考虑中断的制造型供应链协调调度模型

供应链协调调度能有效提高企业应对供应链中断的能力。以两阶段制造供应链为研究对象，研究了中断情境下具有交付时间约束的多产品类型制造供应链协调调度问题。制造商接到包含多产品类型的工件加工订单，各工件需经供应商处理为原材料工件后，交付给制造商处理为完成品，各工件均有一个独立的交付期。如果供应商单方面调整工件加工顺序，会导致制造商冲突成本的增加，需双方协商处理。以最小化供应商总拖期交付成本和最小化制造商总冲突成本为目标，基于收益共享契约协调机制，构建了考虑中断的制造型供应链协调调度模型。设计了一个融合自适应邻域搜索算子的混合自适应遗传算法。通过算例仿真，验证了所提模型与算法的有效性。     

浅谈基于浸润原理的事务安排算法

针对单个安排事务避免冲突的传统方法 ,提出一种基于浸润原理的事物安排算法。该算法采用漫布式将各个事务分摊到各个位置 ,根据条件计算权值 ,并有意造成冲突 ,从而发现冲突位置 ,最后从最不可能冲突的位置入手 ,逐步完成安排过程。该方法事务安排的复杂度为 O(n2× k× x) ,大大减少事务安排所需的时间 .     

用遗传算法解决一类模糊流水车间调度问题

对同时考虑模糊加工时间和模糊交货期的模糊流水车间调度问题进行了研究 ,模糊加工时间用三角模糊数来表示 ,模糊交货期用梯形模糊数来表示。应用遗传算法搜索最优排序 ,在适应度函数处理中引入模糊数处理方法 ,以平均满意度最大作为优化目标。最后给出了实验结果和结论     

LOGISTICS SCHEDULING： ANALYSIS OFTWO-STAGE PROBLEMS

This paper studies the coordination effects between stages for scheduling problems where decision-making is a two-stage process. Two stages are considered as one system. The system can be a supply chain that links two stages, one stage representing a manufacturer; and the other, a distributor It also can represent a single manufacturer, while each stage represents a different department responsible for a part of operations. A problem that jointly considers both stages in order to achieve ideal overall system performance is defined as a system problem. In practice, at times, it might not be feasible for the two stages to make coordinated decisions due to (i) the lack of channels that allow decision makers at the two stages to cooperate, and/or (ii) the optimal solution to the system problem is too difficult (or costly) to achieve.Two practical approaches are applied to solve a variant of two-stage logistic scheduling problems. The Forward Approach is defined as a solution procedure by which the first sta     

FROM MANUFACTURING SCHEDULING TO SUPPLY CHAIN COORDINATION：THE CONTROL OF COMPLEXITY AND UNCERTAINTY

With time-based competition and rapid technology advancements, effective manufacturingscheduling and supply chain coordination are critical to quickly respond to changing marketconditions. These problems, however, are difficult in view of inherent complexity and variousuncertainties involved. Based on a series of results by the authors, decomposition and coordination byusing Lagrangian relaxation is identified in this paper as an effective way to control complexity anduncertainty.A manufacturing scheduling problem is first formulated within the job shop context withuncertain order arrivals, processing times, due dates, and part priorities as a separable optimizationproblem. A solution methodology that combines Lagrangian relaxation, stochastic dynamicprogramming, and heuristics is developed. Method improvements to effectively solve large problemsare also highlighted. To extend manufacturing scheduling within a factory to coordinate autonomicmembers across chains of suppliers, a decentralized supply chai     

SCHEDULING PROBLEMS - AN OVERVIEW

There seems to be a significant gap between the theoretical and the practical aspects of scheduling problems in the job shop environment. Theoretically, scheduling systems are designed on the basis of an optimum approach to the scheduling model. However in the practice, the optimum that is built into the scheduling applications seems to face some challenges when dealing with the dynamic character of a scheduling system, for instance machine breakdown or change of orders. Scheduling systems have become quite complex in the past few years. Competitive business environments and shorter product life cycles are the imminent challenges being faced by many companies these days. These challenges push companies to anticipate a demand driven supply chain in their business environment. A demand-driven supply chain incorporates the customer view into the supply chain processes. As a consequence of this, scheduling as a core process of the demand-driven supply chain must also reflect the customer view. In addition,     

一种求解资源受限工程调度问题的遗传算法

针对资源受限工程调度问题的特点，设计了一种改进的遗传算法，对算法的编码方式和解码规则，适值函数，遗传算法、初始种群的产生方法进行了详细的说明，利用被普遍应用的标准问题对该算法进行了大量的测试，分析了算法参数和问题参数对算法效果的影响，取得了令人满意的结果。     

A Nonprecedence－based Query Schedule Algorithm on Heterogeneous Multiprocessor System

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应用禁忌粒子群算法的车间调度及其并行化实现

为了解决批量生产、制造、装配等车间调度问题,基于Hadoop集群,提出应用禁忌粒子群算法的车间调度及其并行化实现.以某装载机制造车间最小化完成时间为目标,通过使用禁忌粒子群算法对车间调度问题进行求解.结果表明：在车间批量大的情况下,禁忌粒子群算法可得出有效的调度方案,避免算法陷入局部最优解.与现有的智能算法相比,禁忌粒子群算法更有利于实现全局最优解.     

面向时间敏感网络的安全感知调度方法

时间敏感网络（TSN）中信息的真实性是系统的关键安全要素,然而直接引入传统安全认证机制会导致系统可调度性和实时性大幅降低。现有的方法仍存在适用场景少、资源消耗高等问题。针对这些问题,文中提出了一种面向TSN的安全感知调度方法。首先基于TSN流量特性设计了一种时间有效的一次性签名安全机制,为消息提供高效的组播源认证;然后提出相应的安全模型对该机制进行评估,描述安全机制对任务和流量的影响;最后对提出的安全感知调度方法进行数学建模,在传统调度约束的基础上,增加了安全机制相关的约束,同时以最小化应用端到端时延为优化目标,使用约束规划进行求解。仿真实验结果表明：改进的一次性签名机制的引入可以有效保护TSN中关键信息的真实性,且对调度的影响有限;在多个基于真实工业场景生成的不同规模测试用例中,产生的应用端到端时延平均仅增加13.3%,带宽消耗平均仅增加5.8%;与其他同类型方法相比,文中方法的带宽消耗更低,更加适用于有严格带宽限制的TSN。