Solving a novel multi-divisional project portfolio selection and scheduling problem. (June 2022)

• Record Type: Journal Article
• Authors: Harrison, Kyle Robert; Elsayed, Saber M.; Weir, Terence; Garanovich, Ivan L.; Boswell, Sharon G.; Sarker, Ruhul A.
• Is Part Of: Engineering applications of artificial intelligence. Volume 112(2022)
• Publication Date: 2022-06
• Subjects: Project selection and scheduling -- Heuristic -- Meta-heuristic -- Memetic algorithm -- Hybrid algorithm; Engineering -- Data processing -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Ingénierie -- Informatique -- Périodiques; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; Artificial intelligence; Engineering -- Data processing; Expert systems (Computer science); Periodicals; 620.00285
• DOI: 10.1016/j.engappai.2022.104771
• Languages: English
• ISSNs: 0952-1976

Abstract

Abstract: 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 custom-purpose 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.