This study presents a multi-objective optimization model for blood supply chain (BSC) management, aiming to maximize total profit and fulfillment rate and minimize carbon emissions. The model is formulated as a mixed-integer linear program (MILP) and solved using the weighted sum method. The...

The wine industry faces distinctive supply chain challenges, including high product variety, export market fragmentation, and seasonal production, all of which contribute to demand uncertainty. Importantly, this uncertainty is not only externally driven but also amplified by tactical and...

Disruptive events like the COVID-19 pandemic have exposed supply chain vulnerabilities. This study focuses on dual sourcing as a resilient strategy and examines a stochastic, single-item, multi-echelon, multi-period, dual sourcing inventory system under backorders. In each echelon, the...

Background: In the context of increasing supply chain complexity, efficient inventory management has become important in enhancing the performance of logistics systems and sustaining the competitiveness of companies. Real-time visibility, tracking, and control over stock levels ensure...

In today's volatile business environment, manufacturers often face the challenge of making sales and production decisions despite unstable market demand. Companies must strategically determine which customer orders to fulfill or which products to stock under limited resources. This study...

Supply chains play an essential role in ensuring operational efficiency and economic stability, yet they facechallenges such as the "bullwhip effect," which amplifies demand fluctuations. Addressing these issues requires innovativestrategies that integrate behavioral theories with technological...

Purpose: This study presents a systematic literature review that provides a broad and holistic view of how machine learning can be used and integrated to enhance decision-making in various areas of the supply chain, highlighting its combination with other techniques and models....

Even in the context of Industry 4.0, conventional warehouse management continues to encounter challenges. Amidst these obstacles, innovative solutions are imperative. Order picking, a critical process with significant implications for customer service, remains labor-intensive within warehousing...

This study examines the challenges of two warehouses operating under Last-In-First-Out (LIFO) order policies in inventory management, including unpredictable demand patterns, the decay of Weibull distribution, and the need to reduce carbon emissions by adopting green technology. The research...

Background: Traditional procurement and price negotiation methods in public hospitals in Thailand involve group purchasing agreements and bulk orders, posing challenges to improving inventory management efficiency. The vendor-managed inventory (VMI) model is a promising alternative for enhancing...

Background: In the current global market, supply chains are increasingly complex, necessitating agile and sustainable management strategies. Traditional analytical methods often fall short in addressing these challenges, creating a need for more advanced approaches. Methods: This study leverages...

Purpose - Inventory is a crucial part of a systematic supply chain of a business. Small firms mostly neglect inventory management (IM) by accumulating excessive inventory for a time. The study aims to examine the IM practices of small and medium enterprises (SMEs) in Bangladesh....

Background: A logistics network plan could be a major key issue due to its effect on supply chain effectiveness and responsiveness. This study aims to investigate the inventory location in the humanitarian logistics response stage using a three-level logistics network to integrate...

This study investigates a non-instantaneous deteriorating two-warehouse inventory problem with allowable delay payments under inflation. The objective is to maximize the total profit per unit of time by determining the optimal order quantity, the product's selling price, and the business cycle...

Spare parts are particularly challenging to forecast due to their lumpiness and representing a significant part of companies’ expenditures, so even small improvement in new approaches can considerably reduce these items’ total inventory. This paper aims to present a new hybrid forecasting...

Spare parts are particularly challenging to forecast due to their lumpiness and representing a significant part of companies' expenditures, so even small improvement in new approaches can considerably reduce these items' total inventory. This paper aims to present a new hybrid forecasting method...

We study a multi-product maritime inventory routing problem (MIRP) with sailing time uncertainty. We explicitly consider the replanning that happens after uncertainty is revealed. The objective is to determine the stability of the adjusted plans after the occurrence of an uncertain event and to...

This research focuses on accurately forecasting steel wire mesh demand to ensure timely order fulfillment. Various univariate time series forecasting methods were employed, including Prophet, Support Vector Regression (SVR), 1-Dimensional Convolutional Neural Network (1D-CNN), Recurrent Neural...