scholarly journals Solving the Multiobjective Transportation Decision-Making Problem Based on Improved S-Type Membership Function

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Xiang Ziquan ◽  
Yang Jiaqi ◽  
Muhammad Hamza Naseem ◽  
Xiang Zuquan
Keyword(s):  
Decision Making ◽  
Linear Programming ◽  
Utility Function ◽  
Objective Function ◽  
Membership Function ◽  
Programming Model ◽  
Experimental Results ◽  
Decision Making Problem ◽  
Decision Making Model ◽  
Single Objective

Aiming at the problem of multiobjective transportation decision-making, a fuzzy compromise method with an improved S-type membership function is proposed. This method not only considers a single objective and evaluates it marginally but also evaluates the overall objective as a whole. First of all, a multiobjective transportation decision-making model is established. Then, each objective function is mapped to a function on the interval [0,1] through the S-type membership function, thereby transforming the multiobjective transportation linear programming model into a multiobjective transportation fuzzy compromise programming model, and its satisfaction is expressed by the global utility function. Finally, through two examples, the results of the example algorithm are compared with the results in the literature, highlighting the superiority of the method. The experimental results show that in the multiobjective transportation decision-making problem, the fuzzy compromise method of the S-type membership function has better flexibility and effectiveness.

Representing a probabilistic linguistic term set with an interval type-2 fuzzy set and the application in green supplier selection

2021 ◽  
pp. 1-18
Author(s):  
Le Jiang ◽  
Hongbin Liu
Keyword(s):  
Decision Making ◽  
Membership Function ◽  
Fuzzy Set ◽  
Supplier Selection ◽  
Symbolic Model ◽  
Green Supplier Selection ◽  
Linguistic Term ◽  
Interval Type ◽  
Decision Making Model

The use of probabilistic linguistic term sets (PLTSs) means the process of computing with words. The existing methods computing with PLTSs mainly use symbolic model. To provide a semantic model for computing with PLTSs, we propose to represent a PLTS by using an interval type-2 fuzzy set (IT2FS). The key step is to compute the footprint of uncertainty of the IT2FS. To this aim, the upper membership function is computed by aggregating the membership functions of the linguistic terms contained in the PLTS, and the lower membership function is obtained by moving the upper membership function downward with the step being total entropy of the PLTS. The comparison rules, some operations, and an aggregation operator for PLTSs are introduced. Based on the proposed method of computing with PLTSs, a multi-criteria group decision making model is introduced. The proposed decision making model is then applied in green supplier selection problem to show its feasibility.

scholarly journals Farm-Boarding School Management: Linear Programming Contributions in the Search of Self-Sufficiency and Optimization

2017 ◽  
Vol 9 (3) ◽  
pp. 59
Author(s):  
Carina Simionato de Barros ◽  
Gabriela Geraldi Mendonça ◽  
Augusto Hauber Gameiro
Keyword(s):  
Decision Making ◽  
Linear Programming ◽  
Programming Model ◽  
Safety Margin ◽  
Boarding School ◽  
Point Of View ◽  
Technical Programs ◽  
Modeling Process ◽  
Self Sufficiency ◽  
Education Of Students

Farm schools offer a learning environment for the education of students in Agricultural Technical Programs and offer this program adopting boarding systems (“farm-boarding schools” or “FBS”). The big challenge in FBS is balancing education and production, that is, provide resources for practical classes and at the same time provide food for farm residents from a pre-defined budget by the sponsoring institution. The aim of this paper is to present a linear programming model to plan and optimize FBS production and supply. The model was applied in two FBS in Brazil. The model developed could show the complexity of the FBS system, which features a variety of productions and the interactions among them. The modeling process presented positive results from a technical and managerial point of view, including people management. The formulated model showed an optimized scenario which extended the managers’ analysis horizon and allowed safer decision making. The system’s complexity hampers dialogue between the farm-boarding school team and managers. From the modeling process and the standardization of data and generated results, there was a greater safety margin to present investment proposals and analyzes, accelerating the decision-making process, which was a positive addition to the system.

