Pawel L. Manikowski
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Pawel L. Manikowski has a total of 3 co-authors. Here are the top co-authors by number of shared publications:
- Matthew J. Craven
University of Plymouth, Plymouth, United Kingdom
3 shared publications - David J. Walker
University of Exeter, Exeter, United Kingdom
2 shared publications David J. Walker
1 shared publication
Latest Publications
- Open Access
- 14 July 2025
- Published by Association for Computing Machinery (ACM)
- p. 2233-2241
Multi-objective Optimisation of Floating Offshore Wind Farms based on a Real-World Case Study
- 14 July 2025
- Published by Association for Computing Machinery (ACM)
- p. 2233-2241
Open AccessMulti-objective Optimisation of Floating Offshore Wind Farms based on a Real-World Case Study
- Open Access
- 22 February 2025
- Published by Elsevier in Applied Soft Computing
- Vol. 173
Many-objective optimisation of offshore wind farms
- 22 February 2025
- Published by Elsevier in Applied Soft Computing
- Vol. 173
Open AccessMany-objective optimisation of offshore wind farms
- Open Access
- 3 December 2021
- Published by MDPI AG in Journal of Marine Science and Engineering
- Vol. 9 (12) , 1376
Multi-Objective Optimisation of the Benchmark Wind Farm Layout Problem
Wind farm layout optimisation has become a very challenging and widespread problem in recent years. In many publications, the main goal is to achieve the maximum power output and minimum wind farm cost. This may be accomplished by applying single or multi-objective optimisation techniques. In this paper, we apply a single objective hill-climbing algorithm (HCA) and three multi-objective evolutionary algorithms (NSGA-II, SPEA2 and PESA-II) to a well-known benchmark optimisation problem proposed by Mosetti et al., which includes three different wind scenarios. We achieved better results by applying single- and multi-objective algorithms. Furthermore, we showed that the best performing multi-objective algorithm was NSGA-II. Finally, an extensive comparison of the results of past publications is made.
- 3 December 2021
- Published by MDPI AG in Journal of Marine Science and Engineering
- Vol. 9 (12) , 1376
Open AccessMulti-Objective Optimisation of the Benchmark Wind Farm Layout Problem
Wind farm layout optimisation has become a very challenging and widespread problem in recent years. In many publications, the main goal is to achieve the maximum power output and minimum wind farm cost. This may be accomplished by applying single or multi-objective optimisation techniques. In this paper, we apply a single objective hill-climbing algorithm (HCA) and three multi-objective evolutionary algorithms (NSGA-II, SPEA2 and PESA-II) to a well-known benchmark optimisation problem proposed by Mosetti et al., which includes three different wind scenarios. We achieved better results by applying single- and multi-objective algorithms. Furthermore, we showed that the best performing multi-objective algorithm was NSGA-II. Finally, an extensive comparison of the results of past publications is made.