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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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.