Review Article
Industry 4.0-Driven Development of Optimization Algorithms: A Systematic Overview
Table 6
Types of optimization problems.
| Optimization models | Model type | Example |
| Stochastic programming | Uncertainty optimization | [69, 86–88] | Robust optimization | Uncertainty optimization | [89–91] | Global optimization | Deterministic, continuous, unconstrained/constrained optimization | [92–94] | Mixed-integer nonlinear programming | Deterministic, continuous, constrained, nonlinear programming | [95–97] | Network optimization | Deterministic, continuous, constrained optimization | [98, 99] | Derivative-free optimization | Deterministic, continuous, constrained, bound constrained optimization | [100–102] | Quadratic programming | Deterministic, continuous, constrained, linearly constrained optimization | [103–105] | Linear programming | Deterministic, continuous, constrained, linearly constrained optimization | [106–108] | Integer linear programming | Deterministic, discrete | [109–111] | Combinatorial optimization | Deterministic, discrete | [112–114] | Multiobjective optimization | — | [115–117] |
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