Appointment sequencing: why the smallest-variance-first rule may not be optimal
type: Item
instance of: scholarly article
title: Appointment sequencing: why the smallest-variance-first rule may not be optimal
zbMATH Open document ID: 1394.90323
author: Qingxia Kong
author: Chung-Yee Lee
author: Chung-Piaw Teo
author: Zhichao Zheng
published in: European Journal of Operational Research
publication date: 2018-05-24T00:00:00Z
full work available at URL: https://ink.library.smu.edu.sg/lkcsb_research/4474
Mathematics Subject Classification ID: 90B36
Mathematics Subject Classification ID: 90B35
Mathematics Subject Classification ID: 90B22
Mathematics Subject Classification ID: 90B70
Mathematics Subject Classification ID: 90C10
zbMATH DE Number: 6872165
zbMATH Keywords: OR in health services
zbMATH Keywords: appointment sequencing
zbMATH Keywords: smallest-variance-first rule
zbMATH Keywords: stochastic ordering
describes a project that uses: YALMIP
MaRDI profile type: Publication
OpenAlex ID: W254988821
cites work: Appointment scheduling with discrete random durations
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cites work: Q4301147
cites work: Sequential clinical scheduling with service criteria
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cites work: Sequencing and scheduling \(N\) customers for a stochastic server
DOI: 10.1016/J.EJOR.2016.06.004
description: scientific article; zbMATH DE number 6872165