A multiobjective evolutionary approach for linearly constrained project selection under uncertainty
| Autor: | Jeffrey L. Ringuest, Andrés L. Medaglia, Samuel B. Graves |
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| Rok vydání: | 2007 |
| Předmět: |
Mathematical optimization
Information Systems and Management General Computer Science Computer science Evolutionary algorithm Efficient frontier Context (language use) Management Science and Operations Research Multi-objective optimization Industrial and Manufacturing Engineering Capital budgeting Modeling and Simulation Genetic algorithm Portfolio Resource allocation Project portfolio management |
| Zdroj: | European Journal of Operational Research. 179:869-894 |
| ISSN: | 0377-2217 |
| DOI: | 10.1016/j.ejor.2005.03.068 |
| Popis: | In the project selection problem a decision maker is required to allocate limited resources among an available set of competing projects. These projects could arise, although not exclusively, in an R&D, information technology or capital budgeting context. We propose an evolutionary method for project selection problems with partially funded projects, multiple (stochastic) objectives, project interdependencies (in the objectives), and a linear structure for resource constraints. The method is based on posterior articulation of preferences and is able to approximate the efficient frontier composed of stochastically nondominated solutions. We compared the method with the stochastic parameter space investigation method (PSI) and illustrate it by means of an R&D portfolio problem under uncertainty based on Monte Carlo simulation. |
| Databáze: | OpenAIRE |
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