Optimal design and operation of cruise ship multi-energy systems: an MILP formulation

Regulations set by governmental and non-governmental maritime regulatory bodies are set to highly impact the cruise ship industry and put pressure on ship owners to invest in energy-efficient ships as well as improve the overall ship operation. To this end, various studies have been performed to analyze the economic and environmental impact of energy efficient technologies and ship operation strategies. These studies typically involve modelling the cruise ship energy consumers and producers as a non-linear model and analyzing the impact of the technology being studied. In this paper, we propose a formulation of the cruise ship energy system design optimization as a generic mixed integer linear program (MILP). The generic formulation of the model allows for a variety of technologies to be tested without much modification to the underlying formulation. The model is instantiated using internal combustion engines (ICEs) and solid oxide fuel cell (SOFC) technologies and an analysis of the optimization results is carried out for three objective functions: greenhouse gas (GHG) emissions, lifecycle cost, and lifecycle cost including carbon tax. The model's design and operation results were validated by experts. Results from the case studies indicated significant reductions in GHG emissions using SOFCs, consistent with the literature. However, the carbon tax analysis over a period of 15 years showed a surprisingly lower impact of carbon tax measures than expected, which could have potential consequences on the adoption of cleaner, yet cost intensive technologies in the cruise ship industry

An Online Learning-based Metaheuristic for Solving Combinatorial Optimization Problems

International audienceThe goal of this contribution is twofold: 1) Proposing a state of the art review on hybridization methods between MHs and ML; and 2) Introducing the concept of a novel approach focused on online learning in population-based MHs

New Insights into the Propulsion Power Prediction of Cruise Ships

International audienceShip propulsion is the largest consumer of energy -- and by extension fuel -- on cruise ships. Improving its efficiency is thus an important aspect of energy management, both for environmental and economic reasons. Various approaches have been detailed in the literature for improving propulsion efficiency, ranging from optimal voyage planning to prediction of propulsion power or fuel consumption using Machine Learning algorithms, trained on high frequency sensor data. On this latter topic, the approaches typically involve a series of data transformations and time-aggregations (windowing), followed by shuffling and separation of data points into train and validation sets. However, this approach leads to very similar data in the train and validation sets, preventing trained models to generalize well on future ship voyages. In this article we highlight methodological issues and give insights on how to tackle them to train models that focus on optimizing generalizability, especially predictive accuracy on unseen future test sets.We present a temporal approach to splitting data into train, validation and test sets. We perform our analysis using simple multilayer perceptron architectures, of distinct dimensions. Our study concludes that smaller/simpler models, trained on temporal-split data have a lower error when predicting on unseen future test data, compared to larger models and usage of shuffle-split datasets, while also providing better confidence in model accuracy, due to reduced discrepancy between obtained validation and test errors

High throughput phenotyping : associated tools and methods to assess determinisms of plant and microbiome interactions

International audienc

New developments towards high throughput phenotyping studies devoted to innovative plant breeding tools

International audienc

Determinisms of plant and microbiome interactions : a multidisciplinary approach involving high-throughput phenotyping

International audienc

Determinisms of plant and microbiome interactions : a multidisciplinary approach involving high-throughput phenotyping

International audienc

From morphological to functional root traits assessment with high throughpout phenotyping

International audienc

Within a high throughput phenotyping platform, mix ecophysiology, microbial ecology, molecular physiology and genetics and stir: the recipe of new breeding tools

International audienc

Determinisms of plant and microbiome interactions : a multidisciplinary approach involving high-throughput phenotyping

International audienc