A JSSP Solution for Production Planning Optimization Combining Industrial Engineering and Evolutionary Algorithms

Sašo Sršen1 and Marjan Mernik1

  1. University of Maribor, Faculty of Electrical Engineering and Computer Science
    Koroška cesta 46, 2000 Maribor, Slovenia
    saso.srsen@student.um.si, marjan.mernik@um.si

Abstract

A Job Shop Scheduling Problem (JSSP), where p processes and n jobs should be processed on m machines so that the total completion time is minimal, is a well-known problem with many industrial applications. Many researchers focus on the JSSP classification and algorithms that address the different JSSP classes. In this research work, the production times, a very well-known theme covered in Industrial Engineering (IE), are integrated into an Evolutionary Algorithm (EA) to solve real-world JSSP problems. Since a drawback of classical IE is a manual determination of the technological times, an Internet of Things (IoT) architecture is proposed as a possible solution.

Key words

JSSP, genetic algorithms, industrial engineering, internet of things

Digital Object Identifier (DOI)

https://doi.org/10.2298/CSIS201009058S

Publication information

Volume 18, Issue 1 (January 2021)
Year of Publication: 2021
ISSN: 2406-1018 (Online)
Publisher: ComSIS Consortium

Full text

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How to cite

Sršen, S., Mernik, M.: A JSSP Solution for Production Planning Optimization Combining Industrial Engineering and Evolutionary Algorithms. Computer Science and Information Systems, Vol. 18, No. 1, 349–378. (2021), https://doi.org/10.2298/CSIS201009058S