The role of setup times in production planning and control was recognised in the late 1960s. Since then, a growing number of scheduling problems have accounted for sequence-dependent setup time variables. This study aims to provide a systematic review of setup times in the short-term production...

In this paper, a novel message-passing algorithm, named AMP-R, based on belief propagation is proposed to solve the heterogeneous multi-depot vehicle routing problem (HMDVRP) in a distributed manner. Unlike traditional approaches, this is the first attempt to decentralize the solution process...

Traffic congestion in urban centers not only hampers mobility but also significantly impacts economic activities and environmental sustainability. This study leverages advanced machine learning techniques to analyze and predict traffic jams, utilizing a detailed dataset of 9847 recorded accident...

This study investigates the impact of competition on credit risk in the Turkish banking system, focusing on Islamic (participation) and conventional banking under the same regulatory conditions regarding credit risk. The credit risk model is trained using CatBoost, extreme gradient boosting...

The financial sector faces mounting challenges in processing vast volumes of high-velocity data to support intelligent, real-time decision-making. Traditional machine learning models often fall short in accuracy, scalability, and responsiveness when dealing with large, dynamic financial...