A Stochastic-Integer Programming Approach to Tactical Fixed Interval Scheduling Problems

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F17%3A10363519" target="_blank" >RIV/00216208:11320/17:10363519 - 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 Stochastic-Integer Programming Approach to Tactical Fixed Interval Scheduling Problems

Popis výsledku v původním jazyce

Fixed interval scheduling (FIS) problems arise in many areas of economics and industry where jobs with processing intervals known in advance are assigned to available machines with forbidden preemption. A special case of such problems appears in the personnel task scheduling where the decision maker (manager) is looking for a minimal number of workers to cover all prescribed shifts. This problem can be classified as a tactical fixed interval scheduling. In this paper, we focus on scheduling of jobs with uncertain processing intervals where the finishing times are modelled as random variables with a known probability distribution. We provide a stochastic integer programming formulation with a joint chance constraint which ensures the reliability of the resulting schedule. We propose an iterative decomposition algorithm for a reformulation where the partial operational FIS problems can be solved as the min-cost network flow problems. The performance of the algorithm is verified on simulated instances.

Název v anglickém jazyce

A Stochastic-Integer Programming Approach to Tactical Fixed Interval Scheduling Problems

Popis výsledku anglicky

Fixed interval scheduling (FIS) problems arise in many areas of economics and industry where jobs with processing intervals known in advance are assigned to available machines with forbidden preemption. A special case of such problems appears in the personnel task scheduling where the decision maker (manager) is looking for a minimal number of workers to cover all prescribed shifts. This problem can be classified as a tactical fixed interval scheduling. In this paper, we focus on scheduling of jobs with uncertain processing intervals where the finishing times are modelled as random variables with a known probability distribution. We provide a stochastic integer programming formulation with a joint chance constraint which ensures the reliability of the resulting schedule. We propose an iterative decomposition algorithm for a reformulation where the partial operational FIS problems can be solved as the min-cost network flow problems. The performance of the algorithm is verified on simulated instances.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10103 - Statistics and probability

Projekt

<a href="/cs/project/GBP402%2F12%2FG097" target="_blank" >GBP402/12/G097: DYME-Dynamické modely v ekonomii</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2017

Kód důvěrnosti údajů

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

Název statě ve sborníku

35TH INTERNATIONAL CONFERENCE MATHEMATICAL METHODS IN ECONOMICS (MME 2017)

ISBN

978-80-7435-678-0

ISSN

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e-ISSN

neuvedeno

Počet stran výsledku

6

Strana od-do

78-83

Název nakladatele

University of Hradec Králové

Místo vydání

Hradec Králové

Místo konání akce

Hradec Králové, Czech Republic

Datum konání akce

13. 9. 2017

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000427151400014