Constraint multi-objective optimization with a limited budget for function evaluations is challenging. This thesis tackles this problem by proposing new optimization algorithms. These algorithms are applied on holistic ship design problems. This helps naval architects balance objectives like cost, efficiency,…

A common method to solve expensive function evaluation problem is using Bayesian Global Optimization, instead of Evolutionary Algorithms.

A modern ship design process is subject to a wide variety of constraints such as safety constraints, regulations, and physical constraints.

Multi-objective optimization is an effective technique for finding optimal solutions that balance several conflicting objectives. It has been applied in many fields of our world, because practical problems usually have more than one desired goal. For example, developing a new vehicle component might…

Promotores: Prof.dr. T.H.W. Bäck, Prof.dr. M.R.V. Chaudron, Co-Promotor: M.T.M. Emmerich

This thesis seeks to combine two different research topics; Multi-Objective Optimization and Complex Network Analysis.

Promotores: Prof.dr. T.H.W. Bäck, Prof.dr. M. Bongards (Cologne University)

The focus of the Multicriteria Optimization and Decision Analysis (MODA) group is to develop foundations of methods in multi-objective optimization.

Multi-objective evolutionary computation aims to find high quality (Pareto optimal) solutions that represent the trade-off between multiple objectives.

Research in the Natural Computing and Optimization cluster covers theoretical foundations, the development of new algorithms, and interdisciplinary applications of natural computing methods.

It is a common technique in global optimization with expensive black-box functions to learn a surrogate-model of the response function from past evaluations and use it to decide on the location of future evaluations.

Optimality in plant properties and processing.

Optimization tasks in practice have multifaceted challenges as they are often black box, subject to multiple equality and inequality constraints and expensive to evaluate.

Optimally solving real-world expensive Black-Box Optimization (BBO) problems w.r.t. real-world constraints, such as wall-clock time and computational costs, is extremely difficult and tedious.

This thesis covers several aspects of quantum algorithms for near-term quantum computers and its applications to quantum chemistry and material science.

Promotor: Prof.dr. H.A.G. Wijshoff

Industrial manufacturing processes, such as the production of steel or the stamping of car body parts, are complex semi-batch processes with many process steps, machine parameters and quality indicators.

In this thesis, topics relating to the optimization of high-throughput pipelines used for imaging are discussed. In particular, different levels of implementation, i.e., conceptual, software, and hardware, are discussed and the thesis outlines how advances on each level need to be made to make gains…

This thesis involves three topics: benchmarking discrete optimization algorithms, empirical analyses of evolutionary computation, and automatic algorithm configuration.

The goal of hit and lead optimization is to optimize suitable chemical starting points that can modulate a drug target. The methods and technologies used are similar to those in Hit Discovery, but once the compound has shown activity in an animal model, it moves from 'hit' to 'lead.'

Continuous optimization is never easy: the exact solution is always a luxury demand and the theory of it is not always analytical and elegant.

Microneedle-based vaccination has several advantages over vaccination by using conventional hypodermic needles.

The better teaching is for pupils and students, the more solid the basis will be that we give them for their future careers. This type of teaching requires strong instructors and insight into the best ways in which pupils can be supported, and research at Leiden University is making a contribution in…

Life Sciences Artificial Intelligence Data Science

The currently available in vitro generated human skin equivalents resemble the human skin in many aspects. However, some essential barrier characteristics do not fully mimic the native barrier. Consequently, the human skin equivalents cannot be used for screening of drugs for skin penetration.

Uncertainty and noise are frequently-encountered obstacles in real-world applications of numerical optimization. The practice of optimization that deals with uncertainties and noise is commonly referred to as robust optimization.

Over several decades, a variety of computational methods for drug discovery have been proposed and applied in practice. With the accumulation of data and the development of machine learning methods, computational drug design methods have gradually shifted to a new paradigm, i.e. deep learning methods…

For optimization problems, it is often unclear how to choose the most appropriate optimization algorithm. As such, rigorous benchmarking practices are critical to ensure we can gain as much insight into the strengths and weaknesses of these types of algorithms.

The Reinforcement Learning lab conducts research into Reinforcement Learning and Intelligent Combinatorial Algorithms.

This thesis is based on five papers on several topics.

Sepsis is a life-threatening condition caused by a dysregulated host response to infection, it is associated with significant morbidity, mortality, and with a high financial burden on global healthcare systems. Bacterial infections are the primary cause of sepsis, but the growing prevalence of antimicrobial…

Carbon dioxide capture and utilization technologies are necessary to create a truly circular economy. The electrochemical reduction of carbon dioxide to formate is an appealing carbon utilization method as it can be performed at room temperature and pressure, it only requires two electrons, and it has…

The German professor of Information Systems and Statistics Heike Trautmann accepted the Pascal chair this month at LIACS, the computer science institute of Leiden University. Trautmann’s main research areas are evolutionary multiobjective optimisation and data science, in which LIACS is strong as we…

Plants and their pollinators form complex interaction networks. Within these networks, species differ widely in the number of species they interact with.

Fungal infections pose a significant threat to individuals with compromised immune systems and despite advancements in diagnosis and treatment, they continue to jeopardize patient’s health.

Previous research has found important inter-individual differences in the pharmacokinetics (PK) of morphine in special populations such as children, the morbidly obese or the critically ill.

The 14th International Global Optimization Workshop (LeGO 2018) was hosted by Leiden University in September.

The increasing competition in the automotive industry requires the tailored, swift development of technologically sophisticated vehicles. Therefore, the computationally expensive state-of-the-art simulation technologies are combined with optimization algorithms. An example of a real-world optimization…

In design optimization problems, engineers typically handcraft design representations based on personal expertise, which leaves a fingerprint of the user experience in the optimization data. Thus, learning this notion of experience as transferrable design features has potential to improve the performance…

PhD defence

On this page you can find information about previous CCLS events.

This study aims to explore the use of a behavioral-design-based approach in simulating patient flow through EMTs. It provides a dynamic behavioral simulation model to assess the interactions between patients, staff members, and the related dynamic movements/interactions with the health care facility,…

This thesis focuses on addressing four research problems in designing embedded streaming systems.

Quantum annealing belongs to a family of quantum optimization algorithms designed to solve combinatorial optimization problems using programmable quantum hardware. In this thesis, various methods are developed and tested to understand how to formulate combinatorial optimization problems for quantum…

Researchers at LED3 are working together with biopharmaceutical company Galapagos to develop software for use in early drug discovery (funded by NWO). This software is able to design molecules with several simultaneously optimized characteristics and will also take prediction reliability into consideration…

DSE 2.0 concerns research on DSE techniques for complex dCPS

Researchers are pulled in various, sometimes contradictory directions by the multiplication of performance metrics and new incentives to align with societal needs. Management structures, funding systems, and publication practices are increasingly influenced by pressures to promote only the highest quality…

Promotor: S.M. Verduyn Lunel