In distribution systems such as airlines and express package delivery, the use of hub-and-spoke networks is common, and flow consolidation at hub facilities is essential for cost reduction. While a constant discount factor is typically used to model cost reduction in interhub links, this paper...

This study proposes a modified Particle Swarm Optimization (PSO) algorithm based on Hummingbird Flight (HBF) patterns to enhance the search quality and population diversity. The HBF has five concepts: (1) Smaller steps toward position updating are more likely than larger ones, (2) Position...

This study proposes an integrated Decision Support System (DSS) with Multi-Criteria Decision-Making (MCDM) to evaluate trainers in organizations and choose the most suitable one(s) for a training program. The clustering stage determines the most appropriate number of trainees to be assigned to a...

Online Portfolio Selection (OLPS) has attracted extensive interest in recent years. Accurate prediction of future prices and determining the optimal portfolio selection strategy based on the estimated return is a challenging topic in machine learning. We propose a novel adjusted learning...

Fraudsters are now more active in their attacks on credit card transactions than ever before. With the advancement in data science and machine learning, various algorithms have been developed to determine whether a transaction is fraudulent. We study the performance of three different machine...

The generation of huge data with high velocity creates alteration in the distribution of the stream data, which is defined as the concept of drifts. The concept drifts negatively influence the classification accuracy and the stability of the data streams. Numerous machine learning-based models...