Fuzzy inventory models for items with imperfect quality and shortage backordering under crisp and fuzzy decision variables

2013 ◽  
Vol 64 (1) ◽  
pp. 190-199 ◽  
Author(s):  
Gour Chandra Mahata ◽  
Adrijit Goswami
Keyword(s):  
Fuzzy Decision ◽  
Inventory Models ◽  
Imperfect Quality ◽  
Decision Variables ◽  
Fuzzy Inventory

scholarly journals Analyzing The Concept Of Graded K-Preference Integration Representation Method

2021 ◽  
Vol 12 (5) ◽  
pp. 866-869
Author(s):  
Anant Tiwari, Dr. Amit Kumar Vats
Keyword(s):  
Integration Method ◽  
Decision Making Process ◽  
Linguistic Variables ◽  
Optimal Solutions ◽  
Order Quantity ◽  
Inventory Models ◽  
Fuzzy Environment ◽  
Representation Method ◽  
Fuzzy Order ◽  
Fuzzy Inventory

Generally, the fuzzy set concept could be used to deal with the problems with the qualities of ambiguity as well as vagueness. In the decision making process, the reference comparisons for criteria & options tend to be more appropriate to make use of the linguistic variables rather than crisp values in some instances. Meanwhile, the GMIR technique is utilized for the constrained trouble construction to derive the weights of options & criteria, which accomplishes the extension of fuzzy environment. Here in this paper we will study about some basic terms related to K-preference Graded Integration method. We will discuss the fuzzy inventory models under decision maker’s preference (k-preference), and find the optimal solutions of these models, the optimal crisp order quantity or the optimal fuzzy order quantity.

scholarly journals Bi-Objective Bilevel Programming Problem: A Fuzzy Approach

2015 ◽  
Vol 11 (2) ◽  
pp. 97-115 ◽  
Author(s):  
S. Haseen ◽  
A. Bari
Keyword(s):  
Programming Problem ◽  
Bilevel Programming ◽  
Decision Model ◽  
Stackelberg Game ◽  
Fuzzy Approach ◽  
Fuzzy Decision ◽  
Bilevel Programming Problem ◽  
Decision Variables ◽  
Fuzzy Decision Model ◽  
Fuzzy Cost

Abstract In this paper, a likely situation of a set of decision maker’s with bi-objectives in case of fuzzy multi-choice goal programming is considered. The problem is then carefully formulated as a bi-objective bilevel programming problem (BOBPP) with multiple fuzzy aspiration goals, fuzzy cost coefficients and fuzzy decision variables. Using Ranking method the fuzzy bi-objective bilevel programming problem (FBOBPP) is converted into a crisp model. The transformed problem is further solved by adopting a two level Stackelberg game theory and fuzzy decision model of Sakawa. A numerical with hypothetical values is also used to illustrate the problem.

scholarly journals Solving Fuzzy Linear Programming Problems with Fuzzy Decision Variables

Mathematics ◽  
2019 ◽  
Vol 7 (7) ◽  
pp. 569
Author(s):  
Wu
Keyword(s):  
Linear Programming ◽  
Numerical Method ◽  
Fuzzy Numbers ◽  
Fuzzy Linear Programming ◽  
Optimal Solutions ◽  
Membership Functions ◽  
Fuzzy Decision ◽  
Existence Of Optimal Solutions ◽  
Decision Variables ◽  
Linear Programming Problems

The numerical method for solving the fuzzy linear programming problems with fuzzydecision variables is proposed in this paper. The difficulty for solving this kind of problem is thatthe decision variables are assumed to be nonnegative fuzzy numbers instead of nonnegative realnumbers. In other words, the decision variables are assumed to be membership functions. One of thepurposes of this paper is to derive the analytic formula of error estimation regarding the approximateoptimal solution. On the other hand, the existence of optimal solutions is also studied in this paper.Finally we present two numerical examples to demonstrate the usefulness of the numerical method.

Direct Solution of Fuzzy Project Crashing Problem with Fuzzy Decision Variables using Tabu Search and Simulated Annealing Algorithms

2017 ◽  
Vol 6 (1) ◽  
pp. 17-35 ◽  
Author(s):  
Tolunay Göçken
Keyword(s):  
Simulated Annealing ◽  
Tabu Search ◽  
Normal Activity ◽  
Transformation Process ◽  
Decision Variable ◽  
Fuzzy Decision ◽  
Project Duration ◽  
Decision Variables ◽  
Important Field ◽  
Annealing Algorithms

Project management is a very important field employed for scheduling activities and monitoring the progress, in competitive and fluctuating environments. Project crashing analysis is concerned with shortening the project duration time by accelerating some of its activities at an additional cost. In reality, because of uncertain environment conditions there can be ambiguity in the parameters of the problem. The uncertainty in the parameters can be modeled via fuzzy set theory. Using fuzzy models give the chance of better project scheduling with more stability under uncertain environmental factors. In this study, a fuzzy project crashing problem with fuzzy decision variable - occurrence time of events - and fuzzy normal activity duration times is handled. The fuzzy project crashing problem is solved without any transformation process by employing a fuzzy ranking method and the tabu search and simulated annealing algorithms.

scholarly journals A Novel Approach to Solve Fully Fuzzy Linear Programming Problems with Modified Triangular Fuzzy Numbers

Mathematics ◽  
2021 ◽  
Vol 9 (22) ◽  
pp. 2937
Author(s):  
Saeid Jafarzadeh Ghoushchi ◽  
Elnaz Osgooei ◽  
Gholamreza Haseli ◽  
Hana Tomaskova
Keyword(s):  
Linear Programming ◽  
Fuzzy Numbers ◽  
Triangular Fuzzy Number ◽  
Fuzzy Linear Programming ◽  
Fuzzy Decision ◽  
Triangular Fuzzy Numbers ◽  
Novel Approach ◽  
Decision Variables ◽  
Linear Programming Problems ◽  
Fuzzy Solution

Recently, new methods have been recommended to solve fully fuzzy linear programming (FFLP) issues. Likewise, the present study examines a new approach to solve FFLP issues through fuzzy decision parameters and variables using triangular fuzzy numbers. The strategy, which is based on alpha-cut theory and modified triangular fuzzy numbers, is suggested to obtain the optimal fully fuzzy solution for real-world problems. In this method, the problem is considered as a fully fuzzy problem and then is solved by applying the new definition presented for the triangular fuzzy number to optimize decision variables and the objective function. Several numerical examples are solved to illustrate the above method.

scholarly journals Fuzzy expert marketing-mix model

2012 ◽  
Vol 51 (No. 2) ◽  
pp. 69-79 ◽  
Author(s):  
S. Aly ◽  
I. Vrana
Keyword(s):  
Business Environment ◽  
Marketing Mix ◽  
Fuzzy Decision Making ◽  
Fuzzy Decision ◽  
Business Environments ◽  
Marketing Decision ◽  
Decision Variables ◽  
Proposed Model ◽  
Decision Making System ◽  
Agricultural Business

A marketing-mix setting model is presented. The all four P’s are integrated and identified. The model makes strong utilization of relevant experts’ knowledge and expertise through a fuzzy-decision-making system tailored to dynamically set the marketing-mix periodically in response to changing business environment. Quantitative, qualitative, uncertain, and vague variables are handled necessary to provide a realistic solution. The proposed model is particularly applicable to changing business environments that are full of such qualitative, stochastic, uncertain, and vague variables as in the case of agricultural business (e.g., agro-food companies, fertilizers and agro-chemical producers), and generally applicable to any other business sector. The method can be considered as the fuzzy-expert system for determining values of the marketing decision variables. 

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