When natural disasters or extreme weather events hit, delivering aid quickly and efficiently to those affected is crucial. Humanitarian relief efforts commonly rely on the combination of trucks and ...

Scientists at the University of Cambridge have developed a new way to alter complex drug molecules using light rather than toxic chemicals—a discovery that could accelerate and improve how medicines ...

Incorporating multiple constraints such as task completion time, UAV payload capacity, and flight range into path optimization algorithms allows for more efficient search patterns.

Transforming a nation of 1.4 billion people into the world's leading R&D hub is a monumental task. But by liberating the minds of the next generation of Indian scientists at 11, 12, and 13 years old, ...

Abstract: In scenarios where multiple decision-makers operate within a common decision space, each focusing on their own multi-objective optimization problem (e.g., bargaining games), the problem can ...

EvoToolkit is a Python library that leverages Large Language Models (LLMs) to evolve solutions for optimization problems. It combines the power of evolutionary algorithms with LLM-based solution ...

ABSTRACT: Multi-objective optimization remains a significant and realistic problem in engineering. A trade-off among conflicting objectives subject to equality and inequality constraints is known as ...

ABSTRACT: Mathematical optimization is a fundamental aspect of machine learning (ML). An ML task can be conceptualized as optimizing a specific objective using the training dataset to discern patterns ...

Abstract: Problem transformation-based multiobjective evolutionary algorithms (MOEAs) face the risk of losing optimal solutions when transforming a large-scale multiobjective optimization problem into ...

Nearly a quarter (24%) of buy-side trading desks plan to implement internal AI technologies for trade execution in the next 12 months, with 15% already doing so, according to a new report from Crisil ...