Container vessel stowage plan using genetic, hill-climbing and simulated annealing algorithms

Yurtseven, Mehmet Ali and Boulougouris, Evangelos and Turan, Osman; Kujala, Pentti and Lu, Liangliang, eds. (2018) Container vessel stowage plan using genetic, hill-climbing and simulated annealing algorithms. In: Marine Design XIII. CRC Press, FIN. ISBN 9781138541870

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Abstract

Container vessel stowage is vital for reducing extra cost and the vessel’s turn-around time in ports. Several studies have been conducted to be able to solve this problem. However, this problem has not been dealt with completely due to container stowage problem is complex problem which is literally considered as a NP-hard problem. Hence, the principal objective of this study is to find optimal container stowage plan for container vessel calling at multiple ports. Algorithms are the most widely-used methods for finding optimal solution in container vessel stowage problem. In this study, Genetic, Hill-Climbing and Simulated Annealing algorithm are implemented considering same size and two different types of containers (refrigerated and standard containers). After finding the numerical test results from these three algorithms, the effectiveness of the algorithms for the problem are evaluated.

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  Item type:	Book Section
  ID code:	64253
  Dates:	Date Event 11 June 2018 Published 31 October 2017 Accepted
  Notes:	This is an Accepted Manuscript of a book chapter published by Routledge/CRC Press in Marine Design XIII : Proceedings of the 13th International Marine Design Conference (IMDC 2018), June 10-14, 2018, Helsinki, Finland, on 11/06/2018, available online https://www.routledge.com/Marine-Design-XIII-Proceedings-of-the-13th-International-Marine-Design/Kujala-Lu/p/book/9781138541870
  Subjects:	Naval Science > Naval architecture. Shipbuilding. Marine engineering
  Department:	Faculty of Engineering > Naval Architecture, Ocean & Marine Engineering
  Depositing user:	Pure Administrator
  Date deposited:	05 Jun 2018 14:09
  Last modified:	18 Apr 2024 00:06
  Related URLs:	Event Publisher
  URI:	https://strathprints.strath.ac.uk/id/eprint/64253