复杂动态执行环境下HMS系统的重构机制与调度理论研究

Integration optimization strategy of configuration selection and scheduling methods are the fundamental issues for scheduling performance and system stability of Holonic Manufacturing System(HMS). However, high performance scheduling methods have scarcely been applied into real production circumstance due to the complexity of configuration selection and scheduling.The project will investigate the configuration programming and scheduling execution mechanism of Holonic manufacturing system. Firstly,the mathematical model of nonlinear reconfigurtaion and scheduling for HMS based on piece logistic over mobile robot will be presented. Secondly,by proposing integration optimization strategy of nonlinear reconfiguration and scheduling for HMS based on pareto optimization, this project divides the complex problems of nonlinear reconfiguration and scheduling optimization for HMS into a quadratic optimization problem including single task and multiple task. With the foundation of production disturbance under dynamic and complex environment, the project aims to build a unified relevance constriction model facing hybrid production operation by utilizing hierarchical modularized quick response mechanism upon analyzing the adjustment strategy for manufacturing resource, and realize the dynamic reconfiguration for manufacturing resource driven by production disturbance. Finally,by considering the strategy of rescheduling and configuration adjustment under disturbance such as equipment failure, job modification, rush order, the project aims at establishing a decision making framework of integration and optimization of modular reconfiguration and real time scheduling for Holonic Manufacturing System in order to provide an innovative path to the solution of reconfiguration decision making, scheduling execution and perturbation analysis of Holonic control system.

Holonic制造系统(HMS)的构型选择及调度集成优化是制造系统调度性能及系统稳定性等方面最重要的基础问题之一，但由于构型选择和调度计算的复杂性，高性能调度方法很少被应用于实际生产中。本项目拟对Holonic制造系统的构型规划及调度执行机制进行研究，建立基于移动机器人工件物流的非线性重构和调度的数学模型，提出基于Pareto最优的HMS非线性重构和调度集成优化策略，将复杂HMS系统的非线性重构和调度优化问题分解成包含单任务及多任务优化的二次优化问题；以动态、复杂生产环境下的生产扰动建模为基础，分析其对制造资源配置方案的调整策略，采取分层模块化的快速响应机制，建立面向混合型生产作业的统一关联约束模型，实现生产扰动事件驱动的制造资源动态重构配置；设计针对典型紧急事件如设备故障、作业变更、紧急订单等扰动机制下的构型调整和重调度策略，实现不确定干扰时HMS系统的构型选择、调度执行及扰动分析评估。

Holonic制造系统(HMS)的构型选择及调度集成优化是制造系统调度性能及系统稳定性等方面最重要的基础问题之一，也是制造执行系统能否高效稳定运行的“卡脖子”问题，但由于构型选择和调度计算的复杂性，高性能调度方法很少被应用于实际生产中。本项目通过对Holonic制造系统的构型规划及调度执行机制进行研究，建立了基于移动机器人工件物流的非线性重构和调度的数学模型，提出了基于Pareto最优的HMS非线性重构和调度集成优化策略，将复杂HMS系统的非线性重构和调度优化问题分解成包含单任务及多任务优化的二次优化问题；提出了一个具有问题特定知识的两阶段协同演化算法(A Two-Stage Cooperative Evolution Algorithm with Problem-specific Knowledge for Energy-Efficient Scheduling of No-wait Flow-Shop Problem, TS-CEA)，解决了带最小化工件最大完工时间和机器总能耗两个指标的零等待流水车间的节能调度问题(Energy-Efficient Scheduling of No-wait Flow-Shop Problem, EENWFSP)。通过对EENWFSP问题属性的抽象和形式化建模后，利用两种构造型启发式算法产生初始解。在TS-CEA的第一个阶段，引入迭代局部搜索策略(Iterative Local Search Strategy, ILS)搜索潜在的极值解，结合问题的混合邻域结构改善了侯选解的质量。在TS-CEA的第二个阶段，提出了一个基于关键路径知识的变异策略，用于将第一阶段获得的极值解分散到非支配前沿面。在TS-CEA的迭代过程中，ILS和变异策略形成一个协同演化的闭环系统，为EENWFSP问题提供了重要的方法体系。以动态、复杂生产环境下的生产扰动建模为基础，分析了其对制造资源配置方案的调整策略，建立了面向混合型生产作业的统一关联约束模型，实现生产扰动事件驱动的制造资源动态重构配置；设计了针对典型紧急事件如设备故障、作业变更、紧急订单等扰动机制下的构型调整和重调度策略，实现不确定干扰时HMS系统的构型选择、调度执行及扰动分析评估。本项目的研究成果对于推动制造系统自动化理论的深入研究与发展，提高制造系统的运行和决策效率都有重要意义。