Paper aims To do a comprehensive review of the exact and heuristic methods, software/programming languages, constraints, and types of analysis (technical and fundamental) used to solve the portfolio ...

Neural-guided Ant Colony Optimization (ACO) currently suffers from a fundamental training-inference misalignment: policies are typically trained to generate static priors (e.g., heatmaps) from ...

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Abstract: Artificial Intelligence (AI) enhances option pricing accuracy and risk management, enabling precise valuation of complex derivatives across various market scenarios. This paper compares ...

In response to the shortcomings of the Salp Swarm Algorithm (SSA) such as low convergence accuracy and slow convergence speed, a Multi-Strategy-Driven Salp Swarm Algorithm (MSD-SSA) was proposed.

The uncertainty of renewable energy and demand response brings many challenges to the microgrid energy management. Driven by the recent advances and applications of deep reinforcement learning a ...

The Ant colony Optimization algorithm is a probabilistic technique for solving computational problems which can be reduced to finding good paths through graphs (source). This implementation of the ACO ...

Predicting the stability of granular materials under particle removal has wide-reaching applications, including automating tunnel excavations. Searching for general laws that govern granular stability ...