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]