A Multi-objective Home Health Care Fuzzy Green Vehicle Routing and Scheduling Problem with Different Types of Vehicles and Vehicle Trip Sharing StrategyA Multi-objective Home Health Care Fuzzy Green Vehicle Routing and Scheduling Problem with Different Types of Vehicles and Vehicle Trip Sharing Strategy

Abstract

Hospitals are facing problems due to the rapid growth of demand for services for ageing people, disabled people, people with fractured hips, different types of chronic diseases, mental illness patients, coma patients, etc. On account of this, the home health care service system is growing worldwide. In a natural-world scenario,  emission depends on some factors like traffic congestion, driver’s driving behaviour, and road surface quality. Therefore, these factors create  emission that are uncertain in nature. The duration of the time window is uncertain in residential healthcare due to unexpected guests arriving, household duties, daily activities, and changes in previous appointments. In this paper, duration of time window and  emission are considered as fuzzy number. This work develops a mixed-integer linear programming model for home health care service routing and scheduling with the goal of minimising the total travel distance, travel cost, visiting cost, and  emission. The Enhanced Artificial bee colony algorithm and Enhanced Mutated cuckoo search algorithm are used to solve the home health care routing and scheduling problem. Owing to the competing nature of these objectives, these two heuristic algorithms use a normalised weighted-sum aggregated approach. A computational experiment has been conducted to test the performance of heuristic algorithms for the new modified instances, which are implemented using Python 3.12. The experiment results have shown that the Enhanced Artificial bee colony algorithm is more efficient than the Enhanced Mutated cuckoo search algorithm.