scholarly journals Maritime Supply Chain Optimization by Using Fuzzy Goal Programming

Algorithms ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 234
Author(s):  
Bekir Sahin ◽  
Devran Yazir ◽  
Abdelsalam Adam Hamid ◽  
Noorul Shaiful Fitri Abdul Rahman
Keyword(s):  
Supply Chain ◽  
Goal Programming ◽  
Optimal Solution ◽  
Theoretical Background ◽  
Fuzzy Goal Programming ◽  
Supply Chain Optimization ◽  
Mathematical Algorithm ◽  
Supply Chain Logistics ◽  
Solution Methods ◽  
Fuzzy Goal

Fuzzy goal programming has important applications in many areas of supply chain, logistics, transportation and shipping business. Business management has complications, and there exist many interactions between the factors of its components. The locomotive of world trade is maritime transport and approximately 90% of the products in the world are transported by sea. Optimization of maritime operations is a challenge in order to provide technical, operational and financial benefits. Fuzzy goal programming models attract interests of many scholars, therefore the objective of this paper is to investigate the problem of minimization of total cost and minimization of loss or damage of containers returned from destination port. There are various types of fuzzy goal programming problems based on models and solution methods. This paper employs fuzzy goal programming with triangular fuzzy numbers, membership functions, constraints, assumptions as well as the variables and parameters for optimizing the solution of the model problem. The proposed model presents the mathematical algorithm, and reveals the optimal solution according to satisfaction rank from 0 to 1. Providing a theoretical background, this study offers novel ideas to researchers, decision makers and authorities.

Fuzzy Goal Programming With Interval Type-2 for Solving Multi-Objective Sustainable Supplier Selection Problems

2021 ◽  
pp. 164-197
Author(s):  
Nurullah UMARUSMAN
Keyword(s):  
Supply Chain ◽  
Goal Programming ◽  
Supplier Selection ◽  
De Novo ◽  
Fuzzy Goal Programming ◽  
Multi Objective ◽  
Sustainable Supplier Selection ◽  
Fuzzy Goal ◽  
Interval Type

Supply chain management is going on changing and developing in line with the needs of the growing global supply chain. Performance of supply chain, considered as a whole so that businesses can accommodate these evolvements and change, needs to be improved in the long run. Actually, businesses work with suppliers complying with their policies from past to present. However, other dimensions of sustainability should be considered, as well as economic criteria when selecting suppliers. With the right supplier selection made in this respect, by contributing to the efficient functioning of the supply chain, it will increase customer satisfaction, and therefore, the enterprises will reach the goals they set. The solution of the multi-objective sustainable supplier selection problem has been realized by using the “satisfied optimal supplier design” algorithm, also called fuzzy goal programming, with de novo-based interval type-2 proposed in this study.

scholarly journals Portfolio selection problem: a comparison of fuzzy goal programming and linear physical programming

2016 ◽  
Vol 6 (2) ◽  
pp. 121-128 ◽  
Author(s):  
Fusun Kucukbay ◽  
Ceyhun Araz
Keyword(s):  
Portfolio Selection ◽  
Goal Programming ◽  
Optimal Solution ◽  
Good Alternative ◽  
Fuzzy Goal Programming ◽  
Selection Problem ◽  
Physical Programming ◽  
Portfolio Selection Problem ◽  
Linear Physical Programming ◽  
Fuzzy Goal

Investors have limited budget and they try to maximize their return with minimum risk. Therefore this study aims to deal with the portfolio selection problem. In the study two criteria are considered which are expected return, and risk. In this respect, linear physical programming (LPP) technique is applied on Bist 100 stocks to be able to find out the optimum portfolio. The analysis covers the period April 2009- March 2015. This period is divided into two; April 2009-March 2014 and April 2014 – March 2015. April 2009-March 2014 period is used as data to find an optimal solution. April 2014-March 2015 period is used to test the real performance of portfolios. The performance of the obtained portfolio is compared with that obtained from fuzzy goal programming (FGP). Then the performances of both method, LPP and FGP are compared with BIST 100 in terms of their Sharpe Indexes. The findings reveal that LPP for portfolio selection problem is a good alternative to FGP.

scholarly journals A Fuzzy Goal Programming Approach for Solving Multi-Objective Supply Chain Network Problems with Pareto-Distributed Random Variables

2019 ◽  
Vol 27 (04) ◽  
pp. 559-593 ◽  
Author(s):  
Vincent Charles ◽  
Srikant Gupta ◽  
Irfan Ali
Keyword(s):  
Supply Chain ◽  
Goal Programming ◽  
Fuzzy Goal Programming ◽  
Programming Approach ◽  
Supply Chain Network ◽  
Delivery Time ◽  
Demand And Supply ◽  
Multi Objective ◽  
Weighted Goal Programming ◽  
Fuzzy Goal

Uncertainty is unavoidable and addressing the same is inevitable. That everything is available at our doorstep is due to a well-managed modern global supply chain, which takes place despite its efficiency and effectiveness being threatened by various sources of uncertainty originating from the demand side, supply side, manufacturing process, and planning and control systems. This paper addresses the demand- and supply-rooted uncertainty. In order to cope with uncertainty within the constrained multi-objective supply chain network, this paper develops a fuzzy goal programming methodology, with solution procedures. The probabilistic fuzzy goal multi-objective supply chain network (PFG-MOSCN) problem is thus formulated and then solved by three different approaches, namely, simple additive goal programming approach, weighted goal programming approach, and pre-emptive goal programming approach, to obtain the optimal solution. The proposed work links fuzziness in transportation cost and delivery time with randomness in demand and supply parameters. The results may prove to be important for operational managers in manufacturing units, interested in optimizing transportation costs and delivery time, and implicitly, in optimizing profits. A numerical example is provided to illustrate the proposed model.

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