35 citations · 66 across the 8 of their papers we have counts for
7 papers · 1 filter
Probability estimation and structured output prediction for learning preferences in last mile delivery
Rocsildes Canoy, Victor Bucarey, Yves Molenbruch +3
We study the problem of learning the preferences of drivers and planners in the context of last mile delivery. Given a data set containing historical decisions and delivery locatio…
Efficiently Explaining CSPs with Unsatisfiable Subset Optimization
Emilio Gamba, Bart Bogaerts, Tias Guns
We build on a recently proposed method for explaining solutions of constraint satisfaction problems. An explanation here is a sequence of simple inference steps, where the simplici…
Learn-n-Route: Learning implicit preferences for vehicle routing
Rocsildes Canoy, Víctor Bucarey, Jayanta Mandi +1
We investigate a learning decision support system for vehicle routing, where the routing engine learns implicit preferences that human planners have when manually creating route pl…
Towards Improving Solution Dominance with Incomparability Conditions: A case-study using Generator Itemset Mining
Gökberk Koçak, Özgür Akgün, Tias Guns +1
Finding interesting patterns is a challenging task in data mining. Constraint based mining is a well-known approach to this, and one for which constraint programming has been shown…
Vehicle routing by learning from historical solutions
Rocsildes Canoy, Tias Guns
The goal of this paper is to investigate a decision support system for vehicle routing, where the routing engine learns from the subjective decisions that human planners have made…
Solution Dominance over Constraint Satisfaction Problems
Tias Guns, Peter J. Stuckey, Guido Tack
Constraint Satisfaction Problems (CSPs) typically have many solutions that satisfy all constraints. Often though, some solutions are preferred over others, that is, some solutions…