Genetic Algorithm for Scheduling Optimization Considering Heterogeneous Containers: A Real-World Case Study

被引：14

作者：

Rivera, Gilberto ^{[1
]}

Cisneros, Luis ^{[1
]}

Sanchez-Solis, Patricia ^{[1
]}

Rangel-Valdez, Nelson ^{[2
]}

Rodas-Osollo, Jorge ^{[1
]}

机构：

[1] Autonomous Univ Cd Juarez, Dept Elect & Comp Engn, Cd Juarez 32315, Mexico

[2] Natl Mexican Inst Technol, Postgrad & Res Div, Madero Inst Technol, Cd Madero 89440, Tamaulipas, Mexico

来源：

AXIOMS | 2020年 / 9卷 / 01期

关键词：

scheduling problem; surgery scheduling; genetic algorithm;

D O I：

10.3390/axioms9010027

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this paper, we develop and apply a genetic algorithm to solve surgery scheduling cases in a Mexican Public Hospital. Here, one of the most challenging issues is to process containers with heterogeneous capacity. Many scheduling problems do not share this restriction; because of this reason, we developed and implemented a strategy for the processing of heterogeneous containers in the genetic algorithm. The final product was named "genetic algorithm for scheduling optimization" (GAfSO). The results of GAfSO were tested with real data of a local hospital. Said hospital assigns different operational time to the operating rooms throughout the week. Also, the computational complexity of GAfSO is analyzed. Results show that GAfSO can assign the corresponding capacity to the operating rooms while optimizing their use.

引用

页数：16

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