Titlebook: Evolutionary and Memetic Computing for Project Portfolio Selection and Scheduling; Kyle Robert Harrison,Saber Elsayed,Ruhul Amin Sark Book

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1867-4534 known that the PPSSP is an NP-hard problem and, thus, there is no known polynomial-time algorithm for this problem. Despite the complexity associated with solving the PPSSP, many traditional approaches to this978-3-030-88317-1978-3-030-88315-7Series ISSN 1867-4534 Series E-ISSN 1867-4542

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Book 2022, and deep uncertainty regarding project costs, benefits, and completion times..It is well known that the PPSSP is an NP-hard problem and, thus, there is no known polynomial-time algorithm for this problem. Despite the complexity associated with solving the PPSSP, many traditional approaches to this

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https://doi.org/10.1007/978-981-99-6167-2ptimization models. Depending on the degree of the estimation error of these input parameters, the optimization results may be lower than the results of the 1/N trading strategy. Robust optimization, fuzzy logic, and prediction are examples of techniques used to reduce estimation errors. Regarding s

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Evolutionary and Memetic Computing for Project Portfolio Selection and Scheduling: An Introduction, portfolio selection and scheduling problem (PPSSP). In nearly all cases, a budgetary constraint limits the number of projects that can be selected. Furthermore, complex operational constraints are often present as well. Hence, the selection of the optimal set of projects is a challenging task, whic