一种热集成系统的动态多智能体微分进化算法

Optimization of Heat Integration in Dynamic Multi-agent Differential Evolution Algorithm

针对热集成系统换热网络存在的严重非凸非线性与多维多极值问题,提出动态多智能体微分进化算法.结合动态更新策略,并引入多智能体算法的环境感知能力,改进微分进化算法的种群生成方式与变异机制,并增强在大规模复杂非线性系统中的全局搜索能力.通过10SP2与9SP1换热网络经典算例优化,得到最佳年综合费用,体现出了改进算法更优的全局搜索能力.

For optimization problem of heat integration system,serious nonlinear and non-convex heat exchanger network belonging to multi-extremum and multi-dimensional problems are considered. Dynamic multi-agent differential evolution algorithm is provided to solve the problem. It makes use of sensing capability of multi-agent with dynamic update strategy,which improves formation mechanism of population and mutation mechanism of differential evolution algorithm and globle searching ability in large scale nonlinear system.The algorithm was applied to 10SP2 and 9SP1 cases of heat exchanger network problems. Better total annual cost is obtained,which indicates better globle searching ability of the algorithm.