Mixed-Integer Nonlinear Programming (MINLP) is provided as an optimization tool. The MINLP framework is written in the Python programming language. The minimum separation distance, deck size, and non-overlapping functions of equipment are included as the MINLP constraint. The separation distances are ...
Such McCormick relaxations provide lower bounds, for example, in branch-and-bound procedures for mixed-integer nonlinear programs but have not gained much attention in PDE-constrained optimization so far. This lack of attention may be due to the distributed nature of such problems, which on the ...
SHOT is a software for solving mathematical optimization problems of the mixed-integer nonlinear programming (MINLP) class. In addition to MINLP problems, SHOT can also be used for subclasses such as NLP and MI(QC)QP. Originally SHOT was intended for convex MINLP problems only, but as of vers...
The combinatorial integral approximation (CIA) decomposition suggests solving mixed-integer optimal control problems by solving one continuous nonlinear control problem and one mixed-integer linear program (MILP). Unrealistic frequent switching can be avoided by adding a constraint on the total variation to...
Data-driven optimization Integrated planning and scheduling Bi-level programming Mixed-integer nonlinear programming 1. Introduction Contemporary process industries constitute one of the major cornerstones of the 21st-century global economy. Nevertheless, uncertainties in the financial ecosystem, stringent environ...
In general, Bonmin tackles MINLP (Mixed Integer NonLinear Programming) problems which is more general than MIQP (Mixed Integer Quadratic Programming) problems, but the performance, when specialized commercial solvers (Gurobi, CPLEX, Mosek; some potentially limited to CMIQP -> convex) are unavailable,...
Solution of Chance-Constrained Mixed-Integer Nonlinear Programming ProblemsChance ConstraintMINLPOptimizationOxidative Coupling of MethaneIn this contribution a framework for the solution of chance-constrained MINLP problems is described and tested to solve of process synthesis problems with strongly nonlinear ...
On the other hand, a set of primitive discrete directions is adopted to guarantee a thorough exploration of the integer lattice in order to escape bad local minima. A first algorithm for bound constrained problems is developed, then it is adapted to handle the presence of general nonlinear ...
(QCQP), which we show to be impractical to solve due to admitting a supremum, but not a maximum. We then introduce a restriction based on a Mixed-Integer Linear Program (MILP) which, while forsaking optimality, always admits an optimal (restricted) solution. Next, we propose an exact ...
two strategies are used: (1) if there exist only continuous variable, polytope sampler, specifically, the double description method80 is implemented; (2) if there exist integer/categorical variables, a method involving solving mixed-integer linear programming (MILP) problems sequentially is implemented...