Journal article

Instance space analysis for a personnel scheduling problem

Lucas Kletzander, Nysret Musliu, Kate Smith-Miles

ANNALS OF MATHEMATICS AND ARTIFICIAL INTELLIGENCE | SPRINGER | Published : 2020

Abstract

This paper considers the Rotating Workforce Scheduling Problem, and shows how the strengths and weaknesses of various solution methods can be understood by the in-depth evaluation offered by a recently developed methodology known as Instance Space Analysis. We first present a set of features aiming to describe hardness of test instances. We create a new, more diverse set of instances based on an initial instance space analysis that reveals gaps in the instance space, and offers the opportunity to generate additional instances to add diversity to the test suite. The results of three algorithms on our extended instance set reveal insights based on this visual methodology. We observe different ..

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University of Melbourne Researchers

Grants

Awarded by Australian Research Council


Funding Acknowledgements

Financial support from the Austrian Federal Ministry for Digital and Economic Affairs and the National Foundation for Research, Technology and Development, and the Australian Research Council under grant FL140100012, is gratefully acknowledged.