Concerning the trade-off between convergence and diversity in solving the multi-trip pickup and delivery Vehicle Routing Problem （VRP）， a hybrid Non-dominated Sorting Genetic Algorithm Ⅱ （NSGA-Ⅱ） combining Adaptive Large Neighborhood Search （ALNS） algorithm and Adaptive Neighborhood Selection （ANS）， called NSGA-Ⅱ-ALNS-ANS， was proposed. Firstly， considering the influence of the initial population on the convergence speed of the algorithm， an improved regret insertion method was employed to obtain high-quality initial population. Secondly， to improve global and local search capabilities of the algorithm， various destroy-repair operators and neighborhood structures were designed， according to the characteristics of the pickup and delivery problem. Finally， a Best Fit Decreasing （BFD） algorithm based on random sampling and an efficient feasible solution evaluation criterion were proposed to generate vehicle routing schemes. The simulation experiments were conducted on public benchmark instances of different scales， in the comparison experiments with the MA （Memetic Algorithm）， the optimal solution quality of the proposed algorithm increased by 27%. The experimental results show that the proposed algorithm can rapidly generate high-quality vehicle routing schemes that satisfy multiple constraints， and outperform the existing algorithms in terms of both convergence and diversity.

The existing two-dimensional codes have the problems of weak antipollution ability and slow decoding speed in complex environment. To solve these problems， a very short antipollution error correcting code based on global distance optimization was proposed. Firstly， a concave-convex polygon mathematical model was constructed to characterize the polluted environment. Then， a very short error correcting code was designed， which uses three coding points to represent one target data bit. Finally， a coding point arrangement method was designed， which optimizes the global distance within a limited constrained domain. The corresponding decoding algorithm was also given. The antipollution ability and recognition speed of very short error correcting code were simulated and analyzed， and the proposed code was compared with the classical Bose-Chaudhuri-Hocquenghem （BCH） codes. The results show that when the target data length is 18 and the number of coding points is 63， the recognition accuracy of very short error correcting code is close to that of BCH codes in the same polluted environment with the decoding speed of 130 times of that of BCH codes. The proposed code also has the obvious advantages of simple and clear structure， strong adaptability of coding points， and being easy to be standardized and popularized.