Solution Representations for Job Shop... (final draft).pdf (200.74 kB)
Solution representation for job shop scheduling problems in ant colony optimisation
conference contribution
posted on 2023-05-23, 09:33 authored by Erin MontgomeryErin Montgomery, Fayad, C, Petrovic, SProduction scheduling problems such as the job shop consist of a collection of operations (grouped into jobs) that must be scheduled for processing on different machines. Typical ant colony optimisation applications for these problems generate solutions by constructing a permutation of the operations, from which a deterministic algorithm can generate the actual schedule. This paper considers an alternative approach in which each machine is assigned a dispatching rule, which heuristically determines the order of operations on that machine. This representation creates a substantially smaller search space that likely contains good solutions. The performance of both approaches is compared on a real-world job shop scheduling problem in which processing times and job due dates are modelled with fuzzy sets. Results indicate that the new approach produces better solutions more quickly than the traditional approach.
History
Publication title
Proceedings of the Fifth International Workshop on Ant Colony Optimization and Swarm Intelligence (ANTS 2006)Volume
4150Editors
M Dorigo, LM Gambardella, M Birattari, A Martinoli, R Poli, T StutzlePagination
484-491ISBN
9783540384823Department/School
School of Information and Communication TechnologyPublisher
Springer-VerlagPlace of publication
BerlinEvent title
Fifth International Workshop on Ant Colony Optimization and Swarm Intelligence (ANTS 2006)Event Venue
Brussels, BelgiumDate of Event (Start Date)
2006-09-04Date of Event (End Date)
2006-09-07Rights statement
Copyright 2006 Springer-Verlag Berlin HeidelbergRepository Status
- Open