Publication detail

Chance-Constrained Optimization Formulation for Ship Conceptual Design: A Comparison of Metaheuristic Algorithms

KŮDELA, J.

Original Title

Chance-Constrained Optimization Formulation for Ship Conceptual Design: A Comparison of Metaheuristic Algorithms

Type

journal article in Web of Science

Language

English

Original Abstract

This paper presents a new chance-constrained optimization (CCO) formulation for the bulk carrier conceptual design. The CCO problem is modeled through the scenario design approach. We conducted extensive numerical experiments comparing the convergence of both canonical and state-of-the-art metaheuristic algorithms on the original and CCO formulations and showed that the CCO formulation is substantially more difficult to solve. The two best-performing methods were both found to be differential evolution-based algorithms. We then provide an analysis of the resulting solutions in terms of the dependence of the distribution functions of the unit transportation costs and annual cargo capacity of the ship design on the probability of violating the chance constraints.

Keywords

chance-constrained optimization; ship conceptual design; metaheuristics; evolutionary computation; numerical optimization

Authors

KŮDELA, J.

Released

3. 11. 2023

Publisher

MDPI

Location

BASEL

ISBN

2073-431X

Periodical

Computers

Year of study

12

Number

11

State

Swiss Confederation

Pages count

17

URL

https://www.mdpi.com/2073-431X/12/11/225

Full text in the Digital Library

http://hdl.handle.net/11012/245110

BibTex

@article{BUT186908,
  author="Jakub {Kůdela}",
  title="Chance-Constrained Optimization Formulation for Ship Conceptual Design: A Comparison of Metaheuristic Algorithms",
  journal="Computers",
  year="2023",
  volume="12",
  number="11",
  pages="17",
  doi="10.3390/computers12110225",
  issn="2073-431X",
  url="https://www.mdpi.com/2073-431X/12/11/225"
}