A New Multi-Objective Model for R&D Project Portfolio Selection Considering Potential Repetitive Projects and Sanction Impacts

A New Multi-Objective Model for R&D Project Portfolio Selection Considering Potential Repetitive Projects and Sanction Impacts

Masoud Rabbani, Amirhossein Najjarbashi, Mohammad Joudi
Copyright: © 2013 |Pages: 14
DOI: 10.4018/ijsds.2013100103
OnDemand:
(Individual Articles)
Available
$37.50
No Current Special Offers
TOTAL SAVINGS: $37.50

Abstract

In today’s highly competitive marketplace, selecting an appropriate set of projects from a portfolio of candidate projects is vital for enterprises. An accurate selection of projects can steer a company to great success, while a careless selection may lead it to bankruptcy. Variability of project parameters such as benefit, cost, risk (failure probability), etc. during planning horizon makes this selection more complicated and increases the importance of an elaborate analysis. In this article, we studied a multi-objective R&D project portfolio selection problem. There is a conflicting desire to maximize expected net benefit and minimize risk in companies. From a novel perspective, the authors considered repetitive projects and variable amounts for aforementioned project parameters during planning horizon that could be an effect of sanctions, in our model that are features of real world problems. Due to NP-hardness of the problem and its high computational effort especially when the number of projects grows, we solved test problems of different sizes using a Multi-Objective Differential Evolution (MODE) algorithm to find pareto optimal solutions.
Article Preview
Top

Introduction

Nowadays, in the highly competitive and globalized marketplace, it’s a necessity to be dynamic, willing to change and innovative in presenting new products. Innovation is one of the significant key strategies for high technology firms to survive. Thus, research and development (R&D) has a critical role in successful performance of these firms.

The portfolio selection is one of the most important strategic decision processes in the definition stage of a project (Deng & Li, 2010; Jianguo & Liang, 2011). Its main purpose is to choose certain group of projects from candidate ones according to some objectives, such as company developing strategies, project investments, project returns and the risks. There are many different techniques that can be used to estimate, evaluate, and choose project portfolios. Some of these techniques are not widely used because they address only some of the above issues, they are too complex and require too much input data, they may be too difficult for decision makers to understand and use, or they may not be used in the form of an organized process (Ghasemzadeh & Archer, 2000). R&D project selection methods can usually be placed into one of the following categories (Henriksen & Traynor, 1999):

  • Unstructured peer review;

  • Scoring;

  • Mathematical programming, including integer programming (IP), linear programming (LP), nonlinear programming (NLP), goal programming (GP), and dynamic programming (DP);

  • Economic models, such as internal return rate (IRR), Net present value (NPV), return on investment (ROI), Cost-benefit analysis, and option pricing theory;

  • Decision analysis, including multi-attribute utility theory (MAUT), decision trees, risk analysis, and the Analytic hierarchy process (AHP);

  • Interactive methods, such as Delphi, Q-sort, Behavioral decision aids (BDA), and Decentralized hierarchical modeling (DHM);

  • Artificial intelligence (AI), including expert systems and fuzzy sets;

The decision quality has great influences on the benefits and the efficiency of the use of resources of the company (Martino, 1995). However, there are two key obstacles for this process: (a) Incomplete and unreliable information which is caused by future events and opportunities that the decision process has to deal with, and (b) difficulties in tradeoffs which are caused by the multi-objective decision making process (Bagloee & Reddick, 2011; Das, Sarkar, & Ray, 2012; Jajimoggala, Kesava Rao, & Beela, 2011; Jajimoggala, Rao, & Beela, 2010; Michalopoulos, Georgiou, & Paparrizos, 2009; Nooraie, 2011; Sodenkamp & Suhl, 2012; J. Wang & Hwang, 2007).

Due to the great importance of project portfolio selection for companies and organizations, many works have been done to tackle the problem since 50 years ago and it attracted a great attention to deal with the R&D project portfolio selection in recent years. In the following of this section we reviewed some recent papers since 2000 that studied R&D project portfolio selection:

Complete Article List

Search this Journal:
Reset
Volume 15: 1 Issue (2024): Forthcoming, Available for Pre-Order
Volume 14: 1 Issue (2023)
Volume 13: 4 Issues (2022): 1 Released, 3 Forthcoming
Volume 12: 3 Issues (2021)
Volume 11: 4 Issues (2020)
Volume 10: 4 Issues (2019)
Volume 9: 4 Issues (2018)
Volume 8: 4 Issues (2017)
Volume 7: 4 Issues (2016)
Volume 6: 4 Issues (2015)
Volume 5: 4 Issues (2014)
Volume 4: 4 Issues (2013)
Volume 3: 4 Issues (2012)
Volume 2: 4 Issues (2011)
Volume 1: 4 Issues (2010)
View Complete Journal Contents Listing