Construction Project Bid Evaluation of Group Decision-Making Model Based on Triangular Fuzzy Number

2013 ◽  
Vol 405-408 ◽  
pp. 3451-3454
Author(s):  
Ming Xuan Zhang ◽  
Dong Lei Zhang
Keyword(s):  
Decision Making ◽  
Membership Function ◽  
Group Decision Making ◽  
Fuzzy Number ◽  
Group Decision ◽  
Comprehensive Evaluation ◽  
Fuzzy Comprehensive Evaluation ◽  
Triangular Fuzzy Number ◽  
Bid Evaluation ◽  
Decision Making Model

A new comprehensive evaluation based on triangular fuzzy number method is put forward in this paper, according to the principle of fuzzy comprehensive evaluation and using trichotomy to determine membership function. And a calculation example is illustrated by using the method presented. The method is a reference to the bid evaluation in the future.

Multi-Attribute Group Decision Making Method for Preference Conflicting with Heterogeneous Information

2018 ◽  
Vol 7 (4) ◽  
pp. 1-14 ◽  
Author(s):  
Kai-Rong Liang
Keyword(s):  
Decision Making ◽  
Objective Function ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Makers ◽  
Heterogeneous Information ◽  
Multi Objective ◽  
Attribute Weights ◽  
Relative Closeness ◽  
Decision Making Model

The aim of this article is to propose a multi-objective decision-making method for researching and solving multi-attribute heterogeneous group decision-making problems. This is in the case that the characters of the decision information and decision makers' preferences are heterogeneous, and the weight information is incomplete. In this method, the multi-objective decision-making model, which considers the alternatives decision relative closeness and the preference of heterogeneous degree of decision makers in the objective function, is put forward. In addition, this article uses the minimax method to derive the multi-objective decision-making model and obtain the attribute weights and decision makers weights, and then the optimal scheme is established. Finally, an illustrative example shows the effectiveness of the proposed method.

scholarly journals Measuring the technical efficiency of local banks in UAE using rough bi-level linear programming technique

2015 ◽  
Vol 1 (1) ◽  
pp. 26
Author(s):  
Doaa Wafik ◽  
O. E. Emam
Keyword(s):  
Decision Making ◽  
Linear Programming ◽  
Technical Efficiency ◽  
Auxiliary Problem ◽  
Optimal Solution ◽  
Objective Functions ◽  
Programming Technique ◽  
Decision Making Problem ◽  
Linear Objective Functions ◽  
Linear Programming Technique

The aim of this paper is to use a bi-level linear programming technique with rough parameters in the constraints, for measuring the technical efficiency of local banks in UAE and Egypt, while the proposed linear objective functions will be maximized for different goals. Based on Dauer's and Krueger's goal programmingmethod, the described approach was developed to deal with the bi-level decision-making problem. The concept of tolerance membership function together was used to generate the optimal solution for the problem under investigation. Also an auxiliary problem is discussed to illustrate the functionality of the proposed approach.

NEW APPROACHES FOR RESOURCE ALLOCATION VIA DEA MODELS

2012 ◽  
Vol 11 (01) ◽  
pp. 103-117 ◽  
Author(s):  
JIE WU ◽  
QINGXIAN AN
Keyword(s):  
Resource Allocation ◽  
Linear Programming ◽  
Programming Model ◽  
Multiple Objective Linear Programming ◽  
Data Envelopment ◽  
Integrated Models ◽  
Decision Making Unit ◽  
Dea Models ◽  
Pareto Efficient ◽  
Single Objective

This paper focuses on the problem of resource allocation through data envelopment analysis. We propose three integrated models for allocating resources. The first model aims at minimizing the input consumption, the second one aims at maximizing the total outputs within the current resources, and the last one aims at maximizing the total outputs using the predicted resources in the next production season. Since the number of inputs or outputs is usually more than one, the abovementioned issue is often a multiple objective linear programming (MOLP) problem. Through the proportion of inputs (outputs) of new decision making unit (DMU) to the total inputs (outputs) of all old DMUs, we transform the MOLP problem into a single objective linear programming model. We assume that decision maker must ensure that the expected outputs of each DMU after allocation in the next production season are not less than this production season. All these proposed models have the same advantage that the results gained from the models are Pareto efficient. A numerical example of 25 supermarkets is used to illustrate our proposed approach.

