Data in Brief (Jun 2022)

Generating datasets for the project portfolio selection and scheduling problem

  • Kyle Robert Harrison,
  • Saber M. Elsayed,
  • Ivan L. Garanovich,
  • Terence Weir,
  • Sharon G. Boswell,
  • Ruhul A. Sarker

Journal volume & issue
Vol. 42
p. 108208

Abstract

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The article presents two variants of the project portfolio selection and scheduling problem (PPSSP). The primary objective of the PPSSP is to maximise the total portfolio value through the selection and scheduling of a subset of projects subject to various operational constraints. This article describes two recently-proposed, generalised models of the PPSSP [1,2] and proposes a set of synthetically generated problem instances for each. These datasets can be used by researchers to compare the performance of heuristic and meta-heuristic solution strategies. In addition, the Python program used to generate the problem instances is supplied, allowing researchers to generate new problem instances.

Keywords