A Hybrid Approach to Detecting the Best Solution in Nurse Scheduling Problem

被引：3

作者：

Simic, Svetlana ^{[1
]}

Simic, Dragan ^{[2
]}

Milutinovic, Dragana ^{[1
]}

Dordevic, Jovanka ^{[3
]}

Simic, Svetislav ^{[2
]}

机构：

[1] Univ Novi Sad, Fac Med, Hajduk Veljkova 1-9, Novi Sad 21000, Serbia

[2] Univ Novi Sad, Fac Tech Sci, Trg Dositeja Obradov 6, Novi Sad 21000, Serbia

[3] Oncol Inst Vojvodina, Put Doktora Goldmana 4, Sremska Kamenica 21208, Serbia

来源：

HYBRID ARTIFICIAL INTELLIGENT SYSTEMS, HAIS 2017 | 2017年 / 10334卷

关键词：

Nurse scheduling problem; Case-based reasoning; General linear empirical model; SYSTEM;

D O I：

10.1007/978-3-319-59650-1_60

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Staff scheduling at hospitals is a widely-studied area in both, operation research and management science because of cost effectiveness that is required from hospitals. There is an interest for procedures on how to run a hospital more economically and efficiently. The goal of nurse scheduling is to minimize the cost of the staff and maximizing their preferences. This paper is focused on a new strategy based on hybrid model for detecting the best solution in nurse scheduling problem. The new proposed hybrid approach is obtained by combining case-based reasoning and general linear empirical model with arbitrary coefficients. The model is tested with original real world dataset obtained from the Oncology Institute of Vojvodina in Serbia.

引用

页码：710 / 721

页数：12

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