An integrated neural network stochastic dynamic programming model for optimizing the operation policy of Aswan High Dam

2011 ◽  
Vol 42 (1) ◽  
pp. 50-67 ◽  
Author(s):  
A. H. El-Shafie ◽  
M. S. El-Manadely
Keyword(s):  
Neural Network ◽  
Decision Making ◽  
Dynamic Programming ◽  
Decision Maker ◽  
Stochastic Dynamic Programming ◽  
Programming Model ◽  
Stochastic Dynamic ◽  
Release Policy ◽  
Aswan High Dam ◽  
Decision Making Model

Developing optimal release policies of multipurpose reservoirs is very complex, especially for reservoirs within a stochastic environment. Existing techniques are limited in their ability to represent risks associated with deciding a release policy. The risk aspect of the decisions affects the design and operation of reservoirs. A decision-making model is presented that is capable of replicating the manner in which risks associated with reservoir release decisions are perceived, interpreted and compared by a decision-maker. The model is based on Neural Network (NN) theory. This decision-making model can be used with a Stochastic Dynamic Programming (SDP) approach to produce a NN-SDP model. The resulting integrated model allows the attitudes towards risk of a decision-maker to be considered explicitly in defining the optimal release policy. Clear differences in the policies generated from the basic SDP and the NN-SDP models are observed when examining the operation of Aswan High Dam (AHD). The NN-SDP model yields policies that are more reliable and resilient and less vulnerable than those obtained using the SDP model.

scholarly journals Finding the Most Preferred Decision-Making Unit in Data Envelopment Analysis

2016 ◽  
Vol 2016 ◽  
pp. 1-8
Author(s):  
Shirin Mohammadi ◽  
S. Morteza Mirdehghan ◽  
Gholamreza Jahanshahloo
Keyword(s):  
Decision Making ◽  
Linear Programming ◽  
Data Envelopment Analysis ◽  
Utility Function ◽  
Decision Maker ◽  
Programming Models ◽  
Data Envelopment ◽  
Production Possibility ◽  
Decision Making Unit ◽  
Inputs And Outputs

Data envelopment analysis (DEA) evaluates the efficiency of the transformation of a decision-making unit’s (DMU’s) inputs into its outputs. Finding the benchmarks of a DMU is one of the important purposes of DEA. The benchmarks of a DMU in DEA are obtained by solving some linear programming models. Currently, the obtained benchmarks are just found by using the information of the data of inputs and outputs without considering the decision-maker’s preferences. If the preferences of the decision-maker are available, it is very important to obtain the most preferred DMU as a benchmark of the under-assessment DMU. In this regard, we present an algorithm to find the most preferred DMU based on the utility function of decision-maker’s preferences by exploring some properties on that. The proposed method is constructed based on the projection of the gradient of the utility function on the production possibility set’s frontier.

The Coal Plough Equipment Gray Connection Decision Model Base on Entropy Value Law

2011 ◽  
Vol 201-203 ◽  
pp. 1268-1271
Author(s):  
Qiang Zhang ◽  
Qiu Shuang Song
Keyword(s):  
Decision Making ◽  
Coal Mining ◽  
Membership Function ◽  
Decision Model ◽  
Mining Method ◽  
Model Base ◽  
Decision Making Model ◽  
Choice Method ◽  
Selection Of

The coal plough equipment of traditional choice method has subjective capriciousness question, This paper discuss and analyze the assessment of mining method by entropy value law and gray connection theory, carries on the quantification recursive operation according to the normalizing formula, calculates all levels of membership function separately, it has established the coal plough way gray connection decision-making model. we research and analyze Yangquan coal mining to prove the model, it provide Selection of coal plough decision-making method.

scholarly journals Fuzzy Matrix for Medical Application

2020 ◽  
Vol 9 (7) ◽  
pp. 333-335
Keyword(s):  
Decision Making ◽  
Membership Function ◽  
Thyroid Disease ◽  
Medical Application ◽  
Disease Diagnosis ◽  
Fuzzy Matrix ◽  
Eye Pain ◽  
Decision Making Problem ◽  
Thyroid Disease Diagnosis ◽  
Is Design

The object of this paper is design a triangular AIFM for thyroid disease diagnosis, by making use of the notion of triangular AIFMs . Further, we extended our approach in the sector of addition and multiplication factors of triangular AIFMsbased on membership and non-membership function. In this work Elevated fever, headache, fatigue, eye pain, swollen are taken as important parameters of thyroid disease diagnosis. Finally, we presented a decision making problem based on one of the operation of triangular AIFMs .

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