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Erschienen in:
Secure Third Party Data Clustering Using Data: Multi-User Order Preserving Encryption and Super Secure Chain Distance Matrices (Best Technical Paper) Kapitel lesen Erstes Kapitel lesen

2018 | OriginalPaper | Buchkapitel

Workforce Rostering via Metaheuristics

verfasst von : Mary Dimitropoulaki, Mathias Kern, Gilbert Owusu, Alistair McCormick

Erschienen in: Artificial Intelligence XXXV

Verlag: Springer International Publishing

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Abstract

Staff scheduling and planning in a cost effective manner has been a topic of scientific discussion for many years, driven by the need of many organisations to fully and effectively utilise their workforce to meet costumer demand and deliver service. Due to the varying nature of industry sectors, problems often require tailoring for particular business needs and types of work. This paper presents an overview of how a version of this problem was solved in a business with a large field workforce. The automation of this process has proved vital in ensuring that there is the right amount of resources rostered in on each day of the week, transforming a lengthy, manual procedure into an operation of a matter of seconds. The paper discusses how a Simulated Annealing approach was implemented, and provides a comparison of its performance versus a standard Hill Climber. We also include a detailed description of how rules and constraints were incorporated into the work, and what effect these had on rostered attendance.

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Vorheriges Kapitel Predicting Fluid Work Demand in Service Organizations Using AI Techniques
Nächstes Kapitel Incorporating Risk in Field Services Operational Planning Process
Fußnoten
1
Emphasis on specific areas to ensure targeted optimisation through the use of penalties/weights.
 
2
The cost function is dependant on the different types of soft constraints.
 
3
For example, a range of 10 on Saturday should not be considered the same as a range of 10 on any other day of the week due to the smaller number of attending resources.
 
4
A “fixed” resource simply means that they cannot change start week.
 
5
Note, some resources are only allowed certain start weeks due to constraints related to factors such as sub-cycles and consecutive Saturdays.
 
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Metadaten
Titel
Workforce Rostering via Metaheuristics
verfasst von
Mary Dimitropoulaki
Mathias Kern
Gilbert Owusu
Alistair McCormick
Copyright-Jahr
2018
Buch
Artificial Intelligence XXXV

Print ISBN: 978-3-030-04190-8

Electronic ISBN: 978-3-030-04191-5

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-3-030-04191-5_25