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Home health care problems consist of scheduling visits to home patients byhealth professionals while following a series of requirements. This paperstudies the Home Health Care Routing and Scheduling Problem, which comprises amulti-attribute vehicle routing problem with soft time windows. Additionalroute inter-dependency constraints apply for patients requesting multiplevisits, either by simultaneous visits or visits with precedence. We apply amathematical programming solver to obtain lower bounds for the problem. We alsopropose a biased random-key genetic algorithm, and we study the effects ofadditional state-of-art components recently proposed in the literature for thisgenetic algorithm. We perform computational experiment using a publiclyavailable benchmark dataset. Regarding the previous local search-based methods,we find results up to 26.1% better than those of the literature. We findimprovements from around 0.4% to 6.36% compared to previous results from asimilar genetic algorithm.

A biased random-key genetic algorithm for the home health care problem