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 ...
An overview of various mathematical optimization methods used for smart charging of EVs, involving either PV generation, electricity consumption or both are given in the following sections. In addition, specific objectives and their constraints are also discussed. The summary of studies on smart chargin...
In the majority of modern nature-inspired algorithms (PSO96, differential evolution57, firefly algorithm42, and many others), individuals in a population are generally not replaced but rather relocated in the design space using certain rules, typically involving random alterations biased towards the ...
This all leads to a need for using meta-heuristics (such as simulated annealing, simulated allocation, evolutionary algorithms, and tabu search) and the algorithms derived from them for dealing with NDPs involving integral (binary) variables and non-linear cost. With adequate heuristic methods we ...
we tried both local learning and global learning modes. The local learning process 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...
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 ...
For the same reason it is advised to replace explicit inequalities involving exp(x) with log-sum-exp variants (see Sec. 5.2.6 (Log-sum-exp)). For example, suppose we have a constraint such as t≥ex1+ex2+ex3. Then after a substitution t=et′ we have 1≥ex1−t′+ex2−t′...
“pure” data-driven models [26,27,31], and streamline-based models [21,30,38]. Finally, geological uncertainty is typically taken into account by involving an ensemble of equiprobable realizations of the reservoir [23,24,25,29]. A detailed review of water injection operation and optimization...
10B). In light of the fact that different cell types are distinguished by the outcomes of intricate and coordinated interactions involving transcription factors (TFs) and their associated target genes, we delved into the interconnectedness among transcription factors within malignant cells using SCENIC ...
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 ...