Volume 37, Issue 2 (IJIEPR- In Progress 2026)                   IJIEPR 2026, 37(2): 14-33 | Back to browse issues page

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Guangul F M, Chala G T, Chandra S. A hybrid AHP–SMART–ILP Framework for pProject Portfolio Selection: Evidence From a Developing Economy. IJIEPR 2026; 37 (2) :14-33
URL: http://ijiepr.iust.ac.ir/article-1-2018-en.html
A hybrid AHP–SMART–ILP Framework for pProject Portfolio Selection: Evidence From a Developing Economy
Fiseha Mekonnen Guangul1 , Girma Tadesse Chala2 , Subhash Chandra3
1- Mechanical Engineering Department, De Montfort University Dubai, Internet City Dubai, Building 12, Dubai, 501870, United Arab Emirates , fiseha@dmu.ac.uk
2- Department of Manufacturing Technology, FTVETI, Addis Ababa, Ethiopia
3- International College of Engineering and Management, P.O. Box 2511, P.C. 111, Muscat, Oman
Abstract:   (1387 Views)
Strategic investment decisions across multiple projects require a systematic assessment of extensive quantitative and qualitative data, especially under conditions of resource constraints and uncertainty. Traditional single-project appraisal methods often fail to identify optimal portfolios aligned with organizational goals. This study presents a hybrid project portfolio selection framework integrating the Analytic Hierarchy Process (AHP), Simple Multi-Attribute Rating Technique (SMART), and 0–1 Integer Linear Programming (ILP) to enhance decision-making clarity and robustness. The framework employs a hierarchical structure, utilizing a comprehensive set of technical, commercial, socio-economic, financial, investment, and institutional criteria. AHP establishes consistent relative weights from expert judgments, while SMART scores candidate projects, generating aggregated scores that inform an ILP optimization model aimed at maximizing portfolio utility while adhering to budget constraints, mandatory project conditions, and interdependencies. Validation is performed using real data from an Endowment Corporate Office in Ethiopia, accounting for ongoing and prospective projects under varying demand scenarios. Scenario and sensitivity analyses reveal how variations in demand and criterion weights affect project rankings and portfolio composition, alongside an assessment of portfolio risk via variance and standard deviation. The hybrid AHP–SMART–ILP approach effectively considers both tangible and intangible objectives, achieving stable portfolios that address investment complexities and interdependencies.
Keywords: Project portfolio optimization, Analytical hierarchy process, Multi-criteria decision making, Multi-attribute rating technique, 0–1 Integer programming, Developing economies
Full-Text [PDF 1072 kb]   (40 Downloads)    
Type of Study: Research | Subject: Project scheduling and Management, Portfolio Optimization, Financial Machine Learning, Applied Operations Research, Reli
Received: 2024/04/13 | Accepted: 2026/01/7 | Published: 2026/06/20
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