52 citations · 61 across the 13 of their papers we have counts for
15 papers
Data-Driven Stress Testing of Intermodal Freight Networks Using GAN-Generated Disruption Scenarios
Xudong Wang, Mustafa Can Camur, Sabarna Choudhuri +1
Intermodal freight networks are increasingly exposed to correlated, multi-mode disruptions, yet resilience assessments often rely on historical or uncorrelated scenarios that under…
Simulating Cognitive Smart Freight Corridors with Agent-Based Models and Reinforcement Learning
Madelaine Martinez-Ferguson, Chun Wang, Mustafa Can Camur +1
Smart freight corridors offer a practical pathway for connected and automated vehicle (CAV) deployment in freight transportation, but physical experimentation is expensive and exis…
Per-Shipment Multi-Agent Reinforcement Learning for Intermodal Freight Routing Under Hurricane Disruption
Aliza Sharmin, Xudong Wang, Mustafa Can Camur +1
Intermodal freight networks face growing disruption risk from climate extremes that degrade multiple corridors simultaneously. To address this, we formulate freight routing as a De…
Dynamic Disruption Resilience in Intermodal Transport Networks: Integrating Flow Weighting and Centrality Measures
Aliza Sharmin, Bharat Sharma, Mustafa Can Camur +2
Resilient intermodal freight networks are vital for sustaining supply chains amid increasing threats from natural hazards and cyberattacks. While transportation resilience has been…
Spatio-Temporal Graph Convolutional Networks for EV Charging Demand Forecasting Using Real-World Multi-Modal Data Integration
Jose Tupayachi, Mustafa C. Camur, Kevin Heaslip +1
Transportation remains a major contributor to greenhouse gas emissions, highlighting the urgency of transitioning toward sustainable alternatives such as electric vehicles (EVs). Y…
Investigating Resiliency of Transportation Network Under Targeted and Potential Climate Change Disruptions
Maedeh Rahimitouranposhti, Bharat Sharma, Mustafa Can Camur +2
Ensuring robustness and resilience in intermodal transportation systems is essential for the continuity and reliability of global logistics. These systems are vulnerable to various…
A Review on Intermodal Transportation and Decarbonization: An Operations Research Perspective
Madelaine Martinez Ferguson, Aliza Sharmin, Mustafa Can Camur +1
This paper reviews intermodal transportation systems and their role in decarbonizing freight networks from an operations research perspective, analyzing over a decade of studies (2…
A Two-Stage Stochastic Model for Road-Rail Intermodal Freight Transportation Under Demand and Capacity Uncertainty
Jeremiah Gbadegoye, Mustafa C. Camur, Xueping Li
With the steady increase in global logistics and freight transport demand, the need for efficient and sustainable intermodal transport systems becomes increasingly important. This…
Assessing the Effects of Container Handling Strategies on Enhancing Freight Throughput
Sarita Rattanakunuprakarn, Mingzhou Jin, Mustafa Can Camur +1
As global supply chains and freight volumes grow, the U.S. faces escalating transportation demands. The heavy reliance on road transport, coupled with the underutilization of the r…
Towards Next-Generation Urban Decision Support Systems through AI-Powered Construction of Scientific Ontology using Large Language Models -- A Case in Optimizing Intermodal Freight Transportation
Jose Tupayachi, Haowen Xu, Olufemi A. Omitaomu +3
The incorporation of Artificial Intelligence (AI) models into various optimization systems is on the rise. Yet, addressing complex urban and environmental management problems norma…
A Survey on Optimization Studies of Group Centrality Metrics
Mustafa Can Camur, Chrysafis Vogiatzis
Centrality metrics have become a popular concept in network science and optimization. Over the years, centrality has been used to assign importance and identify influential element…
An Integrated System Dynamics and Discrete Event Supply Chain Simulation Framework for Supply Chain Resilience with Non-Stationary Pandemic Demand
Mustafa Can Camur, Chin-Yuan Tseng, Aristotelis E. Thanos +3
COVID-19 resulted in some of the largest supply chain disruptions in recent history. To mitigate the impact of future disruptions, we propose an integrated hybrid simulation framew…
Enhancing Supply Chain Resilience: A Machine Learning Approach for Predicting Product Availability Dates Under Disruption
Mustafa Can Camur, Sandipp Krishnan Ravi, Shadi Saleh
The COVID 19 pandemic and ongoing political and regional conflicts have a highly detrimental impact on the global supply chain, causing significant delays in logistics operations a…
An Optimization Framework for Efficient and Sustainable Logistics Operations via Transportation Mode Optimization and Shipment Consolidation: A Case Study for GE Gas Power
Mustafa C. Camur, Srinivas Bollapragada, Aristotelis E. Thanos +2
General Electric (GE) Gas Power, a leading manufacturer of gas and steam turbines, manufactures and installs these turbines in power generation plants worldwide. They source compon…
Identification of Essential Proteins Using Induced Stars in Protein-Protein Interaction Networks
Chrysafis Vogiatzis, Mustafa Can Camur
In this work, we propose a novel centrality metric, referred to as star centrality, which incorporates information from the closed neighborhood of a node, rather than solely from t…