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 Two-Stage Fuzzy Portfolio Selection Problem with Transaction Costs

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Yanju Chen ◽  
Ye Wang
Keyword(s):  
Transaction Costs ◽  
Portfolio Selection ◽  
Optimal Solution ◽  
Single Stage ◽  
Selection Problem ◽  
Stage Model ◽  
Two Stage ◽  
Portfolio Selection Problem ◽  
Fuzzy Portfolio Selection ◽  
Proposed Model

This paper studies a two-period portfolio selection problem. The problem is formulated as a two-stage fuzzy portfolio selection model with transaction costs, in which the future returns of risky security are characterized by possibility distributions. The objective of the proposed model is to achieve the maximum utility in terms of the expected value and variance of the final wealth. Given the first-stage decision vector and a realization of fuzzy return, the optimal value expression of the second-stage programming problem is derived. As a result, the proposed two-stage model is equivalent to a single-stage model, and the analytical optimal solution of the two-stage model is obtained, which helps us to discuss the properties of the optimal solution. Finally, some numerical experiments are performed to demonstrate the new modeling idea and the effectiveness. The computational results provided by the proposed model show that the more risk-averse investor will invest more wealth in the risk-free security. They also show that the optimal invested amount in risky security increases as the risk-free return decreases and the optimal utility increases as the risk-free return increases, whereas the optimal utility increases as the transaction costs decrease. In most instances the utilities provided by the proposed two-stage model are larger than those provided by the single-stage model.

scholarly journals Solving multi-level multiobjective fractional programming problem with rough interval parameter under neutrosophic environment

2021 ◽  
Author(s):  
FIROZ AHMAD
Keyword(s):  
Goal Programming ◽  
Fractional Programming ◽  
Optimal Solution ◽  
Fuzzy Goal Programming ◽  
Programming Algorithm ◽  
Objective Functions ◽  
Multiobjective Fractional Programming ◽  
Upper Approximation ◽  
Fuzzy Goal ◽  
Multi Level

In this study, a novel algorithm is developed to solve the multi-level multiobjective fractional programming problems, using the idea of a neutrosophic fuzzy set. The co-efficients in each objective functions is assumed to be rough intervals. Furthermore, the objective functions are transformed into two sub-problems based on lower and upper approximation intervals. The marginal evaluation of pre-determined neutrosophic fuzzy goals for all objective functions at each level is achieved by different membership functions, such as truth, indeterminacy/neutral, and falsity degrees in neutrosophic uncertainty. In addition, the neutrosophic fuzzy goal programming algorithm is proposed to attain the highest degrees of each marginal evaluation goals by reducing their deviational variables and consequently obtain the optimal solution for all the decision-makers at all levels. To verify and validate the proposed neutrosophic fuzzy goal programming techniques, a numerical example is adressed in a hierarchical decision-making environment along with the conclusions.

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.

A fuzzy goal programming approach to portfolio selection

2001 ◽  
Vol 133 (2) ◽  
pp. 287-297 ◽  
Author(s):  
M. Arenas Parra ◽  
A. Bilbao Terol ◽  
M.V. Rodrı́guez Urı́a
Keyword(s):  
Portfolio Selection ◽  
Goal Programming ◽  
Fuzzy Goal Programming ◽  
Programming Approach ◽  
Fuzzy Goal
Sign in / Sign up

Export Citation Format

Share Document