A hybrid genetic algorithm for a home health care routing problem with time window and fuzzy demand

2017 ◽  
Vol 72 ◽  
pp. 160-176 ◽  
Author(s):  
Yong Shi ◽  
Toufik Boudouh ◽  
Olivier Grunder
Keyword(s):  
Genetic Algorithm ◽  
Health Care ◽  
Home Health Care ◽  
Time Window ◽  
Hybrid Genetic Algorithm ◽  
Home Health ◽  
Routing Problem ◽  
Fuzzy Demand

scholarly journals Randomized and Generated Instances Fitting with the Home Health Care Problem Subjected to Certain Constraints

2021 ◽  
Vol 11 (8) ◽  
pp. 3346
Author(s):  
Colin Huvent ◽  
Caroline Gagné ◽  
Aymen Sioud
Keyword(s):  
Health Care ◽  
Home Health Care ◽  
Hospital Cost ◽  
Time Window ◽  
Developed Countries ◽  
Home Health ◽  
Precedence Constraints ◽  
Social Organizations ◽  
Health Support ◽  
Time Window Constraints

Home Health Care (HHC) is a worldwide issue. It focuses on how medical and social organizations of different countries handle providing patients with health support at home. In most developed countries, reducing hospital cost constitutes a main objective. It is important to research the improvement of HHC logistics. This paper addressed the generation and development of a benchmark properly fitting different constraints of the HCC problem. Consequently, a generator was proposed dealing with all kinds of constraints such as time window constraints, workload constraints, synchronization, and precedence constraints. This generator allows researchers to validate and compare solving methods on a common dataset regardless of confidentiality issues. We validated our generator by firstly creating a common benchmark available for researchers and secondly by proposing a set of instances and a solving method based on an HHC problem found in the literature.

A bi-objective green home health care routing problem

2018 ◽  
Vol 200 ◽  
pp. 423-443 ◽  
Author(s):  
Amir Mohammad Fathollahi-Fard ◽  
Mostafa Hajiaghaei-Keshteli ◽  
Reza Tavakkoli-Moghaddam
Keyword(s):  
Health Care ◽  
Home Health Care ◽  
Home Health ◽  
Routing Problem
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