Summary: To use $α$-dense curves for solving an optimization problem with constraints involving integer variables. $α$-dense curves are curves in $R^n$ depending on a single variable able to approximate a compact $K\\subset R^n$ with precision $α$. It is proposed $α$-dense curves ...
The inequality constraints may be simple bound constraints on individual variables, such as x1≥ 0, or they may be more complex nonlinear constraints involving multiple variables, such as 2−x12−x22≥0. An important definition that is used throughout constrained optimization is the Lagrangian ...
Various metaheuristic algorithms have been proposed for smart charging of EVs involving either PV generation, electricity consumption or both. Genetic algorithm: A genetic algorithm (GA) is a metaheuristic algorithm inspired by the process of natural selection and commonly used to solve optimization ...
The analysis of the properties of lower-fidelity EM simulations in terms of the simulation time versus accuracy trade-offs, has been followed by a formulation of a specific optimization framework, involving convergence-driven model management scheme. In particular, the model fidelity has been selected...
Also, problems with many competing minima without a pronounced global descent towards global minimum (e.g., Bukin N.6 problem) may not be solved acceptably as in most cases they require exhaustive search or a search involving knowledge of the structure of the problem. When the problem field ...
i.e. the objective value of (7.2), measures the violation of a conic constraint involving K. Obviously dist(x,K)=0⟺x∈K. This distance measure is attractive because it depends only on the set K and not on any particular representation of K using (in)equalities. Example 7.9 Surprisingl...
EXPLAIN PARTITIONSis useful only when examining queries involving partitioned tables. For details, seeSection 17.3.4, “Obtaining Information About Partitions”. This section describes the second use ofEXPLAINfor obtaining query execution plan information. See alsoSection 12.8.2, “EXPLAINSyntax”. For...
characterizes the readout bias on each single qubit independently (involving 2 calibration circuits in the minimal case), while the global learning process models the readout bias of the Hilbert space expanded on all the qubits (involving 2ncalibration circuits) by capturing the readout correlation ...
We have shown that the problems involving convex and concave functions can be approximated by the LP and MIP problems, respectively, sometimes in a nifty way. Then, in Section 4.4, we have discussed the problems involving the budget constraint on links cost rather than minimizing the links cost...
We may, also, refer to “multiobjective optimization” problems when involving more than one objective function to be optimized simultaneously. These objectives are often conflicting and incommensurable. Usually, there is no single solution that is optimal with respect to all the used objective ...