Simulated Annealing is a family of randomized algorithms used to solve many combinatorial optimization problems. In practice they have been applied to solve some presumably hard (e.g., NP-complete) problems. The level of performance obtained has been promising [5, 2, 6, 14]. The success of this heuristic technique has motivated analysis of this algorithm from a theoretical point of view. In par...

We study errors of quantum annealing and simulated annealing to highlight better performance of quantum annealing over simulated annealing. Quantum annealing and simulated annealing perform optimization through a quantum adiabatic evolution and a quasi-static evolution respectively. In both methods, dynamics across a phase transition plays a crucial role. The Kibble-Zurek mechanism is known as ...

In a multi-rate environment fairness is not guaranteed, there is a tradeoff between fairness and throughput in such WLANs. To reduce the tradeoff problem we construct a novel intuitive simplified mathematical model called simplified coefficient of variation (SCV) model, we use SCV model to solve the optimization tradeoff problem through power control of APs, to improve balance between proportio...

the markowitz issue of optimization can’t be solved by precise mathematical methods such as second order schematization, when real world condition and limitations are considered. on the other hand, most managers prefer to manage a small portfolio of available assets in place of a huge portfolio. it can be analogized to cardinal constrains, that is, constrains related to minimum and maximum curr...

Thousands of equipments of the wireless local access network and the mobile devices are widely used and the demand of dynamic spectrum resources is significantly growing. How to maximize the social utility in modern technique becomes an important issue. In this paper, the simulated annealing based approach which dynamically allocates the power spectrum is proposed to enhance the system efficien...

An essential aspect of efficiency control of a three-phase induction motor is the ability to generate the optimal magnetic flux required for different operating modes. In this paper, we use the genetic algorithm (GA), the particle swarm optimization algorithm (PSO) and the simulated annealing (SA) to cope with the complexity of the problem and compute feasible and quasi-optimal magnetic flux ne...