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Analytics and Optimization

Analytics involves transforming data into decisions. At the A&O Research Group, we cover the whole process, with a special focus on optimization.

We specialize in stochastic processes, such as queuing systems and their controlled counterparts, Markov decision processes. Additionally, we cover related areas including combinatorics, simulation, machine learning, and statistics. A considerable part of our research is in collaboration with the Stochastics group at CWI.

The research questions we explore in these technical areas are often inspired by practical challenges encountered across various application domains. Thus, we strive to lead in both the development of application domains and solution methods.

Our primary focus is on service-oriented applications, which are distinguished by the influence of customer interactions on the product. The variability in customer demand and preferences introduces randomness as an essential element in the mathematical modeling of services.

A key area of our research is health care, particularly in ambulance planning, nursing homes, and hospital operations. Notable achievements include the planning and dynamic reallocation of ambulances, resulting in significantly improved service levels. Within hospital settings, we specialize in various aspects of patient flow, from appointment scheduling to dynamic bed capacity models. We collaborate with the VU Medical Center through PICA, the joint health care logistics center, in these efforts. Another significant research focus is on long-term care, especially home care and nursing homes.

Next to these more traditional fields, where we often discover innovative solutions, some of our researchers delve into emerging fields created by the current data proliferation. Noteworthy areas include social media, public transportation, and human resource management. Our innovative research includes projects on detecting unexpected behavior on Twitter, the analysis of employee profiles, and identifying changes in group behaviour in public transportation.

Researchers and their interests

  • René Bekker. Queueing models and health care applications.

    My research focuses on two related areas. First, I like to analyze the performance of queueing models and stochastic processes. Such models provide a fundamental understanding of the behaviour of practical systems where uncertainty is involved. Second, I am excited about applications to health care operations, including hospital care, home care and nursing home care. This calls for a wider set of methods from optimization and operations research.

  • Joost Berkhout. Applied stochastic optimization.

    My research focuses on stochastic optimization with a focus on real-life applications. To that end, I use techniques from simulation optimization, (meta)heuristics, and machine learning. Current application areas include production scheduling, home health care scheduling, and robust ship design. A second research focus is on applying Markov chain theory to analyze and design real-life networks, such as social networks and internet networks.


  • Sandjai Bhulai. Business analytics.

    My research lies at the intersection of mathematics, computer science, and operations management. I am passionate about employing operations research, statistics, and machine learning to address practical challenges associated with decision-making under uncertainty. My current research projects are centered on HR analytics, social media analytics, predictive analytics, dynamic pricing, and the planning and scheduling of complex systems.


  • Ger Koole. Service operations management.

    My research is at the interface of stochastic operations research and service operations management. I like to solve practical problems in a mathematically correct way. For that I use and also extend results from queueing theory and Markov decision chains. Also combinatorial optimization, statistics and machine learning belong to my toolbox. My favorite application areas are call centers, health care operations, and revenue management. 

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  • Rob van der Mei. Applied mathematics

    My research in the area of stochastic operations research and machine learning, at the challenging interface of theory and application. Over the years, I have built up a huge network of research collaborations with industries and governments, and established many public-private partnerships, bridging the gap between academic research and application in practice. My research interests include emergency-response systems, predictive policing, management of road traffic, modeling and scalability analysis of ICT systems, service logistics, freight logistics, revenue management, military operations research and queueing theory. 

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  • Alessandro Zocca. Complex networked systems.

    My research is centered around the study of complex networked systems in which randomness plays a crucial role. More specifically, I study dynamics and rare events in networks affected by uncertainty, drawing motivation from applications to sustainable power grid networks. My research uses cutting-edge techniques from applied probability, graph theory, stochastic optimization, and reinforcement learning.


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