加工时间可控的多主体调度问题

为了解决加工时间可控条件下的并行机调度问题,设计了一种基于重复叫价组合拍卖的多主体调度机制.该机制将组合拍卖的一般形式与机器调度的建模技术相结合,将可控加工时间引入竞胜标模型,使生产资源得到更加有效的配置;在价格更新方法上,设计了一种基于次梯度的自适应价格更新机制,提高了拍卖的收敛速度.对该机制进行了仿真实验.结果表明,与传统的“刚性”加工时间的调度模型相比,该机制在提高资源拥有者收益的同时,使生产资源得到了更加充分的利用.     

基于组合拍卖的半导体生产线短期调度技术研究

针对缺乏半导体生产线调度与控制分布协同机制的研究现状,建立了半导体生产线短期全局调度多代理模型,提出了基于组合拍卖的多目标短期调度协同机制,以上海某半导体制造企业152 mm晶圆生产线为实例,验证了多代理模型和协同机制的有效性。     

基于组合拍卖方法的资源受限多项目调度

为求解资源受限多项目调度问题,提出了一种基于组合拍卖机制的项目资源分配方法.该方法将单位时段的单位资源看作拍卖品,引入动态资源价格,将单个项目进度计划看作一个组合拍卖品.要求单个项目进度计划在满足任务紧前关系与资源约束的前提下,既要减少项目误期赔偿.又要降低项目资源成本.通过逐步调节不同资源在不同时段的价格,引导各项目合理利用不同时段的资源,从而解决各项目之间的资源冲突,实现资源受限多项目调度问题的整体优化.通过实际算例,演示了该方法的资源调配过程,并通过数字实验验证了该方法的有效性.     

基于多Agent的敏捷生产调度中的协商策略

为了解决基于多智能体的敏捷生产调度中资源分配的协商策略问题,提出了实现组合拍卖的协商策略的解决方法.在描述资源分配问题的基础上,基于组合拍卖解法,利用对偶理论与组合拍卖设计之间的联系,给出了组合拍卖的设计和拍卖的过程.根据设计结果和拍卖过程,采用分布规则,描述和构建实现组合拍卖的协商策略,并存储在相关智能体的规则库内.运行时,通过这些策略使资源分配问题以组合拍卖的方式得到了解决,同时对协商策略的计算复杂性和通信瓶颈进行了分析.计算实验表明,提出的协商策略是可行和有效的.     

基于Agent的生产调度混合协商策略研究

当前大多协商策略无法兼顾规划和反应能力,为此,本文提出一种短期规划与动态响应能力相结合的混合协商策略。该策略针对柔性车间生产调度问题和面对扰动的再调度问题,将组合拍卖与改进合同网相结合,通过规定相关智能体的动作和交互顺序,实现系统在平稳或扰动状态下的生产调度。基于上述协商策略,开发了一个基于智能体的生产调度原型系统,并通过仿真实验验证协商策略的可行性和有效性。     

工程机械机群多智能主体容错调度研究

以工程机械机群多智能主体系统为例,介绍了在此系统上实现的一种容错调度技术。将大型施工机群的复合主体抽象简化成三个层次的主体,具体设定了各个单机主体的功能,并结合单机智能故障诊断系统提出了以主控主体为核心的混合实时任务容错调度。通过充分利用周期任务的剩余处理机时间调度非周期任务和主动备份与被动备份相结合的方法,有效地减少了单机数,仿真结果证明了算法的有效性。     

基于信任的反拍卖式制造网格资源调度

基于市场中的竞争规律,建立制造网格(ManufactureGrid,MGrid)反拍卖式(Reverse Auction,RA)经济模型,提出了信用指数(Trust Index,TI)和服务价格(Service Price,SP)相结合的MGrid资源调度算法,实现了gridsim工具对本算法的测试,结果表明本算法在降低资源使用者(User)成本的同时,提高了MGrid反拍卖的成功率和稳定性.     

基于多代理和规则调度的敏捷调度系统研究

研究了在敏捷制造环境下制造车间过程的动态调度问题,针对敏捷化调度的特殊要求,提出了综合运用多代理机制与规则调度实现敏捷化制造车间生产过程动态调度的方法,建立了基于多代理生产组织和运行模式的生产过程动态调度系统框架结构,研究了在多代理结构的基础上实现规则调的方法,创建了适应实际生产环境的代理的模型结构,并以一类敏捷加工车间动态调度的仿真研究说明所提出方法的思路和可行性。     

基于多代理的分布式规则调度研究

针对航空制造企业生产调度系统的复杂性,提出基于多代理和规则调度构建分布式调度系统。研究了系统的体系结构,给出了系统中代理的划分和功能介绍,介绍了代理之间的控制关系、代理的实现结构及代理间的通信机制,研究了基于多代理的分布式规则调度机制,最后基于JADE(Java Agent DEvelopment Framework)构建了适用于航空制造业的分布式规则调度系统,给出了其在某航空制造企业的生产调度中应用的实例。     

基于多主体知识集成模型的智能产品报价系统

产品报价历来都是企业面向客户的一项关键和复杂的知识工作,需要综合多种信息和知识.传统的人工为主的报价方式使得报价的准确性和及时性难以保证.本文在多主体知识集成模型的基础上,建立了一个智能产品报价系统,运用网络搜索和智能.推理技术,快速形成产品报价表,并在一个光学产品的报价服务中得到了有效的应用.     

