Selecting an ERP system using multi-criteria decision making method: a goal programming and fuzzy approach

2014 ◽  
Vol 16 (1) ◽  
pp. 55 ◽  
Author(s):  
Abolfazl Kazemi ◽  
Seyed Reza Saeidi ◽  
Mahdi Azizmohammadi
Keyword(s):  
Decision Making ◽  
Goal Programming ◽  
Multi Criteria Decision Making ◽  
Fuzzy Approach ◽  
Erp System

A Fuzzy Approach for Ranking of Student's Expectation From a Technical Institute

2021 ◽  
pp. 1628-1640
Author(s):  
Ajit Kumar Singh ◽  
A. M. Rawani
Keyword(s):  
Decision Making ◽  
Technical Education ◽  
Education Sector ◽  
Educational Services ◽  
Multi Criteria Decision Making ◽  
Fuzzy Approach ◽  
Technical Institute ◽  
Student Expectations

Due to high competition and less employability in the technical education sector, quality in technical education has turned out to be most extreme imperative criteria to deliver better educational services. For this reason, it is required to screen the expectation of the customer of the education sector for fulfilling their needs. With aim of this, this article first illustrates the identification of the customer of the education sector, then their expectations from an institute and finally a detailed ranking of each expectation which has been done. For the ranking of student's expectations, various authors have used a number of multi-criteria decision-making methods, but the vagueness of the result was not being handled in their research. Therefore, in this study, a fuzzy approach has been used to rank the various expectations of customers. The result of the study indicates that among all student expectations, the job-oriented expectation is the most important expectation and further, an ergonomics-based expectation and a sports-based expectation are the least important expectations of the students.

Goal Programming and Its Variants

2011 ◽  
pp. 410-417
Author(s):  
John Wang ◽  
Dajin Wang ◽  
Aihua Li
Keyword(s):  
Decision Making ◽  
Linear Programming ◽  
Goal Programming ◽  
Multicriteria Decision Making ◽  
Industrial Applications ◽  
Multiple Objective ◽  
Multi Criteria Decision Making ◽  
Powerful Method ◽  
Noticeable Increase ◽  
New Type

Within the realm of multicriteria decision making (MCDM) exists a powerful method for solving problems with multiple objectives. Goal programming (GP) was the first multiple-objective technique presented in the literature (Dowlatshahi, 2001). The premise of GP traces its origin back to a linear programming study on executive compensation in 1955 by Charnes, Cooper, and Ferguson even though the specific name did not appear in publications until the 1961 textbook entitled Management Models and Industrial Applications of Linear Programming, also by Charnes and Cooper (Schniederjans, 1995). Initial applications of this new type of modeling technique demonstrated its potential for a variety of applications in numerous different areas. Until the middle of the 1970s, GP applications reported in the literature were few and far between. Since that time, primarily due to influential works by Lee and Ignizio, a noticeable increase of published GP applications and technical improvements has been recognized. The number of case studies, along with the range of fields, to which GP has been and still is being applied is impressive, as shown in surveys by Romero (1991) and Aouni and Kettani (2001). It can be said that GP has been, and still is, the “most widely used multi-criteria decision making technique” (Tamiz, Jones, & Romero, 1998, p. 570).

Contractor Selection Using Integrated Goal Programming and Fuzzy ELECTRE

2014 ◽  
Vol 5 (3) ◽  
pp. 65-86 ◽  
Author(s):  
Ahmad Jafarnejad Chaghooshi ◽  
Ehsan Khanmohammadi ◽  
Maryam Faghei ◽  
Amir Karimi
Keyword(s):  
Decision Making ◽  
Goal Programming ◽  
Fuzzy Numbers ◽  
Multi Criteria Decision Making ◽  
Contractor Selection ◽  
Trapezoidal Fuzzy Numbers ◽  
Technical Capacity ◽  
Selection Of

Outsourcing plays an important role in the success of organizations. One of the risks associated with outsourcing is inappropriate contractor selection which significantly influences the implementation of projects in terms of time, quality, and cost. In this study, we applied multi-criteria decision-making techniques in order to determine the best contractor using criteria such as reputation, offered price, and technical capacity. This study is primarily aimed at identifying important criteria of contractor selection, determining the significance of the criteria, and designing a framework for selection of the most appropriate contractor. Important criteria for selecting contractors were extracted from the literature and experts' views were collected using questionnaire. Accordingly, six criteria were selected and their weights were determined by the application of goal programming. Finally, contractors were ranked and the best contractor was selected using fuzzy ELECTRE technique with trapezoidal fuzzy numbers.

scholarly journals Multi-Criteria Decision-Making Techniques for Solving the Airport Ground Handling Service Equipment Vendor Selection Problem

2019 ◽  
Vol 11 (12) ◽  
pp. 3466 ◽  
Author(s):  
Shen ◽  
Peng ◽  
Tu
Keyword(s):  
Decision Making ◽  
Goal Programming ◽  
Quantitative Methods ◽  
Weighted Average ◽  
Fuzzy Topsis ◽  
Programming Approach ◽  
Vendor Selection ◽  
Multi Criteria Decision Making ◽  
Study Results ◽  
Ground Handling

Appropriate airport ground handling service (AGHS) equipment vendor selection (AGHSEVS) can prevent aircraft damage and delays in airlines schedules, and ensure reliable and high-quality ground handling service. Previous research has seldom integrated multi-criteria decision-making techniques with goal programming to solve the AGHSEVS problem. This paper describes a new system evaluation model for AGHSEVS by considering both qualitative and quantitative methods. We compare the fuzzy TOPSIS method based on fuzzy weighted average left and right score methods with multi-choice and multi-aspiration goal programming approach of an AGHS company in Taiwan. These study results can help airport ground handling service company managers make optimal decisions for AGHSEVS problems. We hope the practicability of the comparable model with slight modifications of real situation data can be used in other AGHS companies.

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