Nonconvex problemDifference of two convex functionsQuadratic functionsGlobal search algorithmComputational testingThis paper addresses the numerical solution of fractional programs with quadratic functions in the ratios. Instead of considering a sum-of-ratios problem directly, we developed an efficient global...doi:10.1007/978-3-030-49988-4_8Tatiana ...
The problem of maximizing the sum of m concave-convex fractional functions on a convex set is shown to be equivalent to the one whose objective function f is the sum of m linear fractional functions defined on a suitable convex set; successively, f is transformed into the sum of one linear...
The PBFT consensus algorithm was improved by Castro et al.13 based on the BFT algorithm for solving the consensus problem of distributed systems in current consortium chains. The PBFT algorithm inherits the advantages of BFT that can tolerate Byzantine nodes and reduces the communication complexity ...
Model Predictive Control (MPC) is a well-known method which has been broadly used in real industrial as an effective way of dealing with multi-variables constrained control problem. MPC depends on predictive models, which is to get the control signal by solving open-loop finite-horizon optimal ...
However, since in the model considered here with a minimal deviation of the SM solving the unitarity problem, one has a mixing where the two angles s24 = s34 = 0, some processes, as for instance D0 − D0, will now have no contributions at tree level. This is also clear from the ...
We provide a complete road map for future research on the open-shop scheduling problem. Abstract One of the basic scheduling problems, the open-shop scheduling problem has a broad range of applications across different sectors. The problem concerns scheduling a set of jobs, each of which has a...
Reinforcement Learning for Solving the Vehicle Routing Problem Mohammadreza Nazari, Afshin Oroojlooy, Lawrence V. Snyder, Martin Takáč NeurIPS 2018 Attention, Learn to Solve Routing Problems! Wouter Kool, Herke van Hoof, Max Welling ICLR 2019 Learning a SAT Solver from Single-Bit Supervision ...
The results obtained from solving the above equation is a number between 0 and 1 for each link in the network. As a(l) increases, link l contributes more to the network performance; thus, links with the highest values of a(l) have the most substantial contribution to network performance....
Self-supervised representation learning (SSL) is a promising paradigm for solving the above issues. In SSL, deep learning models are trained via pretext tasks, in which supervision signals are automatically extracted from unlabelled data without the need for manual annotation. Self-supervised representat...
However, solving the bidomain equations is computationally expensive because of the required fine spatial and temporal discretization, which limits the size and duration of the problem that can be modeled27. The monodomain model is a simplification of the bidomain model. Compared with the bidomain ...