University of Calgary

Software researchers help City of Calgary improve garbage, recycling pickup practices

UToday HomeMay 31, 2013

Guenther Ruhe, professor in the Schulich School of Engineering, says his lab’s collaboration with City of Calgary Waste and Recycling Services generates “thousands of scenarios” to help make decisions about management of the waste and recycling network.Guenther Ruhe, professor in the Schulich School of Engineering, says his lab’s collaboration with City of Calgary Waste and Recycling Services generates “thousands of scenarios” to help make decisions about management of the waste and recycling network. Photo by Riley BrandtMost of us don’t give much thought to the city trucks that trundle through our neighbourhoods, collecting the contents of our black, blue and in some cases green bins.

But Guenther Ruhe does. He and his students in the Software Engineering Decision Support Laboratory are collaborating with the City of Calgary to identify better ways to use existing resources to collect waste from 300,000 homes across Calgary.

The city’s Waste and Recycling Services (WRS) employs hundreds of operators, runs three landfills and a number of community recycling depots and is aiming to recycle 80 per cent of the city’s waste by 2020.

That’s a lot of moving parts, not to mention trucks, and Ruhe and his lab have helped WRS make better decisions based on objective data. Those decisions include “which type of vehicle, how many do they need, what type of routing for the vehicles, that sort of thing.”

Ruhe says they’ve also built algorithms and run models that predict how much waste to expect at different times of the year, how to manage hundreds of different drivers and routes with varying degrees of difficulty and importance, all to improve WRS’s strategic and operational planning.

“This is not intended to prescribe to them what to do, it’s intended to help them better see different implications of different scenarios,” says Ruhe, the Industrial Research Chair in Software Engineering, a joint position between the Department of Computer Science in the Faculty of Science and the Department of Electrical and Computer Engineering at the Schulich School of Engineering.

The researchers used a comprehensive model called Bayesian Belief Network that takes stock of all the factors. “We input all the impacting factors — the quality of the service provided, the cost needed to provide the service, the qualifications of the people, the amount of trucks, length of route, etc.,” he says. “There are thousands of scenarios that are played through and they get a better sense how to put the pieces together.”

The collaboration, “one of the best I’ve been involved with,” says Ruhe, is funded by the City and matched by NSERC.

It was originally intended to run three years, but it’s been extended to a fourth. The results will be made available to other municipalities and regional governments to help them improve their waste and recycling services and meet waste reduction targets.

 

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