Two-agent group scheduling with deteriorating jobs on a single machine

This paper considers the two-agent scheduling problems with deteriorating jobs and group technology on a single machine, where the objective is to minimize the total completion time of the first agent with the restriction that the maximum cost of the second agent cannot exceed a given upper bound. Two agents compete to perform their respective jobs on a common single machine, and each agent has his own criterion to optimize. We introduce deteriorating jobs and group technology into the two-agent single-machine scheduling where the job processing times and group setup times are both functions of their starting times. There are two different linear deterioration functions. We propose the optimal properties and present the optimal polynomial time algorithms for two different scheduling problems, respectively.     

An investigation on single machine total weighted tardiness scheduling problems

The urge to produce products in the production line at a faster rate with no compromise in quality has led to scheduling gaining greater importance in the modern day industries. Scheduling is concerned with the allocation of limited resources to tasks over time. The investigations on various scheduling problems have been of constant interest to researchers worldwide. This paper deals with an investigation on the total weighted tardiness of the single machine scheduling problems. The problems are solved by a heuristic procedure, namely backward forward heuristics. The different methods of formulating the problem instances are discussed. The benchmark problems and their best known values available in the OR library are used for the comparison to find out the influence of Relative Due Date (RDD) and Tardiness Factor (TF) used to generate the problem instances.     

A meta-heuristic approach to single machine scheduling problems

A new meta-heuristic evolutionary algorithm, named a memetic algorithm, for solving single machine total weighted tardiness scheduling problems is presented in this paper. Scheduling problems are proved to be NP-hard (Non-deterministic polynomial-time hard) types of problems and they are not easily or exactly solved for larger sizes. Therefore, application of the meta-heuristic technique to solve such NP hard problems is pursued by many researchers. The memetic algorithm is a marriage between population-based global searches with local improvement for each individual. The algorithm is tested with benchmark problems available in the OR (operations research) library. The results of the proposed algorithm are compared with the best available results and were found to be nearer to optimal. The memetic algorithm performs better than the heuristics like earliest due date and modified due date.     

Robust and stable scheduling of a single machine with random machine breakdowns

For single-machine scheduling with random machine breakdowns, a new method considering both robustness and stability is proposed in this paper. The stability of the predictive schedule is measured by the sum of the absolute deviations between the planned job completion times and the realized ones. A surrogate measure is developed to evaluate the stability, assuming that there is only one breakdown. Generating a robust and stable schedule becomes a bi-objective optimization problem. A two-stage multi-population genetic algorithm is proposed to solve the bi-objective optimization problem. The method is applied to minimizing the total weighted tardiness of all jobs. The computational results show that the schedule generated by the proposed method is insensitive to disturbances, along with providing better robustness and stability.     

基于前序基因表达式编程的单机成组调度算法

建立了满足成组技术要求的带有提前/拖期惩罚的单机调度模型,考虑了订单达到时间不同、交货期窗口不同、机器调整时间与工件组加工顺序相关等多种情形;设计了基于基因表达式编程的多层染色体编码方案,将染色体对应于工件的优先规则公式;最后,实现了利用先进的前序基因表达式编程搜索技术求解该问题的算法,并通过实验验证了该算法的可行性和有效性.     

工件加工随机调度中优先约束问题的研究

讨论工件加工时间为任意随机分布的随机变量的单机随机调度问题,设工件间的约束为树优先约束,目标函数为极小化加权完工时间和的数学期望.这一模型在机械设计与制造行业中的多个元器组件加工,以及钢铁板坯轧制等众多实际生产制造领域中都具有广泛的应用背景.证明了工件加工时间为任意随机分布的随机变量的情况下,最大家庭树中的工件优先于家庭树中其它的工件加工,并且其工件连续加工所得到的调度为最优调度,给出了最优多项式算法,该算法可以被推广应用于实际的生产中,具有较强的实际应用性.     

基于工序约束并行机模型的冲压线调度

根据双向冲压线的实际生产特点,提出了一种基于工序约束并行机的双向冲压线调度模型.在该模型中,工件同时在牛产线两端按设备顺序加工,且加工工件及其加工开始时间和完工时间受生产线两端工件工序数目约束和生产线设备加工能力的约束,给出了该约束的规则;设计了启发规则和遗传算法混合的求解算法.最后,以最大完工时间为优化指标进行验证,证明该模型具有较好的实用价值.     

A fuzzy multi-objective programming for scheduling of weighted jobs on a single machine

This paper considers a classic model of weighted single machine scheduling problem and aims to improve it to a real-world application through fuzzy set theory. For this purpose, processing times and due dates of jobs are defined as fuzzy numbers. In the proposed model, two objectives are considered to be minimized: average tardiness and number of tardy jobs. The objectives are converted into fuzzy statement through fuzzy arithmetic. Because the problem is NP-hard, it is proposed to solve the model through three well-known meta-heuristic algorithms as Simulated Annealing, Tabu Search, and Genetic Algorithm albeit with some modifications. Comparative analysis of algorithms is attainable through different experimented results on generated benchmark problems with different sizes and difficulties. Efficiency of the developed algorithms is analyzed on the different versions of the model which come from the assumption of different parameters and/or components. Algorithms' behaviors to managerial insights are also considered in some sensitivity analysis experiments. The obtained results show the applicability of the proposed model in real-world scheduling problems.