Hybrid heuristics for the single machine scheduling problem with quadratic earliness and tardiness costs

• Type: Article in International Scientific Journal
• Date: 2012

Authors

Alok Singh (Author) Other; Jorge M S Valente (Author) FEP; Maria R A Moreira (Author) FEP

Journal

Title: International Journal of Machine Learning and Cybernetics

Vol. 3 No. 4

Pages: 327-333

ISSN: 1868-8071

Publisher: Springer Nature

Indexing

ISI Web of Knowledge - 5 Citations

Scopus - 6 Citations

Scientific classification

FOS: Natural sciences > Computer and information sciences

CORDIS: Social sciences > Economics > Management studies

Other information

Authenticus ID: P-008-72H

DOI: 10.1007/s13042-011-0067-3

Abstract (EN): In this paper we present three hybrid heuristics for the single machine scheduling problem with quadratic earliness and tardiness costs, and no machine idle time. Our heuristic is a combination of a steady-state genetic algorithm and three improvement procedures. The two computationally less expensive of these three improvement procedures are used inside the genetic algorithm to improve the schedule obtained after the application of genetic operators, whereas the more expensive one is used to improve the best solution returned by the genetic algorithm. We have compared our hybrid approaches against existing recovering beam search and genetic algorithms. The computational results show the effectiveness of our hybrid approaches. Indeed, our hybrid approaches outperformed the existing heuristics in terms of solution quality as well as running time.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 7