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KŮDELA, J.
Original Title
Chance-Constrained Optimization Formulation for Ship Conceptual Design: A Comparison of Metaheuristic Algorithms
English Title
Type
WoS Article
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.
English abstract
Keywords
chance-constrained optimization; ship conceptual design; metaheuristics; evolutionary computation; numerical optimization
Key words in English
Authors
RIV year
2024
Released
03.11.2023
Publisher
MDPI
Location
BASEL
ISBN
2073-431X
Periodical
Computers
Volume
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" }
Documents
computers-12-00225