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An Artificial Neural Network for Berth and Quay Crane Allocation in Container Terminals

Bijlard, J.S. (2017) An Artificial Neural Network for Berth and Quay Crane Allocation in Container Terminals. Master's Thesis / Essay, Industrial Engineering and Management.

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Abstract

Cahyono, Flonk, and Jayawardhana (2015) proposed a method for solving the berth allocation problem and the quay crane allocation problem simultaneously based on the model predictive control paradigm. However, the problem with this MPC algorithm is the high calculation time. In this thesis, first the current MPC algorithm is analyzed, then an artificial neural network is implemented to speed up the calculation time and last both algorithms are compared for different time horizons. Results show a range between -0.3 to 6.6 % increase in total cost for different time horizons. Calculations times decreased from 64.52 to 1.38 seconds. Summarizing, this thesis shows the implementation of an artificial neural network for solving the berth allocation and quay crane allocation problems.

Item Type: Thesis (Master's Thesis / Essay)
Degree programme: Industrial Engineering and Management
Thesis type: Master's Thesis / Essay
Language: English
Date Deposited: 15 Feb 2018 08:27
Last Modified: 15 Feb 2018 08:27
URI: http://fse.studenttheses.ub.rug.nl/id/eprint/15072

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