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针对多处理器系统任务调度复杂问题,在自适应差分进化算法基础上增加惯性速度分项,提出一种称为惯性速度差分进化(IVDE)的改进算法,以避免陷入局部最优解.结合启发式任务列表,对算法的状态编码提出了处理器列表(PL)、部分偏序任务列表(PTL)和全部任务列表(CTL)等3种形式.通过求解随机生成的任务调度标准图和真实求解任务问题,进行了数值仿真验证,其中PTL-IVDE算法相比蚁群优化(ACO)算法、混合遗传算法(TLPLC-GA),能快速求得更好的任务调度方案.
In order to solve the complex task scheduling problem of multiprocessor system, an inertial velocity sub-item is added to the adaptive differential evolution algorithm, and an improved algorithm called IVDE (inertial velocity difference evolution) is proposed to avoid falling into the local optimal solution. (PL), partial partial task list (PTL) and total task list (CTL) are proposed for the state encoding of the algorithm.Through solving the randomly generated standard map of the task scheduling and the real solution Task problem, the numerical simulation is carried out. Among them, PTL-IVDE algorithm can get a better task scheduling solution than ACO algorithm and hybrid genetic algorithm (TLPLC-GA).