FWO Postdoctoral fellowship Yves Molenbruch
In a traditional mobility policy, public transport is supplemented with (private) dial-a-ride services, providing demand-dependent door-to-door transport to people with reduced mobility. For efficiency reasons, many governments are currently implementing an innovative demand-driven mobility policy in which private dial-a-ride services also replace unprofitable public transport in rural areas. This project focuses on developing a dynamic matheuristic routing algorithm which provides integrated solutions, combining public transport and dial-a-ride services by ensuring synchronization between routes and modes.
FWO Strategic Basic Research ORDinL
The ORDinL project seeks to develop innovative methodologies for data-driven optimisation in logistics. Such an approach would enable the use of available data to learn and find patterns, thereby continuously and automatically adapting and improving logistics optimisation processes. The project is carried out in cooperation with partners from KU Leuven and VUB.
FWO PhD fellowship Lien Vanbrabant
Emergency departments constitute an important chain in a health care system. Due to a remarkable growth in demand and the ever tightening budgets, the need for services often exceeds the available resources. In this project, the aim is to analyse, optimise and manage emergency departments in order to reduce emergency department crowding and to make emergency departments work more efficiently by use of simulation and simulation-optimisation techniques.
FWO PhD fellowship Sebastian Rojas Gonzalez
The use of numerical models to simulate and analyse complex real world systems is now commonplace in many scientific and engineering domains. Depending on the system under study, and the assumptions of the modeller, the models can be deterministic (e.g., in the case of analytical functions) or stochastic (e.g., when Monte Carlo simulation or discrete-event simulation is used). Often, the goal of the modeller is to find the values of controllable parameters (i.e., decision variables) that optimize the performance measure(s) of interest. As the evaluation of the primary numerical model can be computationally expensive, different approaches have been developed to provide less expensive metamodels, also referred to as surrogate models. The goal of this research is to develop effective and efficient algorithms for multi-objective simulation optimization, using such metamodels, and to compare the performance of different algorithms using appropriate metrics. The challenge lies in the inherent randomness of the observed outputs, which complicates the search for the Pareto front, as well as the efficient identification of this front. Additionally, the simulation budget is typically limited, so a major question is how to allocate this budget optimally between the exploration and exploitation stages of the algorithms.
TETRA Transport met PIT
Upcomming IT-driven market developments in the Flemish transport sector (e.g., e-CMR, real-time delivery information) force transport companies to revise their processes . The impact of these market developments is substantial, but facing these innovations is difficult, especially in small companies. This TETRA project, coordinated by the PXL and Hasselt University, aims to design a methology in order to support small- and medium-sized transport companies to analyse and revise their processes independently. The methodology will enable these companies to rethink their business processes to respond to future innovations.
FWO PhD grant strategic basic research Tomas Ambra
Tomas Ambra is currently an FWO-supported research associate at MOBI – Mobility, Logistics and Automotive technology (Vrije Universiteit Brussel) and the research group Logistics at Hasselt University. His joint PhD research, supervised by Prof. dr. Cathy Macharis and Prof. dr. An Caris, is situated in the field of sustainable logistics, with the main focus on synchromodal transport. He is developing the SYnchronization Model for Belgian Inland Transport (SYMBIT) which is a computational model that combines features of geographic information systems, agent-based modelling and discrete event simulations.