两台可拒绝同类机在线排序问题近似算法的参数性能比

讨论两台可拒绝同类机在线排序问题的近似算法。设两台机器的速度之比为ｓ（≥１）。工件逐个到位,可以被加工,也可以被拒绝,但要付出相应的罚值ｐｊ。并且只有在安排完当前工件之后,下一个工件才到达。目标函数要求被加工工件集的最迟工件完工时间与被拒绝工件集的总罚值之和达到最小。文中设计出线性时间的ＲＬＳ（α）算法,并证明了其关于ｓ的参数紧界,这个界于ｓ＝１以及ｓ≥（５＋１）／２均是不可改进的。     

带服务器的三台平行机排序问题的复杂性和近似算法

讨论带有两具服务器的三台机的平行机排序问题,在这个问题的实例中,每一个工件都有一个时间长度 安装操作必须要由服务器来完成,每一个服务器在同一时刻只能安装一个工件,用三段式描述表示此问题即为Ｐ３,Ｓ２／ｓｉ＝１／Ｃｍａｘ,证明了此问题为ＮＰ－Ｃ的,分别给出了在在线和离线条件下的近似算法,并且估计了算法的最坏情况界。     

带服务器的三台平行机排序问题的复杂性和近似算法

本文研究了带服务器的三台平行机排序问题的复杂性，并给出了一个最好的在线近似算法．     

带机器准备时间的平行机ordinal排序及近似算法

本文研究带机器准备时间的m台平行机ordinal在线排序问题。讨论了在极小化最大机器完工时间和极小化最大工件完工时间两种目标下的不同下界和相应的在线近似算法。对第一个目标，我们得到了3/2的下界和最坏情况界为2-1/m的近似算法。对第二个目标，我们得到了最坏情况为m的最好近似算法。我们还对一些特殊情况进行了分析。     

最小度生成树的一种近似算法

最小度生成树问题是一个NP难问题.本文给出了求最小度生成树的一种近似算法,这种算法得到的生成树的度数比最优解至多大1.     

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.     

有尺寸的同型机分批排序问题的近似算法

对工件有不同到达时间、不同加工时间和尺寸的同型机分批排序问题寻找近似算法.对于大工件(工件的体积严格大于机器容量的÷)的加工时间不小于小工件(工件的体积小于或等于机器容量的÷)的加工时间的特定情形,利用动态规划的方法和拆分的技巧,我们设计了近似算法并分析了其最差性能比.     

目标是最小化最大完工时间带柔性维修时间限制的两台机器排序问题的一个近似算法

本文研究了两台机器带柔性维修时间限制的排序问题,其中第一台机器在固定的时间内必须进行维修,而第二台机器一直可用,目标是最小化所有工件的最大完工时间。工件在加工过程中不允许中断。对于该问题,我们给出了一个性能比为的近似算法,并证明了该性能比是紧的。     

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.     

问题Pm|rj,B|∑Cj的多项式时间近似算法

本文针对同型机分批排序问题Pm|rj,B|∑Cj进行了研究,给出了该问题在批容量B及机器台数m为常数情况下的多项式时间近似算法(以下简称PTAS);在B为常数时设计出了问题1|rj,B|∑WjCj的计算时间更少的PTAS．     

A dynamic programming algorithm for preemptive scheduling of a single machine to minimize the number of late jobs

The scheduling problem 1|pmtn, r _j |w _j U _j calls forn jobs with arbitrary release dates and due dates to be preemptively scheduled for processing by a single machine, with the objective of minimizing the sum of the weights of the late jobs. A dynamic programming algorithm for this problem is described. Time and space bounds for the algorithm are, respectively,O(nk ² W ²) andO(k ² W), wherek is the number of distinct release dates andW is the sum of the integer job weights. Thus, for the problem 1|pmtn, r _j |U _j , in which the objective is simply to minimize the number of late jobs, the pseudopolynomial time bound becomes polynomial, i.e.O(n ³ k ²).     

A branch-and-check algorithm for minimizing the weighted number of late jobs on a single machine with release dates

In this paper we consider the scheduling problem of minimizing the weighted number of late jobs on a single machine (1|_rj|∑_wjUj)$\left(1|r_j|\sum w_j{U}_j\right)$. A branch-and-check algorithm is proposed, where a relaxed integer programming formulation is solved by branch-and-bound and infeasible solutions are cut off using infeasibility cuts. We suggest two ways to generate cuts. First, tightened “no-good” cuts are derived using a modification of the algorithm by Carlier (1982, EJOR, v.11, 42–47) which was developed for the problem of minimizing maximum lateness on a single machine. Secondly we show how to create cuts by using constraint propagation. The proposed algorithm is implemented in the Mosel modelling and optimization language. Computational experiments on instances with up to 140 jobs are reported. A comparison is presented with the exact approach of Péridy at al. (2003, EJOR, v.148, 591–603).     

