A Knowledge-based System for Berth Allocation in a Container Terminal

Junliang He, Youfang Huang, Daofang Chang, Weimin Zhang

Abstract


Both of berth allocation and quay crane assignment are one of the most complex parts in container terminal operations, which significantly affect the operational efficiency, energy consumption and operational cost of the entire container terminal. Therefore, it is necessary to develop an efficient strategy for integrated berth allocation and quay crane assignment (BACP) from the perspective of knowledge, which aims at energy-saving and improving operational efficiency. In this paper, knowledge acquisition for BACP is initially conducted. And then, knowledge sorting process for BACP, including taxonomic tree generation and organization of acquired knowledge, is performed. After that, rules for BACP are extracted using the IF and THEN clause. Furthermore, a knowledge reasoning mechanism is designed. Finally, numerical experiments are used to illustrate the proposed knowledge-based system and verify the effectiveness and reliability.

 

DOI: http://dx.doi.org/10.11591/telkomnika.v11i5.2452


Full Text:

PDF

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

shopify stats IJEECS visitor statistics