Geometric Generalisation of Surrogate Model Based Optimisation to Combinatorial Spaces

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A Random Forest-Assisted Evolutionary Algorithm for Data-Driven Constrained Multiobjective Combinatorial Optimization of Trauma Systems (2020, methodology): “for surrogate-assisted continuous optimization are directly adopted as surrogates for mixed-integer optimization problems [35]–[37] or combinatorial optimization [38]–[40].”
Efficient global optimization for combinatorial problems (2014, methodology): “Publication rights licensed to ACM.”
Linear Combination of Distance Measures for Surrogate Models in Genetic Programming (2018, unknown): “It is straightforward to extend kernel-based models to combinatorial search spaces [6,7].”
Data-Driven Evolutionary Optimization: An Overview and Case Studies (2019, background): “However, many real-world on-line data-driven problems are constrained [54, 85, 75, 76, 34, 48] and / or of mixed-integer decision variables [68, 71, 121, 112, 99, 73, 2].”