Abstract
Project selection has become crucial in the fields of science and engineering. This paper discusses the specific problem of selecting a portfolio of projects that achieves an organization's objectives without exceeding limited capital resources, especially when each project possesses vague input and output data in the selection. In this paper, a data envelopment analysis (DEA), knapsack formulation and fuzzy set theory integrated model is proposed to deal with the problem, and the model is demonstrated via a case study problem in engineering-procurement-construction (EPC) industry. Moreover, this paper applies three constraint handling techniques, which are factor-free penalty function based, to transform a constrained optimization problem into an unconstrained problem, and for the first time adopts the artificial bee colony (ABC) algorithm to search the solutions. The performances of these three constraint handling techniques with respect to the ABC algorithm are compared for the first time in this paper.
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