A Low Time-Consuming Rosters Evaluation in Personnel Scheduling Problems Based on Pattern Learning

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F13%3A00208836" target="_blank" >RIV/68407700:21230/13:00208836 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

A Low Time-Consuming Rosters Evaluation in Personnel Scheduling Problems Based on Pattern Learning

Popis výsledku v původním jazyce

Numerous (meta-)heuristics for solving personnel scheduling problems have been introduced in various papers over the last few years. In most cases, These methods consist of two usual steps: 1) generate new solutions and 2) determine their quality (cost)given by an objective function which is very computationally expensive. Our paper proposes a faster evaluation of the objective function based on the solution structure (pattern). The inspiration was found in creating a roster by a human, who is able torecognize an obviously bad roster using their own experience instead of complex computing. For this purpose, a neural network is used as a tool of pattern recognition to distinguish between good and bad solutions. The given approach is applied to the standard benchmark instances for the nurse rostering problem. We demonstrate that the proposed classifier can reduce the runtime of the scheduling algorithm in comparison with standard cost-oriented evaluation of the objective function with

Název v anglickém jazyce

A Low Time-Consuming Rosters Evaluation in Personnel Scheduling Problems Based on Pattern Learning

Popis výsledku anglicky

Numerous (meta-)heuristics for solving personnel scheduling problems have been introduced in various papers over the last few years. In most cases, These methods consist of two usual steps: 1) generate new solutions and 2) determine their quality (cost)given by an objective function which is very computationally expensive. Our paper proposes a faster evaluation of the objective function based on the solution structure (pattern). The inspiration was found in creating a roster by a human, who is able torecognize an obviously bad roster using their own experience instead of complex computing. For this purpose, a neural network is used as a tool of pattern recognition to distinguish between good and bad solutions. The given approach is applied to the standard benchmark instances for the nurse rostering problem. We demonstrate that the proposed classifier can reduce the runtime of the scheduling algorithm in comparison with standard cost-oriented evaluation of the objective function with

Druh

D - Stať ve sborníku

CEP obor

JC - Počítačový hardware a software

OECD FORD obor

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Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2013

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the 14th EU/ME workshop

ISBN

978-3-86818-049-7

ISSN

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e-ISSN

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Počet stran výsledku

6

Strana od-do

38-43

Název nakladatele

EURO - The Association of European Operational Research Societies

Místo vydání

Erkelenz

Místo konání akce

Hamburg

Datum konání akce

28. 2. 2013

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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