Hangar Parking Optimization with Path Planning Integration: A novel Approach to Minimize Movements via A* Adaptations and Neighborhood Search

MIHEA in Action: A Reproduction Study and Evaluation on Learning Bayesian Networks from Data

The Impact of Charging Electric Vehicles Between Routing Instances: The Modeling of a Combined Electric Vehicle Routing and Charging Model

Raising the acceptance for a preference-based design methodology in the context of urban development

Mobile EV Charging: Design, Optimization and Evaluation of Battery-Integrated Robots to Improve Electric Mobility

Feasibility study on the integration of a deep learning dose computation algorithm in an automated proton therapy treatment planning system

Topology and variable optimization of a planar quasi-zero stiffness mechanism for motion isolation during the installation of wind turbine blades

Design and Operation Optimization of Hybrid Energy Systems for a General Cargo Vessel: Well-to-Wake Emission Analysis and Plant Lifetime Estimation

Seismic acquisition analysis and design using multiple reflections

Glare-based control strategy for Venetian blinds in a mixed-use conference space with fully glazed facades

Learning-Based Multi-UAV Flocking Control With Limited Visual Field and Instinctive Repulsion

EV Smart Charging in Distribution Grids - Experimental evaluation using Hardware in the Loop Setup

Machine learning in process systems engineering: Challenges and opportunities

Automatic enhancement of vascular configuration for self-healing concrete through reinforcement learning approach

Multi-criteria design methods in façade engineering: State-of-the-art and future trends

A multi-objective optimization and multi-attribute decision-making analysis for technical-thermodynamic-economic evaluation considering the rock damage on production performance of hot dry rock geothermal resources

Synchronized optimization of wind farm start-stop and yaw control based on 3D wake model

Statistically Distinct Plans for Multi-Objective Task Assignment

High-Confidence Data-Driven Ambiguity Sets for Time-Varying Linear Systems

Improving Traffic Efficiency With Lane Guidance Based on Desired Speeds