<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The objective of this article is to provide an in-depth exploration of the complex task of container storage at seaports, a problem characterized as one of the challenging NP (Non-Deterministic Polynomial time) problems. Seaports are faced with the dilemma of accommodating a finite number of containers due to the constrained surface area available, making the management of container storage operations a formidable task.</p>
<p>To address this challenge, the present study leverages a meta-heuristic approach aimed at identifying an optimal storage plan for containers within a storage area. This approach is informed by insights drawn from bat swarm intelligence, commonly known as the Bat Algorithm. By integrating principles from this nature-inspired algorithm, the authors seek to develop a robust solution for optimizing container storage strategies in seaports. This approach takes into account several critical constraints, including container travel distances and considerations related to container type and departure dates.</p>
</abstract>

The objective of this article is to provide an in-depth exploration of the complex task of container storage at seaports, a problem characterized as one of the challenging NP (Non-Deterministic Polynomial time) problems. Seaports are faced with the dilemma of accommodating a finite number of containers due to the constrained surface area available, making the management of container storage operations a formidable task.
To address this challenge, the present study leverages a meta-heuristic approach aimed at identifying an optimal storage plan for containers within a storage area. This approach is informed by insights drawn from bat swarm intelligence, commonly known as the Bat Algorithm. By integrating principles from this nature-inspired algorithm, the authors seek to develop a robust solution for optimizing container storage strategies in seaports. This approach takes into account several critical constraints, including container travel distances and considerations related to container type and departure dates.

Enhancing Transportation Efficiency with Optimal Container Placement Using the Bat Algorithm

Transport and Telecommunication Journal

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

The objective of this article is to provide an in-depth exploration of the complex task of container storage at seaports, a problem characterized as one of the...

Enhancing Transportation Efficiency with Optimal Container Placement Using the Bat Algorithm

Publié en ligne: 23 avr. 2024

Pages: 200 - 208

DOI: https://doi.org/10.2478/ttj-2024-0015

Mots clés
Storage area, container, port, stack, container placement problem, optimization, bio-inspired method, the bat algorithm

© 2024 Yachba Khadidja et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Enhancing Transportation Efficiency with Optimal Container Placement Using the Bat Algorithm

Publié en ligne: 23 avr. 2024

Pages: 200 - 208

DOI: https://doi.org/10.2478/ttj-2024-0015

Mots clésStorage area, container, port, stack, container placement problem, optimization, bio-inspired method, the bat algorithm

© 2024 Yachba Khadidja et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Mots clés
Storage area, container, port, stack, container placement problem, optimization, bio-inspired method, the bat algorithm