Artificial Bee Colony to Solve the Berth Allocation and Crane Assignment Problem
محورهای موضوعی : production scheduling and sequencingSara SOUAINI 1 , Jamal Benhra 2 , Salma Mouatassim 3
1 - LARILE Laboratory, TEAM OSIL Hassan II University of Casablanca, Morocco
2 - LARILE Laboratory, TEAM OSIL Hassan II University of Casablanca, Morocco
3 - LARILE Laboratory, TEAM OSIL Hassan II University of Casablanca, Morocco
کلید واژه: Optimization , Scheduling , Berth Allocation , Crane Assignment , Artificial bee colony,
چکیده مقاله :
The efficient operation of container terminals relies on two crucial aspects: vessel scheduling and resource allocation. These tasks, considered NP-hard optimization problems, aim to minimize the total processing time of vessels at docks. While prior research predominantly focused on optimizing vessel arrival and departure times, recent studies emphasize the significance of addressing resource allocation challenges to enhance overall port efficiency. Recognizing this, our study employs a mathematical model to deepen understanding and elucidate inherent constraints. To effectively resolve the model, we employ the Artificial Bee Colony (ABC) algorithm. This algorithm is chosen for its efficacy in addressing scheduling problems characterized by limited identical resources, unitary processing, and non-repetitive tasks. By utilizing the mathematical model and ABC algorithm, our research aims to optimize vessel scheduling and resource allocation in container terminals. Ultimately, the goal is to minimize the total processing time of vessels at docks, thereby streamlining operations and improving port efficiency. This research contributes to the field by offering a comprehensive approach to address the intertwined issues of vessel scheduling and resource allocation. Its findings hold significance for stakeholders in maritime logistics, providing strategies to enhance service delivery and operational performance in container terminals.
The efficient operation of container terminals relies on two crucial aspects: vessel scheduling and resource allocation. These tasks, considered NP-hard optimization problems, aim to minimize the total processing time of vessels at docks. While prior research predominantly focused on optimizing vessel arrival and departure times, recent studies emphasize the significance of addressing resource allocation challenges to enhance overall port efficiency. Recognizing this, our study employs a mathematical model to deepen understanding and elucidate inherent constraints. To effectively resolve the model, we employ the Artificial Bee Colony (ABC) algorithm. This algorithm is chosen for its efficacy in addressing scheduling problems characterized by limited identical resources, unitary processing, and non-repetitive tasks. By utilizing the mathematical model and ABC algorithm, our research aims to optimize vessel scheduling and resource allocation in container terminals. Ultimately, the goal is to minimize the total processing time of vessels at docks, thereby streamlining operations and improving port efficiency. This research contributes to the field by offering a comprehensive approach to address the intertwined issues of vessel scheduling and resource allocation. Its findings hold significance for stakeholders in maritime logistics, providing strategies to enhance service delivery and operational performance in container terminals.
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