Abstract
Invariants that incrementally maintain the value of expressions under assignments to their variables are a natural abstraction to build high-level local search algorithms. But their functionalities are not sufficient to allow arbitrary expressions as constraints or objective functions as in constraint programming. Differentiable invariants bridge this expressiveness gap. A differentiable invariant maintains the value of an expression and its variable gradients, it supports differentiation to evaluate the effect of local moves. The benefits of differentiable invariants are illustrated on a number of applications which feature complex, possibly reified, expressions and whose models are essentially similar to their CP counterparts. Experimental results demonstrate their practicability.
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Van Hentenryck, P., Michel, L. (2006). Differentiable Invariants. In: Benhamou, F. (eds) Principles and Practice of Constraint Programming - CP 2006. CP 2006. Lecture Notes in Computer Science, vol 4204. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11889205_43
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DOI: https://doi.org/10.1007/11889205_43
Publisher Name: Springer, Berlin, Heidelberg
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