Generalized Model and Deep Reinforcement Learning-Based Evolutionary Method for Multitype Satellite Observation Scheduling

Multitype satellite observation, including optical observation satellites, synthetic aperture radar (SAR) satellites, and electromagnetic satellites, has become an important direction in integrated satellite applications due to its ability to cope with various complex situations. In the multitype satellite observation scheduling problem ...

Thermal-mechanical-electrical Co-design of Fan-Out Panel-Level SiC MOSFET Packaging with a Multi-objective Optimization Algorithm

As the next generation of semiconductor devices, SiC MOSFETs have demonstrated significant performance improvements in switching loss, switching frequency, and high-temperature operation compared to Si-based MOSFETs. However, the long-term reliability of such devices and their packaging continues to be a major concern. Towards addressing this...

A novel strain-based health indicator for the remaining useful life estimation of degrading composite structures

We present a generic methodology for developing a Health Indicator out of strain-based Structural Health Monitoring data suitable for implementation in prognostic tasks. For this purpose, an in-house test campaign is launched. Single-stringered composite panels are subjected to compression-compression fatigue with the strains being monitored...

Mixed-Integer Nonlinear Programming for Energy-Efficient Container Handling: Formulation and Customized Genetic Algorithm

Energy consumption is expected to be reduced while maintaining high productivity for container handling. This paper investigates a new energy-efficient scheduling problem of automated container terminals, in which quay cranes (QCs) and lift automated guided vehicles (AGVs) cooperate to handle inbound and outbound containers. In our scheduling...

On the impact of linkage learning, gene-pool optimal mixing, and non-redundant encoding on permutation optimization

Gene-pool Optimal Mixing Evolutionary Algorithms (GOMEAs) have been shown to achieve state-of-the-art results on various types of optimization problems with various types of problem variables. Recently, a GOMEA for permutation spaces was introduced by leveraging the random keys encoding, obtaining promising first results on permutation flow...

Evolutionary algorithms for designing reversible cellular automata

Reversible Cellular Automata (RCA) are a particular kind of shift-invariant transformations characterized by dynamics composed only of disjoint cycles. They have many applications in the simulation of physical systems, cryptography, and reversible computing. In this work, we formulate the search of a specific class of RCA – namely, those...

Optimizing entanglement generation and distribution using genetic algorithms

Long-distance quantum communication via entanglement distribution is of great importance for the quantum internet. However, scaling up to such long distances has proved challenging due to the loss of photons, which grows exponentially with the distance covered. Quantum repeaters could in theory be used to extend the distances over which...

Optimal Battery Energy Storage System Sizing for Demand Charge Management in EV Fast Charging Stations

The high pulsating demand of fast charging stations (FCS) may cause monthly demand charges to account for a significant fraction of a station's electric bill. To reduce these costs, demand charge management can be applied to suppress peak power demands at FCSs, also using battery energy storage systems (BESS). This paper proposes a multi...

Layout optimization of heaving Wave Energy Converters linear arrays in front of a vertical wall

The present paper focuses on the determination of optimum layouts for linear arrays of heaving Wave Energy Converters (WECs) in front of a vertical wall. Optimum layouts maximize the annual averaged absorbed energy at a given marine site and satisfy spatial constraints. For achieving this goal, we developed an efficient optimization numerical...

Towards stochastic simulations of relevance profiles

Recently proposed methods allow the generation of simulated scores representing the values of an effectiveness metric, but they do not investigate the generation of the actual lists of retrieved documents. In this paper we address this limitation: we present an approach that exploits an evolutionary algorithm and, given a metric score,...

Multi-scenario Model Predictive Control based on genetic algorithms for level regulation of open water systems under ensemble forecasts

Operational water resources management needs to adopt operational strategies to re-allocate water resources by manipulating hydraulic structures. Model Predictive Control (MPC) has been shown to be a promising technique in this context. However, we still need to advance MPC in the face of hydrological uncertainties. This study makes the first...

Progressive design methodology for complex engineering systems based on multiobjective genetic algorithms and linguistic decision making

This work focuses on a design methodology that aids in design and development of complex engineering systems. This design methodology consists of simulation, optimization and decision making. Within this work a framework is presented in which modelling, multi-objective optimization and multi criteria decision making techniques are used to design...

Improved genetic algorithm inspired by biological evolution

Application of genetic algorithms to the design of airfoil pressure distributions

NLR participates in the ECARF (European Computation Aerodynamics Research Project) "Optimum Design" project, developing an algorithm for multi-point airfoil design. Within the ECARP project a test case has been defined for two-point design with the aid of well-specified target pressure distributions. It appears that optimization of pressure...

Automatic generation of a section erection planning for European shipyards building complex ships