机器带不可用时间限制的简单线性恶化供应链排序问题

研究的单机供应链排序问题中, 机器有一个不可用时间限制, 工件的加工时间与恶化率及其开工时间有关, 且工件的加工不可恢复. 一个或多个完工工件可组成一个发送批由车辆发送给客户, 且在机器不可用时间限制之前完工的工件必须在限制开始之时或之前完成发送. 问题的目标是最小化总发送时间与总发送费用之和. 证明问题是NP-难的, 提出了伪多项式时间的动态规划算法. 进一步, 在确定问题目标函数值的上界及下界之后, 设计了一个完全多项式时间近似方案(FPTAS).     

工件带就绪时间的单机供应链排序问题

研究工件带就绪时间的单机供应链排序问题,即工件到达后按何种顺序在机器上加工,并将完工工件如何由运输工具发送给客户,使得生产费用与发送费用总和最少.这里,每个工件的生产费用为工件的发送时刻,多个工件可组成一批一次发送给客户,发送费用与发送次数成正比.对于工件允许中断加工的问题,基于SRPT规则给出多项式时间的动态规划算法求解最优序；对于工件不允许中断加工的问题,证明问题是强NP难的,并提出了性能比为2的近似算法.     

极小化总完工时间的同时加工排序

讨论了并行工件同时加工排序问题,即n个同时到达的工件在m台批处理机上排序的问题.批处理机一次最多能加工B个工件.每批的加工时间等于该批中所含工件的加工时间的最大者.主要考虑B n的特殊情况,即每批可包含任意多个工件,目标函数是极小化总完工时间.首先对同型批处理机的情况给出了动态规划算法,算法的运行时间为O(m nm+1),并进一步将结论推广到同类批处理机的情况.     

有使用限制的二台机器流水作业问题

本文研究了机器有使用限制的二台机器流水作业排序问题,目标为最小化最大完工时间,工件加工可以被机器的不可用时间段中断。我们讨论了两台机器上均有使用限制离线问题的可近似情形,并给出了性能比为3/2的近似算法。同时我们还考虑了在第二台机器上存在一个不可用时间段情况下的半在线问题,给出了一个竞争比为3/2的半在线算法。     

工作有到达时间且拒绝工件总个数受限的单机平行分批排序问题的近似算法

考虑了工件有到达时间且拒绝工件总个数不超过某个给定值的单机平行分批排序问题.在该问题中,给定一个工件集和一台可以进行批处理加工的机器.每个工件有它的到达时间和加工时间;对于每个工件来说要么被拒绝要么被接受安排在机器的某一个批次里进行加工;一个工件如果被拒绝,则需支付该工件对应的拒绝费用.为了保证一定的服务水平,要求拒绝工件的总个数不超过给定值.目标是如何安排被接受工件的加工批次和加工次序使得其最大完工时间与被拒绝工件的总拒绝费用之和最小.该问题是NP-难的,对此给出了伪多项式时间动态规划精确算法,2-近似算法和完全多项式时间近似方案.     

工件有到达时间且拒绝工件总个数受限的单机平行分批排序问题的近似算法

考虑了工件有到达时间且拒绝工件总个数不超过某个给定值的单机平行分批排序问题.在该问题中,给定一个工件集和一台可以进行批处理加工的机器.每个工件有它的到达时间和加工时间;对于每个工件来说要么被拒绝要么被接受安排在机器的某一个批次里进行加工;一个工件如果被拒绝,则需支付该工件对应的拒绝费用.为了保证一定的服务水平,要求拒绝工件的总个数不超过给定值.目标是如何安排被接受工件的加工批次和加工次序使得其最大完工时间与被拒绝工件的总拒绝费用之和最小.该问题是NP-难的,对此给出了伪多项式时间动态规划精确算法,2-近似算法和完全多项式时间近似方案.     

