire. In many economic problems, the well-known probabilities or fuzzy solutions procedures are not suitable because they cannot deal the situation when indeterminacy inherently involves in the problem. In this case we propose a new concept in optimization problem under uncertainty and indeterminacy. It is an extension of fuzzy and intuitionistic fuzzy optimization in which the degrees of indeterminacy and falsity (rejection) of objectives and constraints are simultaneously considered together with the degrees of truth membership (satisfaction/acceptance). The drawbacks of the existing neutrosophic optimization models have been presented and new framework of multi-objective optimization in neutrosophic environment has been proposed. The essence of the proposed approach is that it is capable of dealing with indeterminacy and falsity simultaneously
Intuitionistic Fuzzy Programming Technique to Solve Multi- Objective Transportation Problem
This paper presents an explanation of the multi-objective-transportation problem (MOTP) via Fuzzy programming algorithm and the goods is to be transported from origin to destination. The time and cost of transportation from origin i to destination j were recorded. Here we-have considered MOTP with-intuitionistic fuzzy numbers and completed the problem in both ways. Therefore, the optimal compromise solution will remain same both the exponential and linear membership function. For the solution the membership functions are used for such a problem. LINDO statistical-software was used in the present facts analysis and is completed in two stages
Multi-objective fully intuitionistic fuzzy fixed-charge solid transportation problem
During past few decades, fuzzy decision is an important attention in the areas of science, engineering, economic system,
business, etc. To solve day-to-day problem, researchers use fuzzy data in transportation problem for presenting the uncontrollable
factors; and most of multi-objective transportation problems are solved using goal programming. However, when the
problem contains interval-valued data, then the obtained solution was provided by goal programming may not satisfy by all
decision-makers. In such condition, we consider a fixed-charge solid transportation problem in multi-objective environment
where all the data are intuitionistic fuzzy numbers with membership and non-membership function. The intuitionistic fuzzy
transportation problem transforms into interval-valued problem using (α, β)-cut, and thereafter, it reduces into a deterministic
problem using accuracy function. Also the optimum value of alternative corresponds to the optimum value of accuracy
function. A numerical example is included to illustrate the usefulness of our proposed model. Finally, conclusions and future
works with the study are described.Portuguese Foundation for Science and Technology ("FCT-Fundacao para a Ciencia e a Tecnologia"), through the CIDMA-Center for Research and Development in Mathematics and Applications
UID/MAT/ 04106/2019Spanish Ministry of Economy and Competitiveness, FEDER funds from the European Union
TIN2014-55024-P
TIN2017-86647-
An Efficient Ranking Technique for Intuitionistic Fuzzy Numbers with Its Application in Chance Constrained Bilevel Programming
The aim of this paper is to develop a new ranking technique for intuitionistic fuzzy numbers using the method of defuzzification based on probability density function of the corresponding membership function, as well as the complement of nonmembership function. Using the proposed ranking technique a methodology for solving linear bilevel fuzzy stochastic programming problem involving normal intuitionistic fuzzy numbers is developed. In the solution process each objective is solved independently to set the individual goal value of the objectives of the decision makers and thereby constructing fuzzy membership goal of the objectives of each decision maker. Finally, a fuzzy goal programming approach is considered to achieve the highest membership degree to the extent possible of each of the membership goals of the decision makers in the decision making context. Illustrative numerical examples are provided to demonstrate the applicability of the proposed methodology and the achieved results are compared with existing techniques
Matrix Game with Payoffs Represented by Triangular Dual Hesitant Fuzzy Numbers
Matrix Game with Payoffs RepresentedDue to the complexity of information or the inaccuracy of decision-makers’ cognition, it is difficult for experts to quantify the information accurately in the decision-making process. However, the integration of the fuzzy set and game theory provides a way to help decision makers solve the problem. This research aims to develop a methodology for solving matrix game with payoffs represented by triangular dual hesitant fuzzy numbers (TDHFNs). First, the definition of TDHFNs with their cut sets are presented. The inequality relations between two TDHFNs are also introduced. Second, the matrix game with payoffs represented by TDHFNs is investigated. Moreover, two TDHFNs programming models are transformed into two linear programming models to obtain the numerical solution of the proposed fuzzy matrix game. Furthermore, a case study is given to to illustrate the efficiency and applicability of the proposed methodology. Our results also demonstrate the advantage of the proposed concept of TDHFNs
Solving fully neutrosophic linear programming problem with application to stock portfolio selection
Neutrosophic set is considered as a generalized of crisp set, fuzzy set, and intuitionistic fuzzy set for representing the uncertainty, inconsistency, and incomplete knowledge about the real world problems. In this paper, a neutrosophic linear programming (NLP) problem with single-valued trapezoidal neutrosophic numbers is formulated and solved. A new method based on the so-called score function to find the neutrosophic optimal solution of fully neutrosophic linear programming (FNLP) problem is proposed. This method is more flexible than the linear programming (LP) problem, where it allows the decision maker to choose the preference he is willing to take. A stock portfolio problem is introduced as an application. Also, a numerical example is given to illustrate the utility and practically of the method
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