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

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

doi:10.3390/jmse7110403

Cited by 11 publications

(8 citation statements)

References 15 publications

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“…With the rapid development of the economy and technology, a large number of optimization problems have appeared in scientific research and actual industrial production, such as the transportation field [1], [2], the power field [3], [4], the material field [5], [6], the communication field [7], [8], the mechanical field [9], [10] and e-commerce field [11], [12], and etc. These problems are usually inferior in nature, that is, non-differentiable, non-linear, etc.…”

Section: Introductionmentioning

confidence: 99%

An Improved Mayfly Optimization Algorithm Based on Median Position and Its Application in the Optimization of PID Parameters of Hydro-Turbine Governor

Guo

Yu³

et al. 2022

IEEE Access

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Mayfly algorithm is a new intelligent optimization algorithm with unique optimization capabilities recently proposed. It has strong research value, but there are also insufficient explorations, and it is easy to fall into the problem of local optimization. This paper aims to improve the optimization performance of the mayfly algorithm and explore its application value in practical engineering optimization problems. An improved mayfly algorithm based on the median position of the group is proposed. In its velocity update, the median position of the group is introduced with emphasis, and a non-linear gravity coefficient is introduced at the same time. Through the benchmark test function, its superiority in exploitation, convergence speed and accuracy and the improvement of exploration are verified. At the same time, the simulation model of the hydro-turbine governor using MATLAB/Simulink is established, and 10% frequency disturbance experiments of this model are carried out separately in two typical working conditions. The experiments results show that the optimal ITAE index value of the system obtained by the improved mayfly algorithm is smaller, and 16.5 and 18.1 iterations to complete on average. In addition, the experiments results reveal that the PID parameters optimized by the improved mayfly algorithm can make the dynamic performance of the regulation system better than other popular swarm intelligence algorithms, where the overshoot decreased by more than 3.1%, and the adjustment time also decreased in different degrees. The proposal of the median position of the group provides a new idea for the improvement of the swarm intelligence optimization algorithm. Meanwhile, a new effective method for optimizing the PID parameters of the hydro-turbine governor has been found.

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Section: Introductionmentioning

confidence: 99%

An Improved Mayfly Optimization Algorithm Based on Median Position and Its Application in the Optimization of PID Parameters of Hydro-Turbine Governor

Guo

Yu³

et al. 2022

IEEE Access

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“…The optimisation of a geothermic plant design shown in [33] is particularly relevant to the present work, as it performs a two-stage optimisation, separating the design phase from the computation of the optimal operating parameters. Moreover, relevant applications to many aspects of ship design can be found in [34][35][36].…”

Section: Introductionmentioning

confidence: 99%

Optimisation of a Diesel-Electric Ship Propulsion and Power Generation System Using a Genetic Algorithm

Zaccone

Campora

Martelli

2021

JMSE

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In recent decades, the design of ship propulsion systems has been focusing on energy efficiency and low pollutant emissions. In this framework, diesel–electric propulsion has become a standard for many ship types and has proven its worth for flexible propulsion design and management. This paper presents an approach to the optimal design of diesel–electric propulsion systems, minimising the fuel consumption while meeting the power and speed requirements. A genetic algorithm performs the optimisation, used to determine the number and type of engines installed on-board and the engines’ design speed and power, selecting within a dataset of four-stroke diesel engines. The same algorithm is then adapted and applied to determine the optimal load sharing strategy in off-design conditions, taking advantage of the high flexibility of the diesel–electric propulsion plants. In order to apply the algorithm, the propulsion layout design is formulated as an optimisation problem, translating the system requirements into a cost function and a set of linear and non-linear constraints. Eventually, the method is applied to a case study vessel: first, the optimal diesel–electric propulsion plants are determined, then the optimal off-design load sharing and working conditions are computed. AC and DC network solutions are compared and critically discussed in both design and off-design conditions.

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“…As the ship machinery is the greatest contributor to carbon emissions, having a significant impact on ship energy efficiency, its selection is a critical decision to improve the ship carbon footprint [21]. Several researchers have looked into alternative ship machinery configurations and how these could affect the EEDI.…”

Section: Introductionmentioning

confidence: 99%

A Comparative Analysis of EEDI Versus Lifetime CO2 Emissions

Trivyza

Rentizelas

Theotokatos

2020

JMSE

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The Energy Efficiency Design Index (EEDI) was introduced as a regulatory tool employed at the ship design phase to reduce the carbon dioxide (CO2) emissions and increase the vessel’s operational efficiency. Although it stimulated the greening of the shipping operations, its effectiveness is considerably criticised from various shipping industry stakeholders. The aim of this study is to investigate the EEDI effectiveness on accurately representing the environmental performance of the next-generation ships power plants for two representative ship types, in specific, an ocean-going tanker and a cruise ship. The performance of the optimal power plant solutions identified in previous studies is analysed according to the existing EEDI regulatory framework and compared with the lifetime CO2 emissions estimated based on an actual operating profile for each ship. The results indicate that the EEDI underestimates the effect of technologies for reducing carbon emissions in all the investigated cases. In this respect, it is concluded that EEDI is classified as a conservative metric, which however can be used as an approximation to compare alternative solutions early in the design phase.

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

Cited by 11 publications

References 15 publications

An Improved Mayfly Optimization Algorithm Based on Median Position and Its Application in the Optimization of PID Parameters of Hydro-Turbine Governor

An Improved Mayfly Optimization Algorithm Based on Median Position and Its Application in the Optimization of PID Parameters of Hydro-Turbine Governor

Optimisation of a Diesel-Electric Ship Propulsion and Power Generation System Using a Genetic Algorithm

A Comparative Analysis of EEDI Versus Lifetime CO2 Emissions

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