工件按加工长度不增序到达的最小化最大流程在线分批排序

研究单处理机工件按加工长度不增顺序到达的在线分批排序问题．工件按时在线到达,目标是最小化最大流程．流程时间是指工件的完工时间与到达时间的差值,它体现了工件在系统内的逗留时间．对于批容量有界的情形,给出了一个竞争比为1＋√5/2的最好可能的在线算法;对于批容量无界的情形,给出了一个竞争比为√2的最好可能的在线算法．     

两台带服务等级的可拒绝同型机排序问题的在线算法

两台同型机M_1,M_2, 加工速度一致, 但拥有不同的加工能力,用其服务等级表示, M_1的服务等级为1, M_2的服务等级为2. 工件j按列表在线到达,每个工件带有三个参数: 长度t_j,等级g_j=1或2, 罚值p_j. 当j到达时, 可以被拒绝, 但要付出相应的罚值p_j, 也可以被接受并分配给服务等级不超过该工件等级的机器加工,事实上等级为1的工件只能分给M_1加工, 等级为2的工件可以分给M_1或M_2加工, 加工不允许中断. 目标为极小化加工工件集的最晚完工时间(makespan)和拒绝工件集的总罚值之和. 对于该问题给出了一个在线算法, 其竞争比为11/6, 以及问题一个下界5/3.     

平行机中关于关于同类机近似算法的研究

我们考虑平行机排序问题中的这样一类:机器两台,类型一样,但效率不同.其中n个工件在第一台机器上的加工时间分别为p1,p2,…,Pn,在第二台机器上的加工时间分别为αρ1,αρ2,…,αρn,其中0<α≤1.每台机器上的工件总数不受限制.n个工件的权分别为w1,w2,…,wn,我们的目标是如何在这两台机器上安排这n个工件以及如何确定每台机器上工件加工的先后顺序,使得这n个工件的完工时间的总权和 达到最小.该问题记为 .对于这个问题,我们给出一个1.1755近似算法.     

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.     

工件可转包加工的排序问题研究

研究工件可以转包加工的单台机排序问题: 有n个工件, 在零时刻已经到达一个单台机处, 每个工件可以由加工者自有的单台机器加工或者转包给其他机器加工. 如果工件被转包加工, 那么其完工时间等于在自有机器上的加工时间, 而产生的加工费用与在自有机器上加工的费用不同. 假设被转包加工的工件的完工时间和加工费用与转包加工机器的总负载没有关系.目标函数是最小化工件最大完工时间与总加工费用的加权和. 该问题已经被证明是NP-难的. 最后给出该问题的伪多项式时间最优算法, 并且提出一个完全多项式时间近似方案(FPTAS).     

Single-machine common due window assignment and scheduling to minimize the total cost

In this paper we consider a single-machine common due window assignment and scheduling problem with batch delivery cost. The starting time and size of the due window are decision variables. Finished jobs are delivered in batches. There is no capacity limit on each delivery batch, and the cost per batch delivery is fixed and independent of the number of jobs in the batch. The objective is to find a job sequence, a delivery date for each job, and a starting time and a size for the due window that jointly minimize the total cost comprising earliness, weighted number of tardy jobs, job holding, due window starting time and size, and batch delivery. We provide some properties of the optimal solution and present polynomial-time algorithms for the problem.     

同时具有学习效应和退化效应的单机排序问题

本文给出了一种同时具有一般化学习效应和退化效应的单机排序模型。在此模型中,工件的实际加工时间既与工件所在位置又与其开工时间有关,且工件在加工之后具有一个配送时间。其中学习效应是工件所在位置的函数,退化效应是工件开工时间的函数。证明了极小化最大完工时间和极小化总完工时间问题是多项式可解的,在满足一定的条件下,极小化加权总完工时间和极小化最大延误问题也是多项式可解的。推广了一些已有文献中的结论。     

Logistics scheduling with batching and transportation

This paper studies a general two-stage scheduling problem, in which jobs of different importance are processed by one first-stage processor and then, in the second stage, the completed jobs need to be batch delivered to various pre-specified destinations in one of a number of available transportation modes. Our objective is to minimize the sum of weighted job delivery time and total transportation cost. Since this problem involves not only the traditional performance measurement, such as weighted completion time, but also transportation arrangement and cost, key factors in logistics management, we thus call this problem logistics scheduling with batching and transportation (LSBT) problem.     

