Baseline value specification and sensitivity analysis in multiattribute project portfolio selection

DOI10.1016/j.ejor.2014.02.009zbMath1338.91131OpenAlexW2065158617MaRDI QIDQ296608

Antti Punkka, Juuso Liesiö

Publication date: 23 June 2016

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ejor.2014.02.009

zbMATH Keywords

resource allocationdecision analysislinear-additive portfolio valuemultiattribute project portfolio selection

Mathematics Subject Classification ID

Portfolio theory (91G10)

Related Items (5)

Nonadditive Multiattribute Utility Functions for Portfolio Decision Analysis ⋮ Measurement issues in the evaluation of projects in a project portfolio ⋮ Adjustable robustness for multi-attribute project portfolio selection ⋮ Modeling project preferences in multiattribute portfolio decision analysis ⋮ Portfolio decision analysis: recent developments and future prospects

Uses Software

• QRM

Cites Work

• Scenario-based portfolio selection of investment projects with incomplete probability and utility information
• Portfolio decision analysis. Improved methods for resource allocation.
• Preference programming for robust portfolio modeling and project selection
• Robust portfolio modeling with incomplete cost information and project interdependencies
• Structuring resource allocation decisions: a framework for building multi-criteria portfolio models with area-grouped options
• Decision making with incomplete information
• Ordinal judgments in multiattribute decision analysis
• Preference programming with incomplete ordinal information
• Transparent prioritisation, budgeting and resource allocation with multi-criteria decision analysis and decision conferencing
• An Integrated Decision-Making Approach for Improving European Air Traffic Management
• Measurable Multiattribute Value Functions
• Measurable Multiattribute Value Functions for Portfolio Decision Analysis
• Scale Dependence and Ranking Intervals in Additive Value Models Under Incomplete Preference Information
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