A Temporal Knapsack Approach to Defence Portfolio Selection

Gregory Calbert, Terence Weir, Ivan L. Garanovich, Carlos C. Carlos

Research output: A Conference proceeding or a Chapter in BookChapterpeer-review

1 Citation (Scopus)


In this chapter we describe the origins and mathematics used in the development of the New Investments to Risked Options (NITRO) portfolio selection tool. This tool was used by the Australian Department of Defence in 2019 for a major review of Australia’s military force structure called the Force Structure Plan 2020. This is a strategic decision making process that specifies the requirements for the future force structure and identifies, selects, and schedules projects to satisfy those requirements. In order to satisfy organisational needs, the tool was implemented in Microsoft Excel® using the What’sBest!® optimisation add-in. In this chapter we provide background on the portfolio optimisation problem in Defence. We discuss the challenges of implementing a project portfolio selection and scheduling tool in the Excel® environment along with simple approaches to the visualisation of optimised portfolios. We examine the performance differences between this tool and other commercial solvers. We also analyse the trade-off of using relaxed versus integer decision variables and the use of budget slack on the portfolio selection. We conclude by discussing current portfolio optimisation issues and challenges, along with the viability of the Excel® environment for Defence portfolio selection.

Original languageEnglish
Title of host publicationAdaptation, Learning, and Optimization
EditorsKyle Robert Harrison, Saber Elsayed, Ivan Leonidovich Garanovich, Terence Weir, Sharon G. Boswell, Ruhul Amin Sarker
Place of PublicationSwitzerland
Number of pages33
ISBN (Electronic)9783030883157
ISBN (Print)9783030883140
Publication statusPublished - 2021
Externally publishedYes

Publication series

NameAdaptation, Learning, and Optimization
ISSN (Print)1867-4534
ISSN (Electronic)1867-4542


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