Main Project: Optimization of Wood Chips Production with Forest and Landscape Denmark

The increased use of wood chips at centralized power plants is an important initiative in the field of biomass in Denmark. In order to cope with the unbalanced supply and demand, the supplier of wood fuel stores 20% of its inventories for a period of time at the storage terminal. A variant of the production, inventory, distribution, routing problem (PIDRP) is developed to describe the production and distribution of wood chips. The work is focused on reducing the high inventory and routing cost by optimizing the production planning in the forest which is divided into different districts and different stands within each district. A mix integer programming model is developed to make a yearly production plan with minimal inventories costs between districts. In addition, a 2-opt tabu search with best improvement solution method is used for intra-districts routing planning. Computational results show great inventory and routing costs saving opportunity for the supplier of wood chips. The methods used provide insight to supply chain managers faced with related challenges.

Main Project: Optimal Tugboats Positioning Problem in the High North

In order to prevent or minimize the risk of oil tankers drifting accidents and corresponding environmental impacts, tug vessels are used and monitored by the Vessel Traffic Services (VTS) in Vardø to patrol every oil ships moving along the coastline. The VTS center in Vardø managed by the Norwegian Coastal Administration (NCA) is faced by several challenges that need to be addressed. In fact, the dynamic and uncertain patrolling operations as well as the high expansion of the petroleum
activity make the sustainable management and control of the fleet vessels a highly complex problem. The aim of the project is to assist the NCA by developing operations research-based models and algorithms.

My main research capabilities

I am mostly interested in applied research, using operational research methods and social sciences approaches to solve real life logistics problems.

Mathematical modelling

Developing mathematical model for real life problems/systems in logistics

Monte Carlo Simulation and Scheduling methods

We use simulation and scheduling models to propose better solutions to complex systems/problems in Logistics 

Meta-heuristics algorithms

We develop complex algorithms for NP-hard problems in Logistics 

Stochastic optimization

Addressing the uncertainty in real life logistics problems by means of stochastic modelling 

Superquantiles optimization

We use superquantiles optimization to assist risk averse decision maker in logistics 

Qualitative and quantitative analysis

We do use social science approaches to logistics problem too 🙂 

Main research interests

Below are some of my main research interests 

Intelligent logistics

The use of integrated intelligent technology (IoT, etc), which allows the logistics system to mimic human intelligence…

Smart Logistics
Vehicles routing problems (VRP)

Combinatorial optimization that  finds an optimal design of routes traveled by a fleet of vehicles to serve a set of customers.

Distribution Management
Urban Logistics

Urban logistics refer to the  movement of goods in urban areas, with the main concern on congestion.

City Logistics
Logistics and value chain

A value chain represent all the valuable activities that a company performs in order to deliver a valuable product to the end customer.

Value Chain Management
Logistics educational needs (LEN)

How do we close the gap between Logistics education and industry needs?

Education and Industry Gap
And many more for developing countries 🙂

Hospital logistics, port/airport  waiting line minimization, emergency police patrol, reverse logistics, petroleum logistics, humanitarian logistics…

Logistics everywhere

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