ITM Web Conf.
Volume 52, 2023International Conference on Connected Object and Artificial Intelligence (COCIA’2023)
|Number of page(s)||14|
|Section||Artificial Intelligence and its Application|
|Published online||08 May 2023|
Optimization Approach for Yard Crane Scheduling Problem using genetic algorithm in Container Terminals
1 National school of electricity and mechanics, Mechanical department, Casablanca, Morocco
2 National school of electricity and mechanics, Mechanical department, Casablanca, Morocco
* Corresponding author: Sanaa.email@example.com
As the core operational issue in container terminals, yard crane scheduling problem directly aﬀects the overall operation eﬃciency of port connecting highway or railway transportation and sea transportation. In practice, the scheduling of yard cranes is subject to many uncertain factors, so the scheme may be inapplicable and needs to be adjusted. From the perspective of proactive strategy, considering fluctuations in arrival time of external trucks as well as varied handling volume of yard cranes,a stochastic programming model is established in this paper to obtain a fixed scheme with the minimum expected value of yard crane makespan and total task waiting time over all the scenarios. The scheme does not require rescheduling when facing diﬀerent situations. Subsequently, two algorithms based on certain rules are proposed to obtain the yard crane operation scheme in the deterministic environment, which are taken as the basic solution inthe uncertain conditions, and then a tailored genetic algorithm is adopted to find the optimal solution with good adaptability to the uncertain scenarios. Finally, we use smallscale examples to compare the performance of algorithms in the deterministic and uncertain environment and then analyze the relationship between diﬀerent yard crane configurations and the number of tasks. Largescale experiments are performed to study the operation eﬃciency of the storage yard with diﬀerent handling volumes assigned to each yard crane.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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