An implementation of Ant Colony Optimisation for solving Cutting Stock Problem

Authors:
Wendy Japutra Jap;Jofry Hadi Sutanto;Raymond Chiong
Affiliations:
Swinburne University of Technology (Sarawak Campus), Kuching, Sarawak, Malaysia;Swinburne University of Technology (Sarawak Campus), Kuching, Sarawak, Malaysia;Swinburne University of Technology (Sarawak Campus), Kuching, Sarawak, Malaysia
Venue:
ACST '08 Proceedings of the Fourth IASTED International Conference on Advances in Computer Science and Technology
Year:
2008

Citing 3
Cited 0

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Abstract

The Cutting Stock Problem (CSP) has gained a lot of attention due to its applicability in many industrial sectors. In this paper, we present an emerging nature-inspired technique, the Ant Colony Optimisation (ACO), for solving CSP. ACO uses artificial pheromone trail as the fundamental method to find new solutions. We conduct experiments with our ACO on the benchmark problems of CSP, and compare the performance of ACO with Evolutionary Programming (EP). While ACO is shown to be a feasible solution for tackling CSP, it is still unable to match EP in terms of accuracy and efficiency in most cases.