Shipping schedule-oriented production planning using genetic algorithm

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25530%2F15%3A39900891" target="_blank" >RIV/00216275:25530/15:39900891 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-319-21206-7_20" target="_blank" >http://dx.doi.org/10.1007/978-3-319-21206-7_20</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-21206-7_20" target="_blank" >10.1007/978-3-319-21206-7_20</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Shipping schedule-oriented production planning using genetic algorithm

Popis výsledku v původním jazyce

This paper presents a modified genetic algorithm for the production planning problem solving while distribution of the products to the customers is considered. The aim of the optimization task is to minimize objective function composed of the joint costsof production (manufacturing line rearrangement minimization), transportation (delivery route minimization) and holding (shipping date optimization) while all the customers' orders are satisfied within the defined production horizon. This class of problems is considered as a NP-hard combinatorial problem and it is not possible to solve it analytically for larger input values. Thus, the stochastic procedure is presented in this paper. This procedure, which is based on the genetic algorithm, respects allthe components of the objective function and provides acceptable solution in reasonable time. The experiments with real data show, that presented procedure provides the same or (in most cases) better solution than algorithms commonly use

Název v anglickém jazyce

Shipping schedule-oriented production planning using genetic algorithm

Popis výsledku anglicky

This paper presents a modified genetic algorithm for the production planning problem solving while distribution of the products to the customers is considered. The aim of the optimization task is to minimize objective function composed of the joint costsof production (manufacturing line rearrangement minimization), transportation (delivery route minimization) and holding (shipping date optimization) while all the customers' orders are satisfied within the defined production horizon. This class of problems is considered as a NP-hard combinatorial problem and it is not possible to solve it analytically for larger input values. Thus, the stochastic procedure is presented in this paper. This procedure, which is based on the genetic algorithm, respects allthe components of the objective function and provides acceptable solution in reasonable time. The experiments with real data show, that presented procedure provides the same or (in most cases) better solution than algorithms commonly use

Druh

D - Stať ve sborníku

CEP obor

BB - Aplikovaná statistika, operační výzkum

OECD FORD obor

—

Projekt

<a href="/cs/project/EE2.3.30.0058" target="_blank" >EE2.3.30.0058: Rozvoj kvalitních vědeckovýzkumných týmů na Univerzitě Pardubice</a><br>

Návaznosti

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

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název statě ve sborníku

Intelligent Data Analysis and Applications: Proceedings of the Second Euro-China Conference on Intelligent Data Analysis and Applications. ECC 2015

ISBN

978-3-319-21205-0

ISSN

2194-5357

e-ISSN

—

Počet stran výsledku

11

Strana od-do

225-235

Název nakladatele

Springer

Místo vydání

Heidelberg

Místo konání akce

Ostrava

Datum konání akce

29. 6. 2015

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000365130300020