Research on flexible job-shop scheduling problem in green sustainable manufacturing based on learning effect

Journal of Intelligent Manufacturing - As one of the manufacturing industries with high energy consumption and high pollution, sand casting is facing major challenges in green manufacturing. In...     

制造网格资源调度及安全性管理

根据制造网格发展的现状和方向,分析了网格资源调度的主要方法,并对Globus环境下的GSI体系结构做了深入研究,分析讨论了其任务提交执行过程和架构特点,对现有的GSI架构基础做了相关改进,构建了一个满足制造网格下部分特性的安全体系结构M-GSI,实现了实时认证和强授权功能,满足了制造网格部分安全需求。     

基于改进蚁群算法的TT&C资源配置方法

研究了航天测控网资源配置问题,它是在航天器一地面站有限的时间窗口内对航天器的测控任务进行合理的配置,给每个任务分配一个开始执行时间,在给定的调度时间下,使得任务完成的目标值最大.将引入了杂交算子的蚁群算法来求解该问题,合理地构造了与问题相适应的杂交算子和杂交段.具体的仿真实例表明,在相同的约束条件下该算法总是能最大化地完成任务,并且求得的目标值也有很大的改进.     

An interoperable adaptive scheduling strategy for knowledgeable manufacturing based on SMGWQ-learning

To address the uncertainty of production environment in knowledgeable manufacturing system, an interoperable knowledgeable dynamic-scheduling system based on multi-agent is designed, wherein an adaptive scheduling mechanism based on the state membership grade weighted Q-learning (known as SMGWQ-learning) is proposed for guiding the equipment agent to select proper scheduling strategy in a dynamic environment. To avoid the side effect of large state space and minimize errors between the clustering and real states, the state membership grade, defined as weight coefficients, is incorporated into the weighted Q-value update so that several Q-values can be updated simultaneously in an iteration. Results from our convergence analysis and simulation experiments show the effectiveness of the proposed strategy that endows the scheduling system with higher intelligence, interoperability and adaptability to environmental changes by self-learning.     

基于BS-GA的资源约束多项目调度问题研究

针对资源约束的多项目调度问题(RCMPSP),考虑到项目、项目任务和资源各自之间的差异性,引入项目权重系数、活动质量因子和资源能力系数3个概念,提出了一个工期与质量的均衡优化模型.该模型根据资源的配置计划,确定了项目任务的资源平均能力系数,然后用项目权重系数和活动质量因子计算出多项目的单位工期时间内资源平均能力系数,利...     

A new approach to scheduling in manufacturing for power consumption and carbon footprint reduction

Manufacturing scheduling strategies have historically emphasized cycle time; in almost all cases, energy and environmental factors have not been considered in scheduling. This paper presents a new mathematical programming model of the flow shop scheduling problem that considers peak power load, energy consumption, and associated carbon footprint in addition to cycle time. The new model is demonstrated using a simple case study: a flow shop where two machines are employed to produce a variety of parts. In addition to the processing order of the jobs, the proposed scheduling problem considers the operation speed as an independent variable, which can be changed to affect the peak load and energy consumption. Even with a single objective, finding an optimal schedule is notoriously difficult, so directly applying commercial software to this multi-objective scheduling problem requires significant computation time. This paper calls for the development of more specialized algorithms for this new scheduling problem and examines computationally tractable approaches for finding near-optimal schedules.     

Deadlock-free genetic scheduling algorithm for automated manufacturing systems based on deadlock control policy

Deadlock-free control and scheduling are vital for optimizing the performance of automated manufacturing systems (AMSs) with shared resources and route flexibility. Based on the Petri net models of AMSs, this paper embeds the optimal deadlock avoidance policy into the genetic algorithm and develops a novel deadlock-free genetic scheduling algorithm for AMSs. A possible solution of the scheduling problem is coded as a chromosome representation that is a permutation with repetition of parts. By using the one-step look-ahead method in the optimal deadlock control policy, the feasibility of a chromosome is checked, and infeasible chromosomes are amended into feasible ones, which can be easily decoded into a feasible deadlock-free schedule. The chromosome representation and polynomial complexity of checking and amending procedures together support the cooperative aspect of genetic search for scheduling problems strongly.     

网格经济模型下基于信誉度的资源调度策略

基于资源的信誉度,提出一种经济模型下的网格资源调度策略.由用户自己设定各因素的重要性,调度器根据用户提交任务的需求不同,将任务放到对应的任务队列中,各队列调用不同的调度算法,以得出最优资源分配.同时每次任务完成后,用户的满意度又直接影响到资源的信誉度.理论上能够实现资源和消费者的有效匹配,使消费者请求达到快速响应,让资源提供者和消费者双方获得更高的满意度.     

Improved methods for scheduling flexible manufacturing systems based on Petri nets and heuristic search

This paper proposes and evaluates two improved Petri net （PN）-based hybrid search strategies and their applications to flexible manufacturing system （FMS） scheduling. The algorithms proposed in some previous papers, which combine PN simulation capabilities with A＊ heuristic search within the PN reachability graph,may not find an optimum solution even with an admissible heuristic function. To remedy the defects an improved heuristic search strategy is proposed, which adopts a different method for selecting the promising markings and reserves the admissibility of the algorithm. To speed up the search process, another algorithm is also proposed which invokes faster termination conditions and still guarantees that the solution found is optimum. The scheduling results are compared through a simple FMS between our algorithms and the previous methods. They are also applied and evaluated in a set of randomly-generated FMSs with such characteristics as multiple resources and alternative routes.     

