Mehdi Sharifyazdi is an Associate Professor of Logistics at BI Norwegian Business School. He received his PhD, MSc and BSc degrees from Sharif University of Technology, Tehran, Iran, in the field of Industrial Engineering (Operational Research). Later on, he got his MPhil degree in Business Research - Logistics and Information Systems from Erasmus Research Institute of Management, Rotterdam, Netherlands in 2011.
Before joining BI, he had been a Postdoc at Department of Mathematics, Chalmers University of Technology and University of Gothenburg, Gothenburg, Sweden, He also worked as Assistant Professor and Part-time Lecturer in the field of Industrial Engineering (Operations research) at University of Science and Culture, Golpayegan University of Engineering and Sharif University of Technology, all in Iran. In addition, he had short-time research positions at Napier University, Edinburgh, United Kingdom, and Erasmus School of Economics, Rotterdam, Netherlands.
He has published papers in journals such as European Journal of Operational Research, International Journal of Production Research and International Journal of Advanced Manufacturing Technology. He has also co-authored a book on facility location.
Mehdi has also worked as consultant in fields such as distribution planning, facility location, vehicle routing, production planning, transport pricing and scheduling in industries such as food, oil, health products and cosmetics, pharmaceutical and automotive.
Traditionally, international humanitarian organisations have used on-demand dispatch of disaster relief goods from regional logistics units (RLUs) for sudden onset disaster response. This paper investigates the improvements in efficiency and resilience of disaster relief operations by combining the existing method of onshore prepositioning of relief items in RLUs with offshore prepositioning of relief items on-board vessels and at seaport terminals. The problem is formulated as a linear programming model that incorporates different logistical costs, including inventory cost, replenishment cost, and transportation cost, to find the best combination of disaster relief methods. At the tactical level, the model determines how much and where disaster relief items need to be prepositioned. At the operational level, the model addresses how much and by which mode of transport the disaster relief items need to be transported to disaster points. The model is tested on 16 major disasters in Southeast Asia. The main finding is that offshore prepositioning can contribute to cost reduction and resilience without compromising on the speed or the scale of the response. The results also suggest that the benefits depend on the duration of the disaster emergency period and the ratio of offshore storage cost to onshore storage cost.
Sharifyazdi, Mehdi & Flygansvær, Bente M. (2015)
Dynamic routing in reverse logistics : the effect of sensors in waste containers on uncertainty
Jæger, Bjørn (red.). NOFOMA 2015 : Post Conference Proceedings, Molde, 3-5 June 2015, Nordic Logistics Research Network
Reverse logistics systems are characterized with inherent uncertainties from supply and demand. Therefore, tools and planning methods must be developed to cope with these uncertainties and at the same time reduce cost and increase service and predictability. This paper develop a dynamic method for vehicle routing in waste collection. In particular, we evaluate the effect of availability of fill-rate data provided by sensors in waste containers. Keywords: Reverse logistics, Uncertainty, Vehicle Routing, Dynamic routing, Waste containers.