Abstract: dynamic multiobjective optimization (DMO) problems are prevalent in many practical applications and have garnered significant attention from both industry and academia, leading to the ...

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Abstract: Fractional programming (FP) is a branch of mathematical optimization that deals with the optimization of ratios. It is an invaluable tool for signal processing and machine learning, because ...

This study develops a unified framework for optimal portfolio selection in jump–uncertain stochastic markets, contributing both theoretical foundations and computational insights. We establish the ...

ABSTRACT: This research investigates the impact of the road network topological structure on facility location modeling. We create four types of road networks, i.e., the radial, the grid, the ring, ...

The ability to solve complex problems effectively has become a defining factor for success. Yet, despite the abundance of tools and methodologies available, I've noticed organizations often struggle ...

Large language models (LLMs) have become crucial tools for applications in natural language processing, computational mathematics, and programming. Such models often require large-scale computational ...