离散加工时间的可控排序问题

本文主要研究了离散加工时间的可控排序问题,目标函数是总压缩费用约束下极小化最大完工时间,对单机工件有不同到达时间以及同型机工件到达时间都相同这两个问题,我们设计了伪多项式时间的动态规划算法,并给出了相应的FPTAS算法．     

在线可中断二台机器流水作业问题

本文研究了可中断的二台机器流水作业排序问题,目标函数为最小化最大完工时间,工件实时到达,工件信息在工件到达之前不可知。我们给出了该在线问题的下界,并对问题中只有两个到达时间的特殊情况给出了3/2竞争的在线算法。     

一类一维在线单位聚类问题的随机近似算法

在给定的度量空间中, 单位聚类问题就是寻找最少的单位球来覆盖给定的所有点。这是一个众所周知的组合优化问题, 其在线版本为: 给定一个度量空间, 其中的n个点会一个接一个的到达任何可能的位置, 在点到达的时候必须给该点分配一个单位聚类, 而此时未来点的相关信息都是未知的, 问题的目标是最后使用的单位聚类数目最少。本文考虑的是带如下假设的一类一维在线单位聚类问题: 在相应离线问题的最优解中任意两个相邻聚类之间的距离都大于0.5。本文首先给出了两个在线算法和一些引理, 接着通过0.5的概率分别运行两个在线算法得到一个组合随机算法, 最后证明了这个组合随机算法的期望竞争比不超过1.5。     

一类一维在线单位聚类问题的随机近似算法

在给定的度量空间中, 单位聚类问题就是寻找最少的单位球来覆盖给定的所有点。这是一个众所周知的组合优化问题, 其在线版本为: 给定一个度量空间, 其中的n个点会一个接一个的到达任何可能的位置, 在点到达的时候必须给该点分配一个单位聚类, 而此时未来点的相关信息都是未知的, 问题的目标是最后使用的单位聚类数目最少。本文考虑的是带如下假设的一类一维在线单位聚类问题: 在相应离线问题的最优解中任意两个相邻聚类之间的距离都大于0.5。本文首先给出了两个在线算法和一些引理, 接着通过0.5的概率分别运行两个在线算法得到一个组合随机算法, 最后证明了这个组合随机算法的期望竞争比不超过1.5。     

具有错位限制且工件可退化的单机重新排序问题

重新排序问题是在原始工件已经按照某种最优规则排列时有一批新的工件到达,新工件的安排使得原始工件重新排序而产生错位.考虑了加权序列错位以及加权时间错位限制条件下具有退化工件,目标函数为最小化总完工时间和最小化总延误时间问题.工件的位置错位和时间错位限制条件下具有退化工件,目标函数为最小化总完工时间和最小化最大延迟问题.其中退化效应是指其实际加工时间是开工时间的非减函数,工件的位置错位是指重新排序过程中原始工件在原始最优序列与新到达工件所构成的新序列的加工位置之差,工件的时间错位是指重新排序过程中原始工件在原始最优序列与新到达工件所构成的新序列的完工时间之差.对以上两类问题,当权重系数或者错位限制满足特殊情况时,最优排序是原始工件集和新工件集中的工件按照退化率非减的序列排列,基于动态规划方法给出了以上几个问题的多项式时间算法或者是拟多项式算法.     

工件有尺寸且分两批到达的单机分批排序

本文首次研究了工件有尺寸大小,有到达时间的分批排序问题,这里目标函数为工件的极大完工时间．就所有工件有两个到达时间的且工件加工时间与尺寸大小一致的排序给出算法,并证明了算法的性能比不超过33/14．     

带机器准备时间的机器覆盖问题的在线、半在线算法

研究以极大化最小机器负载为目标的机器带准备时间的同型机排序问题.证明了LS算法是求解该问题的最好的在线算法,它的最坏情况界为1/m.同时给出了求解两台机的预先知道工件最大加工时间,预先知道工件集的总加工时间以及预先知道工件从大到小到达这三种情形下最好的半在线算法,这三个算法的最坏情况界分别为2/3,2/3以及3/4.     

具有服务等级的两台同型机实时在线排序

考虑具有服务等级的两台同型机在线排序问题, 其中工件带有到达时间, 目标为最小化最大完工时间, 设计了竞争比为\frac{7}{4}的在线算法.     

