This review article explores how emerging generative artificial intelligence (GenAI) models,
such as large language models (LLMs), can enhance solution methodologies within process …

The accurate forecasting of energy consumption is essential for companies, primarily for
planning energy procurement. An overestimated or underestimated forecasting value may …

The precise prediction of energy consumption is crucial for businesses, companies, and
households especially when it comes to planning energy purchases. An underestimated or …

ABSTRACT The Resilient Modulus (Mr) is perhaps the most relevant and widely used
parameter to characterise the soil behaviour under repetitive loading for pavement …

Crude oil resource scheduling is one of the critical issues upstream in the crude oil industry
chain. It aims to reduce transportation and inventory costs and avoid alerts of inventory limit …

The spot flexibility markets are before the real-time energy exchange, allowing demand-side
management to reduce energy consumption during peak periods. In these markets, demand …

Complex combinatorial optimization problems serve as the foundation for various real-world
applications. The time required to identify the optimal solutions to these problems escalates …

The imperative for swift and intelligent decision making in production scheduling has
intensified in recent years. Deep reinforcement learning, akin to human cognitive processes …

The Stirling numbers for graphs provide a combinatorial interpretation of the number of cycle
covers in a given graph. The problem of generating all cycle covers or enumerating these …

Introduction Soccer events require a lot of energy, resulting in significant carbon emissions.
To achieve carbon neutrality, it is crucial to reduce the cost and energy consumption of …