期刊名称：iSys - Revista Brasileira de Sistemas de Informação
印刷版ISSN：1984-2902
出版年度：2014
卷号：7
期号：4
页码：60-74
语种：English
出版社：iSys - Revista Brasileira de Sistemas de Informação
摘要：This paper proposes a multiobjective heuristic search approach to support a project portfolio selection technique on scenarios with a large number of candidate projects. The original formulation for the technique requires analyzing all combinations of the candidate projects, which turns to be unfeasible when more than a few alternatives are available. We have used a multiobjective genetic algorithm to partially explore the search space of project combinations and select the most effective ones. We present an experimental study based on four real-world project selection problems that compares the results found by the genetic algorithm to those yielded by a non-systematic search procedure (random search). A second experimental study evaluates the best parameter settings to perform the heuristic search. Experimental results show evidence that the project selection technique can be used in large-scale scenarios and that the genetic algorithm presents better results than simpler search strategies.
