Abstract
Home Health Care (HHC) services provide health care and assistance to patients at their homes according to their specific health needs. In the HHC setting, healthcare staff scheduling is a hard combinatorial problem that is concerned with the allocation of care tasks to healthcare givers at a minimal cost while considering healthcare service quality by striving to meet the time window restrictions specified by the patients. This chapter proposes two metaheuristic grouping approaches for addressing the scheduling problem; Grouping Genetic Algorithm (GGA) and Grouping Particle Swarm Optimization (GPSO). These approaches utilize the strengths of unique grouping operators, effectively and efficiently taking advantage the group structure of the problem, and providing good solutions within reasonable computation times. Illustrative computational examples are provided. Computational results show that the metaheuristic grouping approaches are promising.
| Original language | English |
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| Pages | 215-224 |
| Number of pages | 10 |
| Publication status | Published - 2014 |
| Event | International MultiConference of Engineers and Computer Scientists, IMECS 2013 under the World Congress on Engineering, WCE 2013 - London, United Kingdom Duration: 3 Jul 2013 → 5 Jul 2013 |
Conference
| Conference | International MultiConference of Engineers and Computer Scientists, IMECS 2013 under the World Congress on Engineering, WCE 2013 |
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| Country/Territory | United Kingdom |
| City | London |
| Period | 3/07/13 → 5/07/13 |
ASJC Scopus subject areas
- Computer Science (miscellaneous)