带机器故障的两台机带权误工数排序问题

讨论机器带故障中断的两台平行机排序问题,工件加工时间均为单位时间,目标是极小化带权误工工件数.当转移时间t=0时给出了最优的算法.当t≠0时,给出了一个多项式时间的近似算法,并证明算法解与最优解至多相差一个带权误工数.     

Minimizing the weighted number of early and tardy jobs in a stochastic single machine scheduling problem

We study a static stochastic single machine scheduling problem in which jobs have random processing times with arbitrary distributions, due dates are known with certainty, and fixed individual penalties (or weights) are imposed on both early and tardy jobs. The objective is to find an optimal sequence that minimizes the expected total weighted number of early and tardy jobs. The general problem is NP-hard to solve; however, in this paper, we develop certain conditions under which the problem is solvable exactly. An efficient heuristic is also introduced to find a candidate for the optimal sequence of the general problem. Our illustrative examples and computational results demonstrate that the heuristic performs well in identifying either optimal sequences or good candidates with low errors. Furthermore, we show that special cases of the problem studied here reduce to some classical stochastic single machine scheduling problems including the problem of minimizing the expected weighted number of early jobs and the problem of minimizing the expected weighted number of tardy jobs which are both solvable by the proposed exact or heuristic methods.     

A new branch and bound algorithm for minimizing the weighted number of tardy jobs

In this paper, the problem of sequencing jobs on a single machine to minimize the weighted number of tardy jobs is considered. Some new dominances between jobs are proposed and studied. A new branch and bound algorithm that can solve large problems, e.g. 85 jobs, is presented.     

Fast approximation algorithm for job sequencing with deadlines

The problem under consideration is to schedule jobs on a machine in order to minimize the sum of the penalties of delayed jobs. A “range-and-bound” method is proposed for finding a tight bound P? such that P?≤P1≤2P?, P1 being the minimal sum desired. The considered scheduling problem, for n jobs and accuracy ε > 0, is solved by a fully polynomial ε-approximation algorithm in $\text{O(n}{}^2\text{log n +}\text{n}{}^2\text{ε}\text{)}$ time and $\text{O(}\text{n}{}^2\text{ε}\text{)}$ space.     

Minimizing the number of early jobs on a proportionate flowshop

A proportionate flowshop is a special case of the classical flowshop, where the job processing times are machine-independent. We study the problem of minimizing the number of early jobs in this machine setting. This objective function has hardly been investigated on a single machine, and never on a flowshop. We introduce an efficient iterative solution algorithm. In each iteration, a single job is moved to the first position (and is added to the set of early jobs), and the remaining jobs are rescheduled such that the maximum earliness is minimized. The algorithm guarantees an optimal solution in O(n³) time, where n is the number of jobs.     

Single machine batch scheduling to minimize the weighted number of late jobs

The single machine batch scheduling problem to minimize the weighted number of late jobs is studied. In this problem,n jobs have to be processed on a single machine. Each job has a processing time, a due date and a weight. Jobs may be combined to form batches containing contiguously scheduled jobs. For each batch, a constant set-up time is needed before the first job of this batch is processed. The completion time of each job in the batch coincides with the completion time of the last job in this batch. A job is late if it is completed after its due date. A schedule specifies the sequence of jobs and the size of each batch, i.e. the number of jobs it contains. The objective is to find a schedule which minimizes the weighted number of late jobs. This problem isNP-hard even if all due dates are equal. For the general case, we present a dynamic programming algorithm which solves the problem with equal weights inO(n ³) time. We formulate a certain scaled problem and show that our dynamic programming algorithm applied to this scaled problem provides a fully polynomial approximation scheme for the original problem. Each algorithm of this scheme has a time requirement ofO(n ³/ +n ³ logn). A side result is anO(n logn) algorithm for the problem of minimizing the maximum weight of late jobs.Supported by INTAS Project 93-257.     

Scheduling jobs with release times preemptively on a single machine to minimize the number of late jobs

We give a direct combinatorial O(n³logn) algorithm for minimizing the number of late jobs on a single machine when jobs have release times and preemptions are allowed. Our algorithm improves the earlier O(n⁵) and O(n⁴) dynamic programming algorithms for this problem.     

一种求解延迟工件数最小的混合流水车间调度问题的模拟退火算法

针对延迟工件数最小的混合流水车间调度问题,给出了一种改进的模拟退火求解算法. 该算法首先给出一个启发式算法来获得初始解,然后用模拟退火算法对初始解改进. 通过交换工件在第一阶段的排序来获得一个新的解,采用最先空闲设备分配规则和先到先被加工规则,对工件在剩余各级的工序进行调度. 实验仿真表明算法是可行有效的.