A Linear Programming Model of Fuzzy Portfolio Selection Problem

Author(s):  
Yuping Lan ◽  
Xuanli Lv ◽  
Weiguo Zhang
2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Yanju Chen ◽  
Ye Wang

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.


2018 ◽  
Vol 154 ◽  
pp. 01071 ◽  
Author(s):  
Purnawan Adi Wicaksono ◽  
I Nyoman Pujawan ◽  
Erwin Widodo ◽  
Sutrisno ◽  
Laila Izzatunnisa

Supplier selection is one of the most important elements in supply chain management. This function involves evaluation of many factors such as, material costs, transportation costs, quality, delays, supplier capacity, storage capacity and others. Each of these factors varies with time, therefore, supplier identified for one period is not necessarily be same for the next period to supply the same product. So, mixed integer linear programming (MILP) was developed to overcome the dynamic supplier selection problem (DSSP). In this paper, a mixed integer linear programming model is built to solve the lot-sizing problem with multiple suppliers, multiple periods, multiple products and quantity discounts. The buyer has to make a decision for some products which will be supplied by some suppliers for some periods cosidering by discount. To validate the MILP model with randomly generated data. The model is solved by Lingo 16.


Author(s):  
C.O. Anyaeche ◽  
R.A. Okwara

Project portfolio selection involves decision making and it plays a crucial role in any organization. Therefore selecting not just the right projects but also the right mix of projects for the portfolio is considered as one of the most important tasks for organisations to ensure the achievement of the corporate strategy within limited resources and capabilities of the organization. Prioritizing and selecting optimal project portfolio can be very challenging especially with a large number of projects with multiple constraints and interdependences. In an ideal world with unlimited budget the project selection process would be very straightforward. However, this is not the case in life situations. In this work, an attempt is made to address this challenge. An integer linear programming model for project selection was developed and applied in a selected organization in Nigeria. The model seeks to optimize the mix of the projects to be undertaken while keeping the total cost and project interdependency as constraints. The analysis of the results showed that a total of 11 projects out of 16 were eligible for selection in the period under review. The total cost of the selected project was 92,840,000 Naira, which was about 90% of the total budget. Ordinarily, apart from not prioritizing and obtaining an optimal project mix, the community would have spread its entire resources on the 16 projects with some of them being abandoned later. The model can also be used to plan an optimal mix of project portfolio for a future date within the limitations of a given set of constraints and interdependence.


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