Multiple-criteria decision-making in two-sided assembly line balancing: A goal programming and a fuzzy goal programming models

2009 ◽  
Vol 36 (6) ◽  
pp. 1955-1965 ◽  
Author(s):  
Uğur Özcan ◽  
Bilal Toklu
Keyword(s):  
Decision Making ◽  
Goal Programming ◽  
Assembly Line ◽  
Assembly Line Balancing ◽  
Multiple Criteria Decision Making ◽  
Multiple Criteria ◽  
Fuzzy Goal Programming ◽  
Programming Models ◽  
Line Balancing ◽  
Fuzzy Goal

WEIGHTED ADDITIVE MODELS FOR SOLVING FUZZY GOAL PROGRAMMING PROBLEMS

2008 ◽  
Vol 25 (05) ◽  
pp. 715-733 ◽  
Author(s):  
M. A. YAGHOOBI ◽  
D. F. JONES ◽  
M. TAMIZ
Keyword(s):  
Decision Making ◽  
Goal Programming ◽  
Real Life ◽  
Additive Model ◽  
Multiple Criteria Decision Making ◽  
Multiple Criteria ◽  
Fuzzy Goal Programming ◽  
Additive Models ◽  
New Model ◽  
Fuzzy Goal

Weighted additive models are well known for dealing with multiple criteria decision making problems. Fuzzy goal programming is a branch of multiple criteria decision making which has been applied to solve real life problems. Several weighted additive models are introduced to handle fuzzy goal programming problems. These models are based on two approaches in fuzzy goal programming namely goal programming and fuzzy programming techniques. However, some of these models are not able to solve all kinds of fuzzy goal programming problems and some of them that appear in current literature suffer from a lack of precision in their formulations. This paper focuses on weighed additive models for fuzzy goal programming. It explains the oversights within some of them and proposes the necessary corrections. A new improved weighted additive model for solving fuzzy goal programming problems is introduced. The relationships between the new model and some of the existing models are discussed and proved. A numerical example is given to demonstrate the validity and strengths of the new model.

Multiple-criteria fuzzy group decision-making with multi-choice goal programming for supplier selection: A case study

2019 ◽  
Vol 11 (03) ◽  
pp. 1950029
Author(s):  
Ashoke Kumar Bera ◽  
Dipak Kumar Jana ◽  
Debamalya Banerjee ◽  
Titas Nandy
Keyword(s):  
Decision Making ◽  
Goal Programming ◽  
Supplier Selection ◽  
Multiple Criteria Decision Making ◽  
Fuzzy Topsis ◽  
Multiple Criteria ◽  
Linguistic Variables ◽  
Manufacturing Organization ◽  
Fuzzy Group Decision Making

In today’s highly turbulent and competitive environment, the success of the organization depends on the performance of its suppliers. However, supplier selection problems are complex as they involve a large number of criteria and, frequently, some of the criteria cannot be evaluated precisely. Moreover, fluctuations of supplier performances and unknown information always exist in real-world decision-making. It is a complex multiple-criteria decision-making (MCDM) problem as it involves a trade-off among various criteria with vagueness and imprecision and also involves a group of experts with diverse opinion. Therefore, to make more practical decisions, this paper is intended to propose an integrated technique for order preference by similarity to ideal solution (TOPSIS) in fuzzy environment with multi-choice goal programming (MCGP) to handle the supplier assessment and order allocation for a battery manufacturing organization. Using linguistic variables, the decision-makers assess the rating of suppliers as well as the importance of various factors. Linguistic variables are expressed in trapezoidal fuzzy numbers (TrFN). Fuzzy-TOPSIS method is proposed to obtain the rank of suppliers and MCGP method is used to allocate suitable orders to the selected suppliers. A case study is implemented to find the applicability and validity of the proposed model. Finally, sensitivity analysis is performed to observe the effect of weights of criteria on supplier evaluation problem.

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