单体型装配问题及其算法

单核苷酸多态性(SNP)单体型装配问题就是从给定的来自某人染色体的SNP片段中去除错误,重构出尽可能与原来片段一致的单体型.这个问题有几个不同的模型最少片段去除(MFR)问题,最少SNP去除(MSR)问题以及最少错误纠正(MEC)问题.前两个问题的复杂性与算法已有一些学者研究过.第三个问题已被证明是NP完全问题,但这个问题的实际算法还没有.该文对MEC问题给出了一个分支定界算法,这个算法能得到问题的全局最优解.通过这个算法对实际数据的计算说明了MEC模型的合理性,即在一定条件下,通过修正最少的错误重构出的单体型确实是真实的单体型.由于分支定界算法对这样一个NP完全问题不能在可接受的时间内解规模较大的问题,文中又给出了求解MEC问题的两个基于动态聚类的算法,以便对规模较大的问题在可接受的时间内得到近似最优解.数值实际表明这两个算法很快,很有效.这两个算法总能得到与分支定界找到的全局最优解很接近的近似最优解.鉴于MEC问题是NP完全的,这两个算法是有效的、实际的算法.     

具有前瞻区间的两个工件组单机在线排序问题

研究具有前瞻区间的两个不相容工件组单位工件单机无界平行分批在线排序问题.工件按时在线到达, 目标是最小化最大完工时间. 在无界平行分批排序中, 一台容量无限制机器可将多个工件形成一批同时加工, 每一批的加工时间等于该批中最长工件的加工时间. 具有前瞻区间是指在时刻t, 在线算法能预见到时间区间(t,t+\beta]内到达的所有工件的信息.不可相容的工件组是指属于不同组的工件不能安排在同一批中加工.对该问题提供了一个竞争比为\ 1+\alpha 的最好可能的在线算法,其中\ \alpha 是方程2\alpha^{2}+(\beta +1)\alpha +\beta -2=0的一个正根, 这里0\leq \beta <1.     

带有拒绝的单机和同型机排序问题

研究了带有拒绝的单机和同型机排序问题. 对于单机情形, 工件的惩罚费用是对应加工时间的\alpha倍.如果工件有到达时间, 目标为最小化时间表长与惩罚费用之和, 证明了这个问题是可解的.如果所有工件在零时刻到达, 目标为最小化总完工时间与惩罚费用之和, 也证明了该问题是可解的.对于同型机排序问题, 研究了工件分两批在线实时到达的情形, 目标为最小化时间表长与惩罚费用之和.针对机器台数2和m, 分别给出了竞争比为2和4-2/m的在线算法.     

Single-machine group scheduling with time-dependent learning effect and position-based setup time learning effect

As to learning effect, it may be more appropriate to assume that position-based learning takes place during machine setups only, while sum-of-processing-time-based learning occurs in considering the experience that workers have gained from producing jobs. Thus, in this paper, we consider sum-of-processing-time-based learning on job processing time and position-based learning on setup time in single-machine group scheduling problems. The objectives are to minimize the makespan and the total completion time, respectively. We provide two polynomial time algorithms to solve the makespan minimization problems. On the other hand, we also provide two polynomial time algorithms to solve the total completion time minimization problems under certain conditions.     

Computational complexity of some scheduling problems with multiprocessor tasks

The paper is concerned with scheduling problems with multiprocessor tasks and presents conditions under which such problems can be solved in polynomial time. The application of these conditions is illustrated by two quite general scheduling problems. These results are complemented by a proof of NP-hardness of the problem with a UET task system, two parallel processors, the criterion of total completion time, and precedence constraints in the form of out-trees.     

Rescheduling with new orders and general maximum allowable time disruptions

We study the rescheduling with new orders on a single machine under the general maximum allowable time disruptions. Under the restriction of general maximum allowable time disruptions, each original job has an upper bound for its time disruption (regarded as the maximum allowable time disruption of the job), or equivalently, in every feasible schedule, the difference of the completion time of each original job compared to that in the pre-schedule does not exceed its maximum allowable time disruption. We also consider a stronger restriction which additionally requires that, in a feasible schedule, the starting time of each original job is not allowed to be scheduled smaller than that in the pre-schedule. Scheduling objectives to be minimized are the maximum lateness and the total completion time, respectively, and the pre-schedules of original jobs are given by EDD-schedule and SPT-schedule, respectively. Then we have four problems for consideration. For the two problems for minimizing the maximum lateness, we present strong NP-hardness proof, provide a simple 2-approximation polynomial-time algorithm, and show that, unless \(\text {P}= \text {NP}\), the two problems cannot have an approximation polynomial-time algorithm with a performance ratio less than 2. For the two problems for minimizing the total completion time, we present strong NP-hardness proof, provide a simple heuristic algorithm, and show that, unless \(\text {P}= \text {NP}\), the two problems cannot have an approximation polynomial-time algorithm with a performance ratio less than 4/3. Moreover, by relaxing the maximum allowable time disruptions of the original jobs, we present a super-optimal dual-approximation polynomial-time algorithm. As a consequence, if the maximum allowable time disruption of each original job is at least its processing time, then the two problems for minimizing the total completion time are solvable in polynomial time. Finally, we show that, under the agreeability assumption (i.e., the nondecreasing order of the maximum allowable time disruptions of the original jobs coincides with their scheduling order in the pre-schedule), the four problems in consideration are solvable in polynomial time.     

