Importance

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Abstract

A computer-implemented method for reducing a computational effort of finding a solution of a first model modeling a real-world scenario is presented. The first model has model variables and is defined by a set of rules comprising a first subset of rules and a second subset of rules, wherein each rule of the set of rules defines at least one condition for at least one model variable. A set of relaxed rules is built by relaxing each rule of the first subset of rules of the first model, wherein relaxing a rule comprises modifying at least one condition of said rule. Further, an initial model is constructed using the set of relaxed rules and the second subset of rules. A solution of the initial model is computed, wherein the solution of the initial model is a set of model variables satisfying each rule defining the initial model. For each rule in the first subset of rules, it is determined if the solution of the initial model satisfies the rule. If the solution of the initial model does not satisfy the rule, a cut for the rule is determined and the cut is stored in a set of initial possible cuts of the initial model, wherein a cut is a constraint on at least one model variable of the rule. If the set of initial possible cuts of the initial model is empty, the solution of the initial model is stored as a solution of the first model.

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