To solve the premature convergence problem of the basic Yin-Yang-Pair Optimization (YYPO) algorithm, the chaos search was introduced to the algorithm to explore more areas based on the ergodicity of chaos, so as to improve the global exploration capability. Besides, based on the intricate operator of I Ching, opposition-based learning was adopted to search for the opposite solutions to the current ones in order to improve the local exploitation ability. The design of parallel programming was also added to the algorithm to make full use of computing resources such as multi-core processors. Benchmark functions were used for numerical experiments to test the performance of the improved YYPO algorithm combined with chaos search and intricate operator, namely CSIOYYPO. Experimental results show that, compared with YYPO algorithms including basic YYPO algorithm and adaptive YYPO algorithm as well as other intelligent optimization algorithms, CSIOYYPO algorithm has higher calculation accuracy and higher convergence speed.

There are two problems to be solved in the traditional System Theoretic Process Analysis (STPA) method. One is the lack of automation means of realization, the other is the ambiguity problem caused by natural language result analysis. To solve these problems, a software safety requirement analysis and verification method based on STPA was proposed. Firstly, the software safety requirements were extracted and converted into formal expressions by the algorithm. Secondly, the state diagram model was built to describe the logic of software safety control behaviors and converted the logic into the readable formal language. Finally, the formal verification was carried out by model checking technology. The effectiveness of the method was verified by the case of a weapon launch control system. The results show that the proposed method can generate the safety requirements automatically and perform formal verification to them, avoid the dependence on manual intervention and solve the natural language description problems in traditional methods.

Focusing on the issue that the Road Side Unit (RSU) has inefficient response to the request of the vehicles in Vehicular Ad Hoc Network (VANET), a data scheduling algorithm based on Software Defined Network (SDN) architecture, namely SDDS, was proposed. Firstly, a graph of conflicting policies was generated based on status information of vehicles, and a maximum weighted independent set of the graph was solved to maximize the number of satisfied requests in current cycle. Secondly, the redundancy of data in vehicles was analyzed to figure out the optimum parameter, and a selection mechanism for collaborative vehicles was designed based on geographical position. Finally, the characteristics of handover vehicles and some factors that would affect the multi-RSU cooperation were analyzed, and a multi-RSU cooperation mechanism was put forward based on collision avoidance. In addition, a new evaluation indicator, service efficiency, was proposed to estimate the overall quality of service. Simulation results showed that compared with Most Requests First (MRF) and Cooperative Data Dissemination (CDD) algorithms, the service efficiency of SDDS algorithm was increased up to 15% and 20% respectively. The simulation results prove that SDDS algorithm can observably improve the sevice eficiency and quality of scheduling system.