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Dr André van Renssen's research focuses on calculating the shortest possible paths through various types of networks - from computer and communications networks to road and other transport networks. By designing routing algorithms that can perform this task quickly and efficiently, he aims to help alleviate both information and vehicle traffic congestion without the need to build more roads or add more cables.
"The main purpose of the networks I study is to allow either information or traffic to move from one node (location) to another. So we need to find the shortest paths between the various nodes. My research focuses on designing efficient algorithms that can determine which node to direct information or traffic to so it reaches its destination in the shortest possible time.
"The problem of finding the fastest route between two locations depends on the state of the network. If there's a lot of communication or traffic over a certain cable or road, additional traffic that intends to use this route will have to wait its turn. This can be solved by adding more cables or building more or wider roads, but that approach is both expensive and impractical. By designing better routing algorithms, I hope to help alleviate these problems without the need to add new cables or roads.
"The time it takes to get from one location to another may also vary depending on the time or day of the week. During rush hour it might be better to take a longer route using side roads than to take the shortest route, which might be fine on weekends. Other factors, such as lanes being closed due to an accident or construction work, must also be taken into account by the algorithm.
"Results from this kind of research are already being used in, for example, the navigation function of Google Maps, which updates routes when a certain road is congested. I hope my work will lead to even fewer or shorter delays in the future.
"I've been working in this field since around 2010, and I joined the University of Sydney in 2018. I'm very eager to start working with my colleagues here and to expand my research."
Dr André van Renssen's research focuses on calculating the shortest possible paths through various types of networks - from computer and communications networks to road and other transport networks. By designing routing algorithms that can perform this task quickly and efficiently, he aims to help alleviate both information and vehicle traffic congestion without the need to build more roads or add more cables.
"The main purpose of the networks I study is to allow either information or traffic to move from one node (location) to another. So we need to find the shortest paths between the various nodes. My research focuses on designing efficient algorithms that can determine which node to direct information or traffic to so it reaches its destination in the shortest possible time.
"The problem of finding the fastest route between two locations depends on the state of the network. If there's a lot of communication or traffic over a certain cable or road, additional traffic that intends to use this route will have to wait its turn. This can be solved by adding more cables or building more or wider roads, but that approach is both expensive and impractical. By designing better routing algorithms, I hope to help alleviate these problems without the need to add new cables or roads.
"The time it takes to get from one location to another may also vary depending on the time or day of the week. During rush hour it might be better to take a longer route using side roads than to take the shortest route, which might be fine on weekends. Other factors, such as lanes being closed due to an accident or construction work, must also be taken into account by the algorithm.
"Results from this kind of research are already being used in, for example, the navigation function of Google Maps, which updates routes when a certain road is congested. I hope my work will lead to even fewer or shorter delays in the future.
"I've been working in this field since around 2010, and I joined the University of Sydney in 2018. I'm very eager to start working with my colleagues here and to expand my research."
研究兴趣
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CoRR (2023)
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CoRR (2023)
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CoRR (2023)
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CoRR (2023): 26:1-26:16
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CoRR (2023): 34:1-34:15
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Algorithmicano. 5 (2022): 1316-1340
arxiv(2022)
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