Scheduling time-dependent jobs under mixed deterioration

We consider a new model of time-dependent scheduling. A set of deteriorating jobs has to be processed on a single machine which is available starting from a non-zero time. The processing times of some jobs from this set are constant, while other ones are either proportional or linear functions of the job starting times. The applied criteria of schedule optimality include the maximum completion time, the total completion time, the total weighted completion time, the maximum lateness and the number of tardy jobs. We delineate a sharp boundary between computationally easy and difficult problems, showing polynomially solvable and NP-hard cases.     

混合分组数据下恒加试验的参数估计

本文研究了恒定心力加速寿命试验在获得混合分组数据情况下的参数估计问题.利用EM算法,扶得了参数极大似然估计的迭代式.该结果推广了分组数据场合下一般恒加试验的参数估计.     

A due-date assignment problem with learning effect and deteriorating jobs

In this paper we consider a single-machine scheduling problem with the effects of learning and deterioration. In this model, job processing times are defined by functions of their starting times and positions in the sequence. The problem is to determine an optimal combination of the due-date and schedule so as to minimize the sum of earliness, tardiness and due-date. We show that the problem remains polynomially solvable under the proposed model.     

New solution methods for single machine bicriteria scheduling problem: Minimization of average flowtime and number of tardy jobs

We consider the bicriteria scheduling problem of minimizing the number of tardy jobs and average flowtime on a single machine. This problem, which is known to be NP-hard, is important in practice, as the former criterion conveys the customer’s position, and the latter reflects the manufacturer’s perspective in the supply chain. We propose four new heuristics to solve this multiobjective scheduling problem. Two of these heuristics are constructive algorithms based on beam search methodology. The other two are metaheuristic approaches using a genetic algorithm and tabu-search. Our computational experiments indicate that the proposed beam search heuristics find efficient schedules optimally in most cases and perform better than the existing heuristics in the literature.     

考虑状态维护策略与工时恶化作用下的单机调度研究

为了解决单机调度问题,提高设备的可靠性和稳定性,根据连续故障检测和离散故障检测的特点,以最小化拖期成本和维护成本为目标,建立了考虑分段线性恶化和维护不可用时间的单机调度模型,基于系统可靠性理论研究考虑机器可靠性的单机调度问题,采用决策条件统一化处理方法对维护策略进行对比,通过单因素和双因素调参分析确定相关参数变化对生产调度优化的影响。结果表明：模型求解时间与单位时间拖期成本的减少呈近似指数级增长,单位拖期成本越大,求解速度越快;单位时间拖期成本的变化不会引起维护成本的大幅度改变,成本函数不存在柔性周期维护中的跳跃节点,不能“自适应”调节;预防性维护时间与故障小修比值对离散检测下的维护决策有较大影响。采用决策条件统一化处理方法,可减少计算时间和检测成本,较好地解决了离散故障检测中易出现的过度维护或维护不足等问题,有助于降低运营成本,提高经济效益。     

基于岗位推荐的高校实习全生命周期管理系统

鉴于目前高校难以有效管理毕业生实习过程,提出并实现了一种基于岗位推荐的实习过程全生命周期管理系统.通过梳理毕业生实习的全生命周期过程,设计了实习点选取、岗位推荐与安排、过程监管、反馈统计与综合评估等模块,构建了一种岗位推荐与实习过程全生命周期闭环动态管理系统.特别的,通过分析并抽取学生信息与职位需求信息可匹配的特征属性,基于统计学的分类思想和文本相似度算法,运用动态权值分配方法计算特征属性匹配度,实现了实习岗位的自动匹配与推荐.最后,基于特征属性匹配度算法、SSM框架与HTML5等技术开发了一套实现岗位推荐与实习过程全生命周期管理的软件系统.测试表明,该系统岗位推荐准确,运行稳定,具有一定的应用价值和推广价值.     

极小化延误工件个数的单机分组排序问题

研究了以极小化延误工件个数为目标的单机分组排序问题，证明了该问题是强ＮＰ困难的，甚至限定所有工件有单位加工时间和一致的组间调整时间也是如此。     

平行机器的分批排序问题

本文研究一类具有分批约束的平行机排序问题.在恒同机情形导出Greedy算法,在m=2情形建立了匹配算法,在两台一致机器情形讨论了2-交换算法,并得到若干计算复杂性结果。     

分组与删失数据下几何分布的参数估计

研究了当寿命分布为几何分布时,观测数据分组与可能删失的情况下的参数估计,利用EM算法求出了参数的MLE估计,在平方损失下得出了参数的Bayes估计,并应用近似Beta分布加权和的方法得出了参数的近似的Bayes置信下限.     

固壁温度对壁湍流相干结构的影响

用半导体元件对平板进行加热，用ＶＩＴＡ法和ｍｕ－ｌｅｖｅｌ法两种条件采样技术研究了固壁温度对湍流相干结构的影响，改进了Ｔｉｅｄｅｒｍａｎ等人提出的“归组”方法，并且用“归组”的ＶＩ－ＴＡ法和ｍｕ－ｌｅｖｅｌ法研究了固壁加热对湍流猝发平均周期的影响．实验结果表明，固壁加热使得湍流脉动速度均方根值变大，条件采样检测到的事件数量增多，但猝发周期维持不变