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A study of genetic operators for the Workforce Scheduling and Routing Problem

Algethami, Haneen; Landa-Silva, Dario

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Authors

Haneen Algethami

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DARIO LANDA SILVA DARIO.LANDASILVA@NOTTINGHAM.AC.UK
Professor of Computational Optimisation



Abstract

The Workforce Scheduling and Routing Problem (WSRP) is concerned with planning visits of qualified workers to different locations to perform a set of tasks, while satisfying each task time-window plus additional requirements such as customer/workers preferences. This type of mobile workforce scheduling problem arises in many real-world operational scenarios. We investigate a set of genetic operators including problem-specific and well-known generic operators used in related problems. The aim is to conduct an in-depth analysis on their performance on this very constrained scheduling problem. In particular, we want to identify genetic operators that could help to minimise the violation of customer/workers preferences. We also develop two cost-based genetic operators tailored to the WSRP. A Steady State Genetic Algorithm (SSGA) is used in the study and experiments are conducted on a set of problem instances from a real-world Home Health Care scenario (HHC). The experimental analysis allows us to better understand how we can more effectively employ genetic operators to tackle WSRPs.

Citation

Algethami, H., & Landa-Silva, D. (2015). A study of genetic operators for the Workforce Scheduling and Routing Problem.

Conference Name 11th Metaheuristics International Conference (MIC 2015)
End Date Jun 10, 2015
Publication Date Jun 10, 2015
Deposit Date Jan 21, 2016
Publicly Available Date Jan 21, 2016
Peer Reviewed Peer Reviewed
Keywords Personnel Scheduling, Genetic Operators, Evolutionary Algorithms
Public URL https://nottingham-repository.worktribe.com/output/754689
Related Public URLs http://www.lifl.fr/MIC2015/index.html

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