Minimum Global Height支撑树及相关问题

本文研究了两个组合优化问题:minimum g1obal height支撑树和minimum aveageheight支撑树问题.利用3SAT问题的时间复杂性,本文证明了这两个问题都是NP-hard的,并分别给出了一个算法,即（mgh）-算法和（mah）-算法.在非负网络中,这两个算法的时间复杂性都为O（n3）.利用第一个问题的复杂性,本文证明了minimum height支撑树问题也是NP-hard的,从而纠正了有关文献中的一个错误结论.     

Batching deteriorating items with applications in computer communication and reverse logistics

We study two deterministic scheduling problems that combine batching and deterioration features. In both problems, there is a certain demand for identical good quality items to be produced in batches. In the first problem, each batch is assigned an individual machine that requires a cost and a time to be activated. All the machines are identical, work in parallel, and always produce good quality items. All the items are available at time zero and they deteriorate while waiting for production. Deterioration results in a linear increase of time and cost of production. In the second problem, there is a single machine that produces good quality as well as defective items in batches. Each batch is preceded by a setup time and requires a setup cost. Defective items have to be reworked on the same machine. They deteriorate while waiting for rework. At a time to be decided, the machine switches from production to rework defective items of the current batch. After rework, every defective item has the required good quality. In both problems, the objective is to find batch partitioning such that a linear combination of the production cost and production completion time is minimized. The two problems are observed at computer service providers and also reverse logistics. In computer service providers, machines and items correspond to communication service channels and information transfer tasks, respectively. We reduce both problems to minimizing a function of one variable representing the number of batches. In an optimal solution of either problem, there are at most two different batch sizes. Linear time algorithms are proposed for both problems.     

具有时间与位置相关及维修限制的单机排序问题

考虑时间和位置相关的单机排序问题, 且机器具有退化的维修限制. 工件的实际加工时间是工件加工位置相关的函数, 目标函数为最大完工时间和总完工时间两个函数, 并利用匹配算法给出这两个问题的多项式时间算法. 最后得出工件满足一定条件时最大完工时间满足组平衡规则.     

Preconditioners for the pressure-correction method applied to the unsteady stokes problem

In this paper, the unsteady Stokes problem is considered and also the pressure-correction method for the problem is described. At a fixed time level, we reduce the problem to two summetric positive definite problems which depend on a time step parameter. Linear systems that arise from the problems are large, sparse, symmetric, positive definite and ill-conditioned as the time step tends to zero. Preconditioned problems based on an additive Schwarz method for solving the symmetric positive definite problems are derived and preconditioners are defined implicitly. It will be shown that the rate of convergence is independent of the mesh parameters as well as the time step size     

Single machine quadratic penalty function scheduling with deteriorating jobs and group technology

This paper considers single machine scheduling problems with group technology (GT) and deteriorating jobs. We consider the case of jobs whose processing times are a simple linear function of their starting time. The two objectives of scheduling problems are to minimize the weighted sum of squared completion times and the weighted sum of squared waiting times, respectively. We also provide polynomial time algorithms to solve these problems.     

Rescheduling problems with deteriorating jobs under disruptions

In this paper, we consider two single-machine rescheduling problems with linear deteriorating jobs under disruption. By a deteriorating jobs, we mean that the actual processing time of the job is an increasing function of its starting time. The two problems correspond to two different increasing linear function. Rescheduling means a set of original jobs has already been scheduled to minimize some classical objective, then a new set of jobs arrives and creates a disruption. We consider the rescheduling problem to minimize the total completion time under a limit of the disruption from the original scheduling. For each problem, we consider two versions. For each version, the polynomial algorithms are proposed, respectively.