A Novel Improved Bat Algorithm in UAV Path Planning

Path planning algorithm is the key point to UAV path planning scenario.Many traditional path planning methods still suffer from low convergence rate and insufficient robustness.In this paper,three main methods are contributed to solving these problems.First,the improved artificial potential field(APF)method is adopted to accelerate the convergence process of the bat’s position update.Second,the optimal success rate strategy is proposed to improve the adaptive inertia weight of bat algorithm.Third chaos strategy is proposed to avoid falling into a local optimum.Compared with standard APF and chaos strategy in UAV path planning scenarios,the improved algorithm CPFIBA(The improved artificial potential field method combined with chaotic bat algorithm,CPFIBA)significantly increases the success rate of finding suitable planning path and decrease the convergence time.Simulation results show that the proposed algorithm also has great robustness for processing with path planning problems.Meanwhile,it overcomes the shortcomings of the traditional meta-heuristic algorithms,as their convergence process is the potential to fall into a local optimum.From the simulation,we can see also obverse that the proposed CPFIBA provides better performance than BA and DEBA in problems of UAV path planning.

Probabilistically implementing nonlocal operations between two distant qutrits

We propose a method to probabilistically implement a nonlocal operation, exp[iζUAUB], between two distant qutrits A and B, where ζ∈ C [0,2π] and UA, UB are local unitary and Hermitian operations for qutrits A and B respectively. The consumptions of resource for one performance of the method are a single non-maximally entangled qutrit state and 1-trit classical communication. For a given ζ, the successful probability of the method depends on the forms of both entanglement resource and Bob＇s partial-measurement basis. We systematically discuss the optimal successful probabilities and their corresponding conditions for three cases： adjustable entanglement resource, adjustable partial-measurement basis, adjustable entanglement resource and partial-measurement basis. It is straightforward to generalize the method for producing nonlocal unitary operations between any two N-level systems.

THE OPTIMAL VARIABLE SUCCESSIVE OVER RELAXATION (OVSOR) METHOD FOR THREE-DIMENSIONAL RESERVOIR SIMULATIONS

This present paper has proved the theorem of the Point Optimal Variable Successive Over Relaxation (OVSOR) method of the three-dimensional unsteady flow in the reservoir, and has put forward a formu- la for calculating optimal parameters for OVSOR which vary with space points and time points. Using this method, internal memory of computer is the smallest, calculating work is the smallest, and calculating funds are the smallest. It is very easy to operate on microcomputers for three-dimensional res- ervoir simulation. The method is stable and convergent even if the time steps are taken to be large (for example, one year). The same applies for space steps. It is applicable both for homogeneous, isotropic porous mediums and for heterogeneous, anisotropic porous medium. On IBM microcomputers with internal memory of 512 thousand bytes, 8000 grid points may be cal- culated for three-dimensional simulation. It takes only two minutes to get convergence for one time step. It may be extended to three-dimensional heat conduction equation and three-dimensional simulation of the ground water flow. It looks much more advantageous for two-dimensional simulation.