Optimization of container stowage using simulated annealing and genetic algorithms

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

Abstract

The purpose of this paper is to investigate the optimization of container stowage plan problem for a container vessel with multiple ports of call. Generally, container vessels visit many different ports on their voyage. Due to the loading and offloading at each port, finding the stowage planning for container vessel is getting more difficult for each subsequent port and also the complexity in stowage planning increases. For that reason, container stowage problem is called NP-hard problem. Genetic Algorithm and Simulated Annealing Algorithm are implemented herein to obtain the optimum solution. After finding the optimum solution from these two algorithms, the results are compared to evaluate their computational cost and efficiency.
LanguageEnglish
Title of host publicationMaritime Transportation and Harvesting of Sea Resources
Subtitle of host publicationProceedings of the 17th International Congress of the International Maritime Association of the Mediterranean
EditorsCarlos Guedes Soares, Ângelo P. Teixeira
Place of Publication[S.I.]
Pages881-886
Number of pages6
Publication statusPublished - 20 Nov 2017
Event17th International Congress of the International Maritime Association of the Mediterranean, Lisbon, Portugal, 9-11 October 2017 - Lisbon, Portugal
Duration: 9 Oct 201711 Oct 2017
Conference number: 17

Conference

Conference17th International Congress of the International Maritime Association of the Mediterranean, Lisbon, Portugal, 9-11 October 2017
Abbreviated titleIMAM 2017
CountryPortugal
CityLisbon
Period9/10/1711/10/17

Fingerprint

Simulated annealing
Containers
Genetic algorithms
Planning
Computational complexity
Costs

Keywords

  • container stowage
  • container vessels

Cite this

Yurtseven, M. A., Boulougouris, E., Turan, O., & Papadopoulos, N. (2017). Optimization of container stowage using simulated annealing and genetic algorithms. In C. G. Soares, & Â. P. Teixeira (Eds.), Maritime Transportation and Harvesting of Sea Resources: Proceedings of the 17th International Congress of the International Maritime Association of the Mediterranean (pp. 881-886). [107] [S.I.].
Yurtseven, M.A. ; Boulougouris, E. ; Turan, O. ; Papadopoulos, N. / Optimization of container stowage using simulated annealing and genetic algorithms. Maritime Transportation and Harvesting of Sea Resources: Proceedings of the 17th International Congress of the International Maritime Association of the Mediterranean. editor / Carlos Guedes Soares ; Ângelo P. Teixeira. [S.I.], 2017. pp. 881-886
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Yurtseven, MA, Boulougouris, E, Turan, O & Papadopoulos, N 2017, Optimization of container stowage using simulated annealing and genetic algorithms. in CG Soares & ÂP Teixeira (eds), Maritime Transportation and Harvesting of Sea Resources: Proceedings of the 17th International Congress of the International Maritime Association of the Mediterranean., 107, [S.I.], pp. 881-886, 17th International Congress of the International Maritime Association of the Mediterranean, Lisbon, Portugal, 9-11 October 2017, Lisbon, Portugal, 9/10/17.

Optimization of container stowage using simulated annealing and genetic algorithms. / Yurtseven, M.A.; Boulougouris, E.; Turan, O.; Papadopoulos, N.

Maritime Transportation and Harvesting of Sea Resources: Proceedings of the 17th International Congress of the International Maritime Association of the Mediterranean. ed. / Carlos Guedes Soares; Ângelo P. Teixeira. [S.I.], 2017. p. 881-886 107.

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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AB - The purpose of this paper is to investigate the optimization of container stowage plan problem for a container vessel with multiple ports of call. Generally, container vessels visit many different ports on their voyage. Due to the loading and offloading at each port, finding the stowage planning for container vessel is getting more difficult for each subsequent port and also the complexity in stowage planning increases. For that reason, container stowage problem is called NP-hard problem. Genetic Algorithm and Simulated Annealing Algorithm are implemented herein to obtain the optimum solution. After finding the optimum solution from these two algorithms, the results are compared to evaluate their computational cost and efficiency.

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Yurtseven MA, Boulougouris E, Turan O, Papadopoulos N. Optimization of container stowage using simulated annealing and genetic algorithms. In Soares CG, Teixeira ÂP, editors, Maritime Transportation and Harvesting of Sea Resources: Proceedings of the 17th International Congress of the International Maritime Association of the Mediterranean. [S.I.]. 2017. p. 881-886. 107