Authors:
Yong Shi
;
Toufik Boudouh
and
Olivier Grunder
Affiliation:
Université de Bourgogne Franche-Comté and UTBM, France
Keyword(s):
Home Health Care, Fuzzy Chance Constraint Programming, Hybrid Genetic Algorithm, Stochastic Simulation.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Artificial Intelligence
;
e-Business
;
Enterprise Information Systems
;
Industrial Engineering
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Logistics
;
Mathematical Modeling
;
Methodologies and Technologies
;
Operational Research
;
Optimization
;
OR in Health
;
Pattern Recognition
;
Routing
;
Software Engineering
;
Stochastic Optimization
;
Supply Chain Management
;
Symbolic Systems
Abstract:
Home Health Care (HHC) companies are widespread in European countries, and aim to serve patients at home to help them recover from illness and injury in a personal environment. Since transportation costs constitute one of the largest forms of expenditure in the Home Health Care industry, it is of great significance to research the optimization of the Home Health Care logistics. This paper considers the Home Health Care Routing Problem with Fuzzy Demand, which comes from the logistics practice of the home health care company. A fuzzy chance constraint programming model is proposed based on the fuzzy credibility theory, the hybrid genetic algorithm and stochastic simulation method are integrated to solve the proposed model. Firstly the uncertain constraints have been reduced to the deterministic ones, experimental results for the benchmark test problem show the good efficiency of the proposed algorithm. Then the proposed hybrid algorithm has been applied to solve the fuzzy model, the i
nfluence of the parameters to the objective function has been discussed. This research will help HHC companies to make appropriate decisions when arranging their vehicle routes.
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