CMA-ES for one-class constraint synthesis

ABSTRACTWe propose CMA-ES for One-Class Constraint Synthesis (CMAESOCCS), a method that synthesizes Mixed-Integer Linear Programming (MILP) model from exemplary feasible solutions to this model using Covariance Matrix Adaptation - Evolutionary Strategy (CMA-ES). Given a one-class training set, CMAESOCCS adaptively detects partitions in this set, synthesizes independent Linear Programming models for all partitions and merges these models into a single MILP model. CMAESOCCS is evaluated experimentally using synthetic problems. A practical use case of CMAESOCCS is demonstrated based on a problem of synthesis of a model for a rice farm. The obtained results are competitive when compared to a state-of-the-art method.