Findings: The proposed algorithm achieves an average efficiency of 99.32% compared to the enumeration algorithm, with minimal deviation (0.4%). The results validate the main proposition for efficient scheduling, including prioritizing jobs based on due dates, allocating job demands based on...

Background: Transportation delays pose significant challenges for perishable products by reducing freshness, shortening selling duration, and causing lost sales during the delay. Methods: Motivated by the growing importance of transportation delays on perishable products, this study develops a...

Background: Digital transformation is reshaping healthcare operations, with loyalty programs increasingly used to strengthen patient engagement and streamline administrative workflows. However, fragmented information systems and manual verification routines continue to create bottlenecks,...

Background: In Engineer-to-Order (EtO) supply chains, managing supplier lead times is particularly challenging due to high customization and intensive customer involvement. This study addresses the critical need for more accurate and dynamic lead time prediction to enhance supply chain...

This research focuses on modeling and solving a bi-objective hybrid flow shop scheduling problem, considering uncertain job-dependent setup times and worker constraints. The main objective of the mathematical model is to simultaneously minimize the Maximum Completion Time (Cmax) and minimize the...