Researchers have developed new software that allows clinicians to design personalized treatments for patients with movement ...

multiobjective optimization programming is often applied. However, several optimization problems that use stochastic programming do not consider the impact of the correlation between the output ...

Our model naturally utilizes a scalable state-of-the-art optimization technique called sequential linear programming that is extensively applied and studied in various engineering problems. In ...

trade-off and goal programming, which treats the objective functions as additional constraints. Some multicriteria optimization problems are given to illustrate each methodology studied here. The ...

Learn how to implement the AdaMax optimization algorithm from scratch in Python. A great tutorial for understanding one of ...

Learn how to implement Adam optimization from the ground up in Python! This step-by-step guide will walk you through the ...

Coverage Path Planning for Thermal Interface Materials” was published by researchers at Karlsruhe Institute of Technology ...

Impaired neuromusculoskeletal function due to conditions such as stroke, osteoarthritis, cerebral palsy, Parkinson's disease, ...

This study investigates designing a resilient biomass supply chain (BSC) network to mitigate disruption risks under uncertain data. It addresses disaster events causing demand uncertainty without ...

Cities generate over 80 per cent of gross domestic product in many countries in Asia and the Pacific and are engines of economic growth that have lifted millions from poverty. This economic growth is ...