Optimization of schedule stability and efficiency under processing time variability and random machine breakdowns in a job shop environment

The ability to cope with uncertainty in dynamic scheduling environments is becoming an increasingly important issue. In such environments, any disruption in the production schedule will translate into a disturbance of the plans for several external activities as well. Hence, from a practical point of view, deviations between the planned and realized schedules are to be avoided as much as possible. The term stability refers to this concern. We propose a proactive approach to generate efficient and stable schedules for a job shop subject to processing time variability and random machine breakdowns. In our approach, efficiency is measured by the makespan, and the stability measure is the sum of the variances of the realized completion times. Because the calculation of the original measure is mathematically intractable, we develop a surrogate stability measure. The version of the problem with the surrogate stability measure is proven to be NP‐hard, even without machine breakdowns; a branch‐and‐bound algorithm is developed for this problem variant. A tabu search algorithm is proposed to handle larger instances of the problem with machine breakdowns. The results of extensive computational experiments indicate that the proposed algorithms are quite promising in performance. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

Waiting time analysis for a queueing system with time‐limited service and exponential timer

We consider a single‐queue with exhaustive or gated time‐limited services and server vacations, in which the length of each service period at the queue is controlled by a timer, i.e., the server serves customers until the timer expires or the queue becomes empty, whichever occurs first, and then takes vacations. The customer whose service is interrupted due to the timer expiration may be attended according to nonpreemptive or preemptive service disciplines. For the M/G/1 exhaustive/gated time‐limited service queueing system with an exponential timer and four typical preemptive/nonpreemptive service disciplines, we derive the Laplace—Stieltjes transforms and the moment formulas for waiting times and sojourn times through a unified approach, and provide some new results for these time‐limited service disciplines. © John Wiley & Sons, Inc. Naval Research Logistics 48: 638–651, 2001.     

基于逆向强化学习的舰载机甲板调度优化方案生成方法

针对计算机辅助指挥调度舰载机甲板作业的决策过程无法脱离人参与这一特点,引入基于逆向学习的强化学习方法,将指挥员或专家的演示作为学习对象,通过分析舰载机的甲板活动,建立舰载机甲板调度的马尔可夫决策模型(MDP)框架;经线性近似,采用逆向学习方法计算得到回报函数,从而能够通过强化学习方法得到智能优化策略,生成舰载机甲板调度方案。经仿真实验验证,本文所提方法能够较好地学习专家演示,结果符合调度方案优化需求,为形成辅助决策提供了基础。     

多载波码分多址在低密度二分图上的建模与分析

多载波码分多址是移动通信重要的多址技术之一,传统方法将扩频序列的构造和多用户检测单独考虑,未能做到发射机和接收机的一体化设计。受到低密度奇偶校验码的启发,基于图论建立多载波码分多址收发机模型,采用二分图定义码片和数据符号间的扩频关系。在此基础上,利用适合低密度二分图的消息传递算法完成多用户迭代检测,推导并分析洪水消息传递和串行消息传递两种检测机制。仿真结果表明,当传统的多载波码分多址系统陷入严重过载而不能正常通信的情况下,基于低密度二分图的多载波码分多址系统依然能够达到理想的传输性能,为下一代移动通信系统的设计提供了有益的参考。     

Scheduling of depalletizing and truck loading operations in a food distribution system

This paper studies a scheduling problem arising in a beef distribution system where pallets of various types of beef products in the warehouse are first depalletized and then individual cases are loaded via conveyors to the trucks which deliver beef products to various customers. Given each customer's demand for each type of beef, the problem is to find a depalletizing and truck loading schedule that fills all the demands at a minimum total cost. We first show that the general problem where there are multiple trucks and each truck covers multiple customers is strongly NP‐hard. Then we propose polynomial‐time algorithms for the case where there are multiple trucks, each covering only one customer, and the case where there is only one truck covering multiple customers. We also develop an optimal dynamic programming algorithm and a heuristic for solving the general problem. By comparing to the optimal solutions generated by the dynamic programming algorithm, the heuristic is shown to be capable of generating near optimal solutions quickly. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2003     

调度感知同步数据流建模

对流应用系统进行吞吐量分析需要将周期静态顺序调度建模到数据流图中,吞吐量分析效率依赖于数据流图的规模及建模时间。为了提高吞吐量分析效率,提出基于同构同步数据流图的调度感知同步数据流模型及相应建模方法。通过利用应用模型结构特征及周期静态顺序调度,可减少模型中的任务、边和初始符号数目;可以使用已有分析方法对模型进行吞吐量分析。实验结果表明,所提建模方法优于已有方法,可有效提高吞吐量分析效率。     

Proactive release procedures for just‐in‐time job shop environments,subject to machine failures

In this paper, we consider just‐in‐time job shop environments (job shop problems with an objective of minimizing the sum of tardiness and inventory costs), subject to uncertainty due to machine failures. We present techniques for proactive uncertainty management that exploit prior knowledge of uncertainty to build competitive release dates, whose execution improves performance. These techniques determine the release dates of different jobs based on measures of shop load, statistical data of machine failures, and repairs with a tradeoff between inventory and tardiness costs. Empirical results show that our methodology is very promising in comparison with simulated annealing and the best of 39 combinations of dispatch rules & release policies, under different frequencies of breakdowns. We observe that the performance of the proactive technique compared to the other two approaches improves in schedule quality (maximizing delivery performance while minimizing costs) with increase in frequency of breakdowns. The proactive technique presented here is also computationally less expensive than the other two approaches. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

资源不确定军事任务计划预测调度模型与算法

针对军事任务计划执行环境中普遍存在的资源不确定性,提出了基于资源缓冲区的军事任务计划预测调度算法。算法首先基于平台有效资源功能向量进行任务—平台分配,分配过程中通过调节平台有效资源功能向量,获得不同的平台资源缓冲区分配方案;然后基于NSGA-Ⅱ算法框架对军事任务计划进行多目标求解,进而获得问题的Pareto最优解集。文章通过仿真算例对算法的可行性和有效性进行验证,实验结果表明,该算法能够有效求解资源不确定军事任务计划问题。     

D运输问题在物资调度中的应用

D运输问题是含离散目标约束的目标规划问题.首先将此多目标问题转化为单一目标问题,使之简化为传统的运输问题,然后使用一种相对简单的方法求解.最后结合一个实例,讨论了D运输问题在物资调度中的应用.     

进度风险的随机网络建模与仿真分析

为研究装备研制工程进度的风险分布特征,建立了包含正态分布、β分布、三角分布的随机网络进度风险分析模型,通过蒙特卡罗法仿真获得工程项目的进度估计及其统计分布特性,从而获得工程总工期的风险,并结合实例进行了分析.