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341.
342.
We consider a problem of scheduling jobs on m parallel machines. The machines are dedicated, i.e., for each job the processing machine is known in advance. We mainly concentrate on the model in which at any time there is one unit of an additional resource. Any job may be assigned the resource and this reduces its processing time. A job that is given the resource uses it at each time of its processing. No two jobs are allowed to use the resource simultaneously. The objective is to minimize the makespan. We prove that the two‐machine problem is NP‐hard in the ordinary sense, describe a pseudopolynomial dynamic programming algorithm and convert it into an FPTAS. For the problem with an arbitrary number of machines we present an algorithm with a worst‐case ratio close to 3/2, and close to 3, if a job can be given several units of the resource. For the problem with a fixed number of machines we give a PTAS. Virtually all algorithms rely on a certain variant of the linear knapsack problem (maximization, minimization, multiple‐choice, bicriteria). © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008 相似文献
343.
We consider a manufacturer, served by a single supplier, who has to quote due dates to arriving customers in a make‐to‐order production environment. The manufacturer is penalized for long lead times and for missing due dates. To meet due dates, the manufacturer has to obtain components from a supplier. We model this manufacturer and supplier as a two‐machine flow shop, consider several variations of this problem, and design effective due‐date quotation and scheduling algorithms for centralized and decentralized versions of the model. We perform extensive computational testing to assess the effectiveness of our algorithms and to compare the centralized and decentralized models to quantify the value of centralized control in a make‐to‐order supply chain. Since complete information exchange and centralized control is not always practical or cost‐effective, we explore the value of partial information exchange for this system. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008 相似文献
344.
利用Monte Carlo随机仿真技术,采用事件调度法的仿真策略对可修件的使用与维修过程进行仿真,给出了在给定备件和维修分队数量下批量独立可修件的备件保障概率仿真算法,并用一系列计算实例证明了算法的可行性和正确性,该算法能有效解决安装在不同装备上,具有不同已工作时间、不同故障间隔时间分布、不同修复时间分布的可修件的备件保障概率计算问题,为备件的科学储备提供了有力的决策依据。 相似文献
345.
旋转泵式鱼雷发射系统建模与仿真 总被引：1，自引：0，他引：1
介绍了由高压气瓶、发射阀、喷射式空气轮机、混流泵组成的一种新型旋转泵式鱼雷发射系统,建立了该系统的仿真模型,对鱼雷发射过程进行了仿真并对结果作了分析. 相似文献
346.
气动光学效应中调制传递函数的计算方法 总被引：1，自引：0，他引：1
从Maxwell方程出发 ,推导了光在湍流中传播的调制传递函数的计算公式。依据折射率起伏相关函数的两种形式 ,计算了光学相位差。根据湍流的动能和动能耗散率输运方程 ,建立了折射率起伏方差的计算模型。最后 ,指出了文中所给公式的适用范围 ,对更好地进行调制传递函数的计算提出了建议。 相似文献
347.
针对传统造船模式下,车间作业计划与工艺设计串行工作方式的缺点,基于并行工程的原理,提出了分段作业计划与工艺设计的集成运行模式,为实现造船CAPP系统与PPC系统的集成化和并行化提供了实现的基础。针对集成模式的特点,建立了分段作业计划系统资源优化的数学模型,应用遗传算法解决了针对任意分段装配工艺方案的多资源平衡优化问题,可以得到每项作业最优的开工时间,同时能够给出多种资源的最优分布结果,满足了多工艺方案之间资源利用率的比较。最后,给出了计算实例,计算机模拟结果说明了这一方法的有效性。 相似文献
348.
We investigate the problem of scheduling a fleet of vehicles to visit the customers located on a path to minimize some regular function of the visiting times of the customers. For the single‐vehicle problem, we prove that it is pseudopolynomially solvable for any minsum objective and polynomially solvable for any minmax objective. Also, we establish the NP‐hardness of minimizing the weighted number of tardy customers and the total weighted tardiness, and present polynomial algorithms for their special cases with a common due date. For the multivehicle problem involving n customers, we show that an optimal solution can be found by solving or O(n) single‐vehicle problems. © 2013 Wiley Periodicals, Inc. Naval Research Logistics 61: 34–43, 2014 相似文献
349.
通过对压制火炮的特点和火控系统的现状进行分析,探讨提出了压制火炮火控系统未来的改进思路,采用新型作战使用流程、简化系统硬件构成、优化人机交互界面、合理利用总线技术。这种思路基于顶层设计的理念,从作战使用与系统构成上对火控系统进行了优化与简化,通过降低系统复杂度、改善人机交互界面来提高可靠性和易用性,使火控系统具有良好的使用灵活性和扩展性,以更好地适应未来信息化战场的作战使用。 相似文献
350.
In a master surgery scheduling (MSS) problem, a hospital's operating room (OR) capacity is assigned to different medical specialties. This task is critical since the risk of assigning too much or too little OR time to a specialty is associated with overtime or deficit hours of the staff, deferral or delay of surgeries, and unsatisfied—or even endangered—patients. Most MSS approaches in the literature focus only on the OR while neglecting the impact on downstream units or reflect a simplified version of the real‐world situation. We present the first prediction model for the integrated OR scheduling problem based on machine learning. Our three‐step approach focuses on the intensive care unit (ICU) and reflects elective and urgent patients, inpatients and outpatients, and all possible paths through the hospital. We provide an empirical evaluation of our method with surgery data for Universitätsklinikum Augsburg, a German tertiary care hospital with 1700 beds. We show that our model outperforms a state‐of‐the‐art model by 43% in number of predicted beds. Our model can be used as supporting tool for hospital managers or incorporated in an optimization model. Eventually, we provide guidance to support hospital managers in scheduling surgeries more efficiently. 相似文献