Title: Application of genetic and differential evolution algorithms on selecting portfolios of projects with consideration of interactions and budgetary segmentation

Authors: Majid Shakhsi-Niaei; Morteza Shiripour; Hamed Shakouri G.; Seyed Hossein Iranmanesh

Addresses: Department of Industrial Engineering, 2nd Campus of Engineering College, Jalal Ale Ahmad Junction, North Kargar, Tehran, Iran ' Department of Industrial Engineering, 2nd Campus of Engineering College, Jalal Ale Ahmad Junction, North Kargar, Tehran, Iran ' Department of Industrial Engineering, 2nd Campus of Engineering College, Jalal Ale Ahmad Junction, North Kargar, Tehran, Iran ' Department of Industrial Engineering, 2nd Campus of Engineering College, Jalal Ale Ahmad Junction, North Kargar, Tehran, Iran

Abstract: Nowadays, defining new projects is significantly vital and necessary for many organisations and companies. The problem arise here is how to select an appropriate portfolio from a set of candidate projects. A good combination of projects can extensively promote the organisations in their competitive performance. Thus, the purpose of this study is to present a practical model in addition to some solution approaches to choose the best and proper project portfolios with the considerations of projects' interactions, quantitative and qualitative criteria, and practical constraints. A linear formulation has been proposed which considers the interaction effects and integrates the number of selected projects, the segmentations, and the budgetary constraints into a single set of constraints. In order to solve the proposed model, a genetic algorithm and also a differential evolution algorithm are presented. Moreover, the efficiencies of these two algorithms are compared with an exact method using various numerical examples. Finally, through a case study the performance of the model is demonstrated.

Keywords: project portfolio selection; project interactions; genetic algorithms; differential evolution; operational research; budgetary segmentation; budgetary constraints.

DOI: 10.1504/IJOR.2015.065941

International Journal of Operational Research, 2015 Vol.22 No.1, pp.106 - 128

Received: 12 Jan 2013
Accepted: 03 Jun 2013
Published online: 09 May 2015 *

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