Amir Gharehgozli

California State University, Northridge, University of Tehran

Papers

Total Citations

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About

Amir Gharehgozli is a leading researcher in the fields of logistics, operations management, and robotics, with a particular focus on transforming e-commerce fulfillment. His major contribution lies in optimizing robotic mobile fulfillment systems (RMFS), the backbone of modern warehouse automation. In his highly cited work, "Robot scheduling for pod retrieval in a robotic mobile fulfillment system" (2020, 82 citations), Gharehgozli tackles the critical challenge of scheduling robots to retrieve inventory pods, directly increasing order picking efficiency for retailers. This research provides foundational algorithms that help balance robot travel time and pick station workload, making same-day delivery more feasible. Earlier in his career, he explored intelligent decision-making in autonomous systems, notably in "Action Selection in Robots Based on Learning Fuzzy Cognitive Map" (2006), where he used fuzzy cognitive maps to mimic human reasoning for robot behavior. His work bridges theoretical optimization with practical, industry-driven problems, earning him recognition as a key figure in the integration of robotics and supply chain management. Gharehgozli’s research continues to shape how warehouses operate, offering scalable solutions for the rapidly growing world of online retail.