Comparative Analysis of Linear and Non-Linear Programming Techniques for the Optimization of Ship-Machinery Systems

Enrico Baldasso*, Mia Elg, Fredrik Haglind, Francesco Baldi

*Corresponding author for this work

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The selection of a proper machinery system is one of the primary decisions to be taken during the ship-design phase. Nonetheless, this selection is made challenging by the presence of a variety of alternatives, and by the limited data availability at the early stages of the design phase. An optimization framework is presented in this paper, supporting decision making at the earliest stages of the ship-design process. The framework is suitable to perform the screening and the selection of optimal machinery configurations for a predefined ship operational profile, and it includes both linear and non-linear optimization routines. The results of the linear and the non-linear approaches are compared, and indications on what conditions are the most suitable for the application of one or the other approach are provided. Both approaches are tested for two case studies, a bulk carrier and a small cruise ship. The results indicate that both optimization approaches lead to the same layout of the machinery system, but to slightly different unit scheduling. This suggests that the use of the linear approach is suitable for design purposes, but less appropriate for operational optimization. In addition, the findings of the work suggest that the trade-off between fuel consumption and volume of the engines should be considered when selecting the machinery system for a ship.
Original languageEnglish
Article number403
JournalJournal of Marine Science and Engineering
Issue number11
Number of pages19
Publication statusPublished - 2019

Bibliographical note

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited


  • Optimization
  • Ship energy system
  • Low carbon shipping
  • Linear programming
  • Genetic algorithm


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