A hybrid genetic algorithm for the job shop scheduling problem

• Type: Article in International Scientific Journal
• Date: 2005

Authors

Goncalves, JF (Author) FEP; Mendes, JJDM (Author) Other; Resende, MGC (Author) Other

Journal

Title: European Journal of Operational Research

Vol. 167 No. 1

Pages: 77-95

ISSN: 0377-2217

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 283 Citations

ISI Web of Science

Scopus - 405 Citations

Scientific classification

FOS: Engineering and technology > Industrial biotechnology

CORDIS: Social sciences > Economics > Management studies

Other information

Authenticus ID: P-000-0FT

DOI: 10.1016/j.ejor.2004.03.012

Abstract (EN): This paper presents a hybrid genetic algorithm for the job shop scheduling problem. The chromosome representation of the problem is based on random keys. The schedules are constructed using a priority rule in which the priorities are defined by the genetic algorithm. Schedules are constructed using a procedure that generates parameterized active schedules. After a schedule is obtained a local search heuristic is applied to improve the solution. The approach is tested on a set of standard instances taken from the literature and compared with other approaches. The computation results validate the effectiveness of the proposed algorithm.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 19