协作制造环境下子任务调度的优化方法

Optimization of subtasks scheduling in cooperative manufacturing

协作制造模式为分布式生产设备的高效利用提供了共享合作平台,如何将生产任务高效调度到各设备中是一个复杂的优化问题。基于对任务结构和过程的分析提出子任务调度模型,使不同位置和功能的设备能协作处理一批任务。基于对生产代价和时延的建模,采用遗传算法实现3种优化调度策略,优化目标分别为设备负载均衡、最小化总生产时延和最小化总生产开销。仿真结果表明这3种策略能分别实现对应的优化目标。

Cooperative manufacturing provides a sharing and cooperation platform for efficient utilization of distributed equipments. However, effective scheduling of subtasks to these equipments is a challenging optimization problem. Based on the analysis on task decomposition and processing procedure, a subtask scheduling model is proposed, so the equipments of different locations and functions can cooperatively handle a batch of tasks. Based on the modeling of production cost and delay, three subtask-scheduling strategies are derived with Genetic Algorithm for three optimization objectives, including load-balance of equipments, minimizing overall cost and minimizing overall processing time. Simulation results demonstrate that each strategy can achieve the relevant optimization objective respectively.