The goal of this literature review is to give an update on the recent developments for semi-
infinite programs (SIPs), approximately over the last 20 years. An overview of the different …

We study a variant of the pessimistic bilevel optimization problem, which comprises
constraints that must be satisfied for any optimal solution of a subordinate (lower-level) …

An algorithm is proposed for locating a feasible point satisfying the KKT conditions to a
specified tolerance of feasible inequality-path-constrained dynamic programs (PCDP) within …

For univariate functions, we compute optimal breakpoint systems subject to the condition
that the piecewise linear approximator, under-, and over-estimator never deviate more than …

The algorithm proposed in Mitsos (Optimization 60 (10–11): 1291–1308, 2011) for the global
optimization of semi-infinite programs is extended to the global optimization of generalized …

A discretization-based algorithm for the global solution of semi-infinite programs (SIPs) is
proposed, which is guaranteed to converge to a feasible, ε ε-optimal solution finitely under …

Discretization-based algorithms are proposed for the global solution of mixed-integer
nonlinear generalized semi-infinite (GSIP) and bilevel (BLP) programs with lower-level …

Solving convex semi-infinite programming (SIP) problems is challenging when the
separation problem, namely, the problem of finding the most violated constraint, is …

The optimal solution in dynamic optimization of batch processes often exhibits active path
constraints. The goal of this work is the robust satisfaction of path constraints in the presence …

Informed learning is an emerging field in machine learning that aims to compensate for
insufficient data with prior knowledge. Shape knowledge covers many types of prior …