Reactive power planning is an optimization problem. Solving this problem requires finding an optimal solution that minimizes an objective function while satisfying certain constraints. This paper proposes an approach for optimum reactive power dispatch throughout the power network, using the Genetic Algorithms (GA). Varying the crossover probability rate Pc and mutation probability rate Pm, the...

This is the first part of a two-part paper which introduces a general schema theory for genetic programming (GP) with subtree-swapping crossover. The theory is based on a Cartesian node reference system which makes it possible to describe programs as functions over the space N(2) and allows one to model the process of selection of the crossover points of subtree-swapping crossovers as a probabi...

Aiming at the inherent problems of swarm intelligence algorithm, such as falling into local extremum in early stage and low precision later stage, this paper proposes an improved sparrow search algorithm (ISSA). Firstly, we introduce idea flight behavior bird SSA to keep diversity population reduce probability optimum; Secondly, creatively crossover mutation genetic get better next-generation p...

Quantum site percolation as a limiting case of binary alloy is studied numerically in 2D within the tightbinding model. We address the transport properties in all regimes ballistic, diffusive (metallic), localized and crossover between the latter two. Special attention is given to the region close to the conduction band center, but even there the Anderson localization persists, without signs of...

In this paper we use a recently proposed elastic model in order to study the competition between linear photoexcitation and cooperative relaxation in spin-crossover molecular magnets. The difference in molecular size between the two possible spin states, that is, the high-spin and the low-spin states, respectively, induces distortions of the crystal lattice. These determine the elastic interact...

Quantum-behaved particle swarm optimization (QPSO) algorithm is a variant of the traditional particle swarm optimization (PSO). The QPSO that was originally developed for continuous search spaces outperforms the traditional PSO in search ability. This paper analyzes the main factors that impact the search ability of QPSO and converts the particle movement formula to the mutation condition by in...

We present a new type of sat problem called the k-gd-sat, which generalizes k-sat and gd-sat. In k-gd-sat, clause lengths have geometric distribution, controlled by a probability parameter p; for p = 1, a k-gd-sat problem is a k-sat problem. We report on the phase transition between satisfiability and unsatisfiability for randomly generated instances of k-gd-sat. We provide theoretical analysis...

The survival probability of a particle diffusing in the two-dimensional domain x > 0 near a "windy cliff" at x = 0 is investigated. The particle dies upon reaching the edge of the cliff: In addition to diffusion, the particle is influenced by a steady "wind shear" with velocity v(x,y)=vsign (y)~, i.e., no average bias either toward or away from the cliff. For this semi-infinite system, the part...

Work fluctuations and work probability distributions are fundamentally different in systems with shortranged versus long-ranged correlations. Specifically, in systems with long-ranged correlations the work distribution is extraordinarily broad compared to systems with shortranged correlations. This difference profoundly affects the possible applicability of fluctuation theorems like the Jarzyns...

We develop an analytical diffusion-equation-type approximation scheme for the one-dimensional coagulation reaction A + A → A with partial reaction probability on particle encounters which are otherwise hard-core. The new approximation describes the crossover from the mean-field rate-equation behavior at short times to the universal, fluctuation-dominated behavior at large times. The approximati...