Journal
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
Volume 112, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.engappai.2022.104771
Keywords
Project selection and scheduling; Heuristic; Meta-heuristic; Memetic algorithm; Hybrid algorithm
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Funding
- Australian Department of Defence, Defence Science and Technology Project [RG191353]
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This article proposes a novel model for project portfolio selection and scheduling problem (PPSSP) that can handle multiple groups of projects in real-world scenarios. It also presents three hybrid meta-heuristic algorithms to provide high-quality solutions.
A common problem faced by organizations is how to select and schedule an optimal portfolio of projects subject to various constraints, such as a limited budget. This problem is known as the project portfolio selection and scheduling problem (PPSSP). Despite the widespread nature of this problem, no existing model adequately addresses a sufficient set of characteristics that arise in real-world problems. One contribution of this article is the proposal of a novel, practical class of PPSSP that consists of multiple groups of projects, proposed by different sections of a major organization. The proposed problem can be considered as a generalized PPSSP given that many specific PPSSPs reported in the literature can be generated by relaxing certain constraints. As this is a novel formulation, existing algorithms cannot ensure high-quality solutions to this problem. Thus, a further contribution of this article is the design of three hybrid meta-heuristic algorithms based on a custompurpose heuristic and local search operator. A case problem, inspired by future force design (FFD) in the Australian Defence Force (ADF), is presented to exemplify the applicability of this model to a real-world problem. Results indicate that the obtained solutions are of acceptable quality for implementation.
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