S.K. Rajesh Kanna, A.D. Jaisree
This research presents an application of Ant Colony Optimization (ACO) meta-heuristic to the bin packing problem (BPP). The objective is to efficiently pack arbitrarily sized three-dimensional rectangular prismatic bins into standard-sized containers, minimizing empty space. A hybridization of the basic ant system is introduced, utilizing the behavior of artificial ants for local search, while addressing packing constraints such as placement, overlapping, shipment, and stability. The outcomes from the ants' algorithm are further optimized and translated into a user-friendly graphical format through a heuristic ant tuning algorithm. Experimental results using well-known benchmark problems indicate that this approach demonstrates improved performance and competitiveness with other evolutionary algorithms, particularly regarding computational time. This research contributes to the field by enhancing the effectiveness of ACO in BPP, providing a practical solution to a common logistical challenge.
@article{4541eb82-66b1-41fd-b89a-0ca6006cf2f7,
title={Optimization of 3D Constrained Rectangul},
author={S.K. Rajesh Kanna and A.D. Jaisree},
year={2026},
language={en}
}TY - JOUR TI - Optimization of 3D Constrained Rectangul AU - S.K. Rajesh Kanna AU - A.D. Jaisree PY - 2026 LA - en ER -
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