JIT single machine scheduling problem with periodic preventive maintenance

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F16%3A10240763" target="_blank" >RIV/61989100:27510/16:10240763 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1007/s40092-016-0147-9" target="_blank" >https://doi.org/10.1007/s40092-016-0147-9</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s40092-016-0147-9" target="_blank" >10.1007/s40092-016-0147-9</a>

Jazyk výsledku

angličtina

Název v původním jazyce

JIT single machine scheduling problem with periodic preventive maintenance

Popis výsledku v původním jazyce

This article investigates a JIT single machine scheduling problem with a periodic preventive maintenance. Also to maintain the quality of the products, there is a limitation on the maximum number of allowable jobs in each period. The proposed bi-objective mixed integer model minimizes total earliness-tardiness and makespan simultaneously. Due to the computational complexity of the problem, multi-objective particle swarm optimization (MOPSO) algorithm is implemented. Also, as well as MOPSO, two other optimization algorithms are used for comparing the results. Eventually, Taguchi method with metrics analysis is presented to tune the algorithms&apos; parameters and a multiple criterion decision making technique based on the technique for order of preference by similarity to ideal solution is applied to choose the best algorithm. Comparison results confirmed the supremacy of MOPSO to the other algorithms. (C) 2016, The Author(s).

Název v anglickém jazyce

JIT single machine scheduling problem with periodic preventive maintenance

Popis výsledku anglicky

This article investigates a JIT single machine scheduling problem with a periodic preventive maintenance. Also to maintain the quality of the products, there is a limitation on the maximum number of allowable jobs in each period. The proposed bi-objective mixed integer model minimizes total earliness-tardiness and makespan simultaneously. Due to the computational complexity of the problem, multi-objective particle swarm optimization (MOPSO) algorithm is implemented. Also, as well as MOPSO, two other optimization algorithms are used for comparing the results. Eventually, Taguchi method with metrics analysis is presented to tune the algorithms&apos; parameters and a multiple criterion decision making technique based on the technique for order of preference by similarity to ideal solution is applied to choose the best algorithm. Comparison results confirmed the supremacy of MOPSO to the other algorithms. (C) 2016, The Author(s).

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

OECD FORD obor

50204 - Business and management

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2016

Kód důvěrnosti údajů

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

Název periodika

Journal of industrial engineering international

ISSN

1735-5702

e-ISSN

—

Svazek periodika

12

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

12

Strana od-do

299-310

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-84979658622