Authors:
Haneen Algethami
1
;
Dario Landa-Silva
1
and
Anna Martínez-Gavara
2
Affiliations:
1
ASAP Research Group, United Kingdom
;
2
Estadística y Investigación Operativa, Spain
Keyword(s):
Genetic Operators, Constraints Satisfaction, Scheduling and Routing Problem, Home Health Care.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Artificial Intelligence
;
e-Business
;
Enterprise Information Systems
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Logistics
;
Methodologies and Technologies
;
Operational Research
;
Optimization
;
OR in Health
;
OR in Transportation
;
Pattern Recognition
;
Routing
;
Scheduling
;
Software Engineering
;
Symbolic Systems
Abstract:
The Workforce Scheduling and Routing Problem (WSRP) is a combinatorial optimisation problem that involves scheduling and routing of workforce. Tackling this type of problem often requires handling a considerable number of requirements, including customers and workers preferences while minimising both operational costs and travelling distance. This study seeks to determine effective combinations of genetic operators combined with heuristics that help to find good solutions for this constrained combinatorial optimisation problem. In particular, it aims to identify the best set of operators that help to maximise customers and workers preferences satisfaction. This paper advances the understanding of how to effectively employ different operators within two variants of genetic algorithms to tackle WSRPs. To tackle infeasibility, an initialisation heuristic is used to generate a conflict-free initial plan and a repair heuristic is used to ensure the satisfaction of constraints. Experiments
are conducted using three sets of real-world Home Health Care (HHC) planning problem instances.
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