Possibility theory for multiobjective fuzzy random portfolio optimization

Abstract

The problem of portfolio optimization is a standard problem in financial world and it has received tremendous attentions. Portfolio optimization plays essential role in determining portfolio strategies for investors. Portfolio optimization is intrinsically a discrete optimization problem whose decision criteria are in conflict and the proposed study of this paper considers a portfolio optimization problem involving fuzzy random variables. To solve the proposed model, we first present the possibility and necessity-based model to reformulate the fuzzy random portfolio selection model into linear programming models and using the resulted linear programs, a multi-objective problem is constructed. To solve the multi-objective problem we propose some methods to consider decision makers' optimistic and pessimistic views. A numerical example illustrates the whole idea on multiobjective fuzzy random portfolio optimization by possibility and necessity-based model.

An Application of Fuzzy Clustering to Customer Portfolio Analysis in Automotive Industry

“…There are many studies on the applications of fuzzy clustering in business and management including planning, engineering, design and management of production (Wang & Hwang, 2007). Fuzzy oriented applications mainly focus on evaluation of different research and development portfolio models such as Masood (2014), financial portfolio optimization problem as in Sadati et al (2014) or they are related to portfolio application in B2B or supplier relationship context similar to the work of Toth et al (2015). The applications of fuzzy models in marketing context could also be found in the related literature covering areas including product innovation, product development, project marketing and customer portfolio analysis (Bozdag, Kahraman, & Ruan, 2003;Buyukozkan, Feyzioglu, & Nebol, 2008;Hsu & Chiu, 2004;Danneels & Kleinschmidtb, 2001;Hiziroglu et al, 2013;Thieme & Song, 2000).…”