Job Shop Scheduling Problem with Heuristic Genetic Programming Operators

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F15%3APU111042" target="_blank" >RIV/00216305:26220/15:PU111042 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/7095307" target="_blank" >https://ieeexplore.ieee.org/document/7095307</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/SPIN.2015.7095307" target="_blank" >10.1109/SPIN.2015.7095307</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Job Shop Scheduling Problem with Heuristic Genetic Programming Operators

Popis výsledku v původním jazyce

This paper introduces an optimization algorithm for job shop scheduling problem in logistic warehouses. The algorithm is based on genetic programming and uses parallel processing. For better performance a new optimization method called "priority rules" was proposed. We found out that the three proposed priority rules help algorithm to prevent stuck in the local optima and get better results from genetic programming optimization. Algorithm was tested with batch of tests based on data from real warehouse and with synthetic tests generated randomly (inspired by the real world scenarios). The results indicate interesting reduction of time that is necessary to fulfill all tasks in warehouses, reduction in number of collisions and better optimization performance.

Název v anglickém jazyce

Job Shop Scheduling Problem with Heuristic Genetic Programming Operators

Popis výsledku anglicky

This paper introduces an optimization algorithm for job shop scheduling problem in logistic warehouses. The algorithm is based on genetic programming and uses parallel processing. For better performance a new optimization method called "priority rules" was proposed. We found out that the three proposed priority rules help algorithm to prevent stuck in the local optima and get better results from genetic programming optimization. Algorithm was tested with batch of tests based on data from real warehouse and with synthetic tests generated randomly (inspired by the real world scenarios). The results indicate interesting reduction of time that is necessary to fulfill all tasks in warehouses, reduction in number of collisions and better optimization performance.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20201 - Electrical and electronic engineering

Projekt

<a href="/cs/project/FR-TI4%2F151" target="_blank" >FR-TI4/151: Výzkum a vývoj technologie pro detekci emocí v nestrukturovaných datech</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

2015 2nd International Conference on Signal Processing and Integrated Networks (SPIN)

ISBN

978-1-4799-5990-7

ISSN

—

e-ISSN

—

Počet stran výsledku

6

Strana od-do

702-707

Název nakladatele

Neuveden

Místo vydání

Noida, Delhi-NCR, India

Místo konání akce

Dept. of ECE, ASET, Amity University, Sector-125

Datum konání akce

19. 2. 2015

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000382970300134