Efficient heuristics to minimize the total tardiness of chemotherapy drug production and delivery
被引:0
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作者:
Alexis Robbes
论文数: 0引用数: 0
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机构:University of Tours,CHRU de Tours
Alexis Robbes
Yannick Kergosien
论文数: 0引用数: 0
h-index: 0
机构:University of Tours,CHRU de Tours
Yannick Kergosien
Virginie André
论文数: 0引用数: 0
h-index: 0
机构:University of Tours,CHRU de Tours
Virginie André
Jean-Charles Billaut
论文数: 0引用数: 0
h-index: 0
机构:University of Tours,CHRU de Tours
Jean-Charles Billaut
机构:
[1] University of Tours,CHRU de Tours
[2] LIFAT (EA 6300),undefined
[3] ERL CNRS ROOT 7002,undefined
[4] Hôpital Bretonneau,undefined
来源:
Flexible Services and Manufacturing Journal
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2022年
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34卷
关键词:
Hybrid flow shop scheduling problem;
Multi-trip vehicle routing problem;
Chemotherapy production;
Healthcare management;
Production and distribution scheduling;
Greedy randomized adaptive search procedure;
D O I:
暂无
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学科分类号:
摘要:
This study considers the production of chemotherapy drugs for cancer treatment. An important factor determining the quality of service of chemotherapy treatment is the time the patient must wait to receive his or her injection of the chemotherapy drug. Chemotherapy production and delivery are modeled as a production scheduling problem combined with a vehicle routing problem. The scheduling problem is a three-stage hybrid flow shop scheduling problem, and the routing problem is a variant of the multi-trip vehicle routing problem with due dates. The objective function is the minimization of the total time delay for chemotherapy treatment. To solve this problem, we propose several heuristic algorithms to provide quality solutions within reasonable computation times. Computational experiments are used to compare the performance of the heuristics applied to real data-based random instances.