Glass container production scheduling through hybrid multi-population based evolutionary algorithm

• Type: Article in International Scientific Journal
• Date: 2013

Authors

toledo, cfm (Author) FADEUP; arantes, md (Author) FADEUP; de oliveira, rrr (Author) FADEUP; almada-lobo, b (Author) FEUP

Journal

Title: Applied Soft Computing Journal

Vol. 13 No. 3

Pages: 1352-1364

ISSN: 1568-4946

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 27 Citations

ISI Web of Science

Scopus - 31 Citations

Other information

Authenticus ID: P-002-0AS

DOI: 10.1016/j.asoc.2012.03.074

Abstract (EN): Driven by a real-world application in the capital-intensive glass container industry, this paper provides the design of a new hybrid evolutionary algorithm to tackle the short-term production planning and scheduling problem. The challenge consists of sizing and scheduling the lots in the most cost-effective manner on a set of parallel molding machines that are fed by a furnace that melts the glass. The solution procedure combines a multi-population hierarchically structured genetic algorithm (GA) with a simulated annealing (SA), and a tailor-made heuristic named cavity heuristic (CH). The SA is applied to intensify the search for solutions in the neighborhood of the best individuals found by the GA, while the CH determines quickly values for a relevant decision variable of the problem: the processing speed of each machine. The results indicate the superior performance of the proposed approach against a state-of-the-art commercial solver, and compared to a non-hybridized multi-population GA.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 13