Benchmark Platform of Particle Swarm Optimization Based on Object Oriented Programming 面向对象的粒子群优化计算性能测试平台
This paper simulates the performance of the proportion resource scheduling algorithm, by adopting the best throughput scheduling as the benchmark. The result indicates: The performance loss is very small by transforming dynamic programming to linear programming; 文中采用吞吐量最大化调度作为比较基准,仿真了比例资源调度算法的性能,结果表明:由动态规划转化为线性规划带来的性能损失很小;
PSO is applied to benchmark functions comparing with sequential quadratic programming SQP. And PSO can get the global minimum quickly while SQP is going to be trapped in local minimum point. 将PSO与序贯二次规划(SQP)算法进行对比仿真实验,求解两个标准函数优化问题,结果表明PSO能够快速有效地求得全局最小点,而SQP则很容易陷入局部极小点。
By testing benchmark problems and comparing results to commercial software, this paper has shown that the solver can handle practical convex quadratic programming problems in predictive control in high accuracy and effiency. 通过对标准问题集的测试,以及与主流商业软件的对比,证明了该软件能够快速精确地求解预测控制中的凸二次规划问题。