带有退化效应和序列相关运输时间的排序问题

考虑带有退化效应和序列相关运输时间的单机排序问题. 工件的加工时间是其开工时间的简单线性增加函数. 当机器单个加工工件时, 极小化最大完工时间、(加权)总完工时间和总延迟问题被证明是多项式可解的, EDD序对于极小化最大延迟问题不是最优排序, 另外, 就交货期和退化率一致情形给出了一最优算法. 当机器可分批加工工件时, 分别就极小化最大完工时间和加权总完工时间问题提出了多项式时间最优算法.     

On-line supply chain scheduling problems with preemption

We consider supply chain scheduling problems where customers release jobs to a manufacturer that has to process the jobs and deliver them to the customers. The jobs are released on-line, that is, at any time there is no information on the number, release and processing times of future jobs; the processing time of a job becomes known when the job is released. Preemption is allowed. To reduce the total costs, processed jobs are grouped into batches, which are delivered to customers as single shipments; we assume that the cost of delivering a batch does not depend on the number of jobs in the batch. The objective is to minimize the total cost, which is the sum of the total flow time and the total delivery cost. For the single-customer problem, we present an on-line two-competitive algorithm, and show that no other on-line algorithm can have a better competitive ratio. We also consider an extension of the algorithm for the case of m customers, and show that its competitive ratio is not greater than 2m if the delivery costs to different customers are equal.     

Approximation schemes for parallel machine scheduling with availability constraints

We investigate the problems of scheduling n weighted jobs to m parallel machines with availability constraints. We consider two different models of availability constraints: the preventive model, in which the unavailability is due to preventive machine maintenance, and the fixed job model, in which the unavailability is due to a priori assignment of some of the n jobs to certain machines at certain times. Both models have applications such as turnaround scheduling or overlay computing. In both models, the objective is to minimize the total weighted completion time. We assume that m is a constant, and that the jobs are non-resumable.For the preventive model, it has been shown that there is no approximation algorithm if all machines have unavailable intervals even if w_i=p_i for all jobs. In this paper, we assume that there is one machine that is permanently available and that the processing time of each job is equal to its weight for all jobs. We develop the first polynomial-time approximation scheme (PTAS) when there is a constant number of unavailable intervals. One main feature of our algorithm is that the classification of large and small jobs is with respect to each individual interval, and thus not fixed. This classification allows us (1) to enumerate the assignments of large jobs efficiently; and (2) to move small jobs around without increasing the objective value too much, and thus derive our PTAS. Next, we show that there is no fully polynomial-time approximation scheme (FPTAS) in this case unless P=NP.For the fixed job model, it has been shown that if job weights are arbitrary then there is no constant approximation for a single machine with 2 fixed jobs or for two machines with one fixed job on each machine, unless P=NP. In this paper, we assume that the weight of a job is the same as its processing time for all jobs. We show that the PTAS for the preventive model can be extended to solve this problem when the number of fixed jobs and the number of machines are both constants.     

考虑部分工件不可打扰的多任务调度问题研究

多任务调度问题存在于各种应用领域,如因特网服务领域,医疗领域等。经典的多任务调度模型中所有工件均可被其他等待工件打扰,且仅打扰一次。然而在生产实践过程中,有些紧急工件是不允许被其他工件打扰。在此启发下,对原有模型进行扩展,研究了在单机多任务环境下部分工件不可打扰的调度问题,模型目标包括最小化最大完工时间,最小化总完工时间,最小化最大延迟以及最小化加权提前期、拖延期和共同交货期之和。对于前三个目标给出了精确算法,对于最后一个目标给出了启发式算法。最后,对今后的研究提出了建议。