Optimum steel making cast plan with unknown cast number based on the modified discrete particle swarm optimization
基于改进离散粒子群算法的炼钢连铸最优浇次计划

An optimum furnace cast plan model with unknown cast number is presented. Based on the analysis of the difficulties in solving the problem, a pseudo traveling salesman problem(TSP) model is presented to describe the plan and scheduling model. Based on that the discrete particle swarm optimization(DPSO) can make the best of the particles local and global optima, but it has the disadvantages of slow convergence and low search precision and the inver over operator is fast converged and high precise, but it is blindfold to learn from the other particles, a novel modified discrete particle swarm optimization algorithm based on the inver over operator(IDPSO) is presented. Experiments carried out on TSP show that IDPSO achieves good results comparing with the general DPSO. It can improve both the convergence speed and solution precision. IDPSO is used to solve the optimum cast plan problem. Simulations have been carried and the results show that the pseudo traveling salesman problem is very fit for describe the model. The computation with practical data shows that the model and the solving method are very effective.