极大化提前完工总量平行机排序问题的LPT算法

研究带有共同交货期的三台平行机排序问题。工件在加工过程中不允许中断, 目标是极大化所有工件的提前完工量, 即在交货期前所加工工件(或部分) 的总加工时长。由于该问题是NP-难问题, 本文应用经典LPT算法来解决该问题。我们证明了LPT算法求解该问题的最坏情况界至多为$\frac{15}{13}$, 并给出实例说明最坏情况界的下界为$\frac{27}{25}$。     

极小化最大提前完工时间的两平行机排序问题

讨论了在两台同型平行机上,加工带截止期限的n个工件,在机器可空闲条件下,确定一个工件排序,使得最大提前完工时间最小.由于工件不允许延迟,问题可能会无可行排序.先讨论问题的可行性,通过子集和问题归约,证明了判定问题的可行性是NP-complete的.如果问题可行,接着讨论了问题的复杂性,通过划分问题归约,证明了其是NP-complete的.最后,考虑了工件加工时间相等的特殊情形,提出了一个算法在多项式时间内获得最优排序.     

带约束的平行机排序的一个近似算法

讨论有资源约束和有机器准备时间的平行机排序问题,资源约束为每个机器至多可加工k个工件,在极小化makespan的上给出了一个匹配算法,证明其最坏情况最紧界是2-m^-1,并进一步给出了它的两个带参数的最坏情况界。     

有两个服务等级的平行机排序问题

对有两个服务等级的平行机排序问题的m台机情形,证明了修正的MF算法的最坏情况界不超过4/3 (1/2)~k,其中k是算法中预先给定的迭代次数.而已有的算法仅为2-1/(m-1),从而大大改进了已有文献中的结果.     

一类带核的平行机排序问题

研究了一类工件具有相似加工时间的带核的平行机排序问题,运用ＬＰＴ算法求解,得到ＬＰＴ算法界的精确估计并对问题的某些情形,给出了界紧的例子。     

可拆分有调整时间的平行机排序问题的一个算法

考虑有独立调整时间的同型号平行机排序问题,极小化最迟完工时间,产品允许拆分,同一产品被拆分后各部分可以在不同机器上同时加工,该问题是ＮＰ－ｈａｒｄ问题。本文首先给出该问题的一个启发式算法ＭＬ,然后证明了其最坏情况估计不超过７／４－１／ｍ（ｍ≥２）。     

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。     

机器具有准备时间的双目标平行机排序问题

本文讨论机器具有准备时间的双目标平行机排序问题，目标函数为完工时间和最优条件下极小化最大完工时间．通过对SPT排序的性质的分析，给出了最优排序的下界．在此基础上证明了SPT排序的误差界为3／2，并且是紧界．     

带强制工期的可中断平行机排序问题

讨论了在m台同型平行机上,加工带强制工期的n个可中断工件,在机器可空闲条件下,确定一个工件排序,使得提前完工时间和最小.先考虑了问题的复杂性,通过3-划分问题归约,证明了其是强NP-hard的.而后,讨论了强制工期相等的特殊情形,由于工件不允许延迟,问题可能会无可行排序.先讨论了可行性,接着针对可行问题,提出一个算法在多项式时间内获得最优排序.     

An improved heuristic for one-machine scheduling with delays constraints

An improved heuristic is proposed for one-machine scheduling problem with delay constraints, thus an open problem raised by Wikumet al. is solved. The heuristic solves the corresponding unit-execution-time problem optimally.     

Multiprocessor scheduling: combining LPT and MULTIFIT

We consider the problem of scheduling a set of n independent jobs on m identical machines with the objective of minimizing the total finishing time. We combine the two most popular algorithms, LTP and MULTIFIT, to form a new one. MULTIFIT is well known to have better error bound than LPT with the price paid in running time. Although MULTIFIT provides a better error bound, in many cases LPT still can yield better results. This motivates the development of this new combined algorithm, which uses the result of LPT as the incumbent and then applies MULTIFIT with fewer iterations. The performance of this combined algorithm is better than that of LPT because it uses LPT as an incumbent. The error bound of this combined algorithm is never worse than that of MULTIFIT. For example, the error bound of implementing this combined algorithm to the two-processor problem is , compared to the error bound of in MULTIFIT. Empirical results of the comparison for schedules obtained by the combined algorithm, MULTIFIT and LPT are also provided.     

Worst-case analysis of a scheduling algorithm

In this note, a heuristic proposed by Ibarra and Kim (IK) for scheduling independent tasks on unrelated processors is analyzed. The heuristic may create a schedule which finishes a time $\text{m 1 OPT}$, where m is the number of processors, and OPT is the time used in the optimal schedule. This compares unfavorably with the heuristics described by Davis and Jaffe [2], which have worst-case behavior which is $\text{O(OPT 1 m}{}^{0.5}\text{)}$.     

Tighter approximation bounds for LPT scheduling in two special cases

$Q||C_{\max }$ denotes the problem of scheduling n jobs on m machines of different speeds such that the makespan is minimized. In the paper two special cases of $Q||C_{\max }$ are considered: case I, when $m?1$ machine speeds are equal, and there is only