Detail publikace

Job Shop Scheduling Problem with Heuristic Genetic Programming Operators

POVODA, L. BURGET, R. MAŠEK, J. DUTTA, M.

Originální název

Job Shop Scheduling Problem with Heuristic Genetic Programming Operators

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

Process planning; job shop; warehouse optimization; heuristic operators; priority rules

Autoři

POVODA, L.; BURGET, R.; MAŠEK, J.; DUTTA, M.

Rok RIV

2015

Vydáno

19. 2. 2015

Místo

Noida, Delhi-NCR, India

ISBN

978-1-4799-5990-7

Kniha

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

Strany od

702

Strany do

707

Strany počet

6

URL

https://ieeexplore.ieee.org/document/7095307

BibTex

@inproceedings{BUT110193,
  author="Lukáš {Povoda} and Radim {Burget} and Jan {Mašek} and Malay Kishore {Dutta}",
  title="Job Shop Scheduling Problem with Heuristic Genetic Programming Operators",
  booktitle="2015 2nd International Conference on Signal Processing and Integrated Networks (SPIN)",
  year="2015",
  pages="702--707",
  address="Noida, Delhi-NCR, India",
  doi="10.1109/SPIN.2015.7095307",
  isbn="978-1-4799-5990-7",
  url="https://ieeexplore.ieee.org/document/7095307"
}