An improved cross entropy algorithm for steelmaking-continuous casting production scheduling with complicated technological routes

In order to increase productivity and reduce energy consumption of steelmaking-continuous casting(SCC) production process, especially with complicated technological routes, the cross entropy(CE) method was adopted to optimize the SCC production scheduling(SCCPS) problem. Based on the CE method, a matrix encoding scheme was proposed and a backward decoding method was used to generate a reasonable schedule. To describe the distribution of the solution space, a probability distribution model was built and used to generate individuals. In addition, the probability updating mechanism of the probability distribution model was proposed which helps to find the optimal individual gradually. Because of the poor stability and premature convergence of the standard cross entropy(SCE) algorithm, the improved cross entropy(ICE) algorithm was proposed with the following improvements: individual generation mechanism combined with heuristic rules, retention mechanism of the optimal individual, local search mechanism and dynamic parameters of the algorithm. Simulation experiments validate that the CE method is effective in solving the SCCPS problem with complicated technological routes and the ICE algorithm proposed has superior performance to the SCE algorithm and the genetic algorithm(GA).

Improved suspension quality and liquid level stability in stirred tanks with Rotor-Stator agitator based on CFD simulation

The solid-liquid mixing is an important operation unit in the preparation of composites by stirring casting.High quality composite materials need good homogeneity and stable liquid level.In this work,the performances of the Rotor-Stator agitator for solid suspension in stirred tank were investigated through CFD modeling,including the homogeneity,power consumption and liquid level stability.The Eulerian-Eulerian(E-E)multiphase model and the RNG k-εturbulence model were adopted for modeling the multiphase flow and the turbulence effects,respectively.The effect of various important parameters such as stirring speed,particle size,solid loading and the use of baffles were examined.Adding a stator structure with array holes outside the rotor can optimize the flow pattern,thereby improving the mixing uniformity and liquid level stability.The homogeneity and liquid level stability attained by the Rotor-Stator agitator were better than those for the A200(an axial-flow agitator)and the Rushton(a radial-flow agitator).

A novel mapping algorithm for three-dimensional network on chip based on quantum-behaved particle swarm optimization

Mapping of three-dimensional network on chip is a key problem in the research of three-dimensional network on chip. The quality of the mapping algorithm used di- rectly affects the communication efficiency between IP cores and plays an important role in the optimization of power consumption and throughput of the whole chip. In this paper, ba- sic concepts and related work of three-dimensional network on chip are introduced. Quantum-behaved particle swarm op- timization algorithm is applied to the mapping problem of three-dimensional network on chip for the first time. Sim- ulation results show that the mapping algorithm based on quantum-behaved particle swarm algorithm has faster con- vergence speed with much better optimization performance compared with the mapping algorithm based on particle swarm algorithm. It also can effectively reduce the power consumption of mapping of three-dimensional network on chip.