LTE系统下行基于调度度量值的资源分配方案

在多业务的正交频分多址(OFDMA)蜂窝系统中,为改善小区整体的吞吐量并提高多用户之间传输数据的公平性,提出一种基于最优调度优先级进行资源块分配的长期演进项目(LTE)下行分配方案。打破传统资源分配过程中顺序分配资源的束缚,将用户与资源块(RB)配对,优先把服务质量最好的RB资源分配给相应的用户,尽量保证用户在各自有利的信道上传输数据。仿真结果表明,该方案在不增大丢包率的前提下,有效提高了系统的吞吐量和公平性指数,对LTE下行链路是一个很好的选择。     

Knowledge based system for scheduling and control of an automated manufacturing cell

Cell Manager (Cm) is a prototype knowledge based system for real-time control and short-term planning of an automated manufacturing facility. It uses background of mathematical programming, simulation, and heuristic search. The Cm engine allows tracking of time related events and facts in discrete or continuous time. The use of Cm is illustrated on a cell that processes discrete batches of parts. There are four workstations and the material handling system consists of automated guided vehicles.     

基于能耗的分簇频谱感知方法

在协作频谱感知中,当信道经历衰落和阴影时,各用户的感知性能会有不同程度影响,某些受影响严重的次用户甚至可能会严重影响到整个感知网络的性能.同时参与协作的用户数越多,认知传感器网络面临的问题越大.为了解决这些问题,提出了一种基于能耗的分簇协作感知算法.该算法引入基于节点能量的LEACH分簇算法,将认知传感器网络中的各个节点按该分簇算法分入若干簇内;在每个簇内,构造了同时考虑检测性能和能量消耗的效用函数,基于该效用函数对最佳协作用户数和用户进行选择,使每个簇内的检测性能和能耗达到很好的折中;在汇聚节点运用OR规则将簇头发送过来的感知信息进行融合,得到最终判决结果.仿真结果表明,该基于能耗的分簇协作频谱感知算法可以有效地延长认知传感器网络的生存时间,节省网络的能耗,并且保证良好的检测性能.     

基于能耗优化的AODV路由协议

在无线传感器网络中,为了优化和平衡各节点的能量消耗从而达到延长了网络寿命的目的,提出了一种基于能耗优化的AODV(E-AODV)路由协议。E-AODV优先选择剩余能量较高的节点参与路由同时选择能耗相对较小的路径作为路由,引进了被动更新路由和动态调整发射功率两种机制。NS-2仿真结果表明:与传统AODV相比,E-AODV降低了网络的整体能耗,有效均衡使用各节点的能量,延长了网络寿命。     

A dynamic scheme for scheduling complex tasks in manufacturing systems based on collaboration of agents

The characteristics of scheduling tasks in the real world is a dynamic and challenging issue as the processes and the companies involved may change from time to time. For small flexible enterprises to respond to business opportunities, an effective scheme to facilitate dynamic coalition, share the core competencies and resources and support inter-enterprise collaboration must be developed. Although multi-agent systems (MAS) provide a paradigm for modeling these characteristics, scheduling tasks in MAS is a complex problem due to the computational complexity involved, distributed architecture for scheduling tasks by individual agents and dependency of different agents’ workflows. How to develop a problem solver that can be applied in MAS to achieve coherent and consistent workflow schedules that can meet a customer’s order is an important issue. In this paper, we propose a solution methodology for scheduling workflows in MAS. Our solution combines the multi-agent system architecture to dynamically discover services, workflow and activity models to specify the capabilities of agents, contract net protocol to facilitate negotiation and coordination of agents and optimization theories to optimize the cost for fulfilling an order. A problem solver for scheduling tasks in MAS has been implemented. An application scenario has also been provided to verify our solution methodology.     

A maximum principle based combined method for scheduling in a flexible manufacturing system

A continuous time dynamic model of discrete scheduling problems for a large class of manufacturing systems is considered in the present paper. The realistic manufacturing based on multi-level bills of materials, flexible machines, controllable buffers and deterministic demand profiles is modeled in the canonical form of optimal control. Carrying buffer costs are minimized by controlling production rates of all machines that can be set up instantly. The maximum principle for the model is studied and properties of the optimal production regimes are revealed. The solution method developed rests on the iterative approach generalizing the method of projected gradient, but takes advantage of the analytical properties of the optimal solution to reduce significantly computational efforts. Computational experiments presented demonstrate effectiveness of the approach in comparison with pure iterative method.     

一种基于实时电价的HEMS家电最优调度方法

提出了一种应用于家庭能量管理系统(HEMS)的基于实时电价的家电最优调度模型。该模型采用线性整数规划方法建模,分别以用电费用最省、用电费用和满意度兼顾、二氧化碳排放最少为优化目标,以用户指定的运行时间要求以及电力公司的需求响应为约束条件。该模型将家庭中可以进行调度的可中断运行电器和不可中断运行电器,以及不可调度而必须运行的电器统一考虑,同时考虑使用家庭光伏(photovoltaic,PV)发电系统并允许剩余电力上网出售。提出的调度模型不仅考虑了家庭用电的各种实际情况,而且考虑了将来电网中可再生新能源的使用以及需求响应等新技术的应用,具有重要的实际意义。最后通过仿真实验验证了提出方法的有效性。     

Stable scheduling policies for flexible manufacturing systems

In this brief note we provide a new analysis of the transient behavior of the clear-a-fraction policy of Perkins and Kumar (1989). In addition, we show that a new “clear-average-oldest-buffer” policy and a “random part selection” policy (of which “first-come-first-served” is a special case) are stable. Finally, we introduce a stable and efficient “stream modifier” that can be used to obtain network level stability results