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     

极小化不可行量函数的Flow Shop变异问题

讨论一类Flowshop的变异问题。在这类变异问题中 ,给定一个截止工期 ,该工期比Flowshop最优调度中的最大完工时间小。讨论的问题是在全部工件的完工时间不超过截止工期的限制下 ,极小化不可行量函数。这类问题与矩阵函数因子分解有着密切联系。基于对问题的分析 ,证明了这一问题等价于单机调度中极小化类似的延迟量函数。推广了已有的结论。     

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。     

对完善我国工伤保险制度的思考

完善我国工伤保险制度的根本措施就是扩大工伤保险的范围、拓宽工伤保险基金的来源渠道，把工伤补偿与工伤预防、医疗康复、职业康复紧密地结合起来，不断提高工伤保险的管理水平。     

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.