协作制造环境下子任务调度的优化方法  

Optimization of subtasks scheduling in cooperative manufacturing

作　　者：林森[1] 黄江波[1] 李文翔[1] 肖兵兵[1] 危露 方奇州 

机构地区：[1]武汉科技大学信息科学与工程学院,武汉430081

出　　处：《智能计算机与应用》2017年第2期14-18,共5页Intelligent Computer and Applications

基　　金：武汉科技大学2015-2016年度大学生科技创新基金项目(15ZRA151)

摘　　要：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.

关 键 词：协作制造 任务调度 遗传算法 开销 时延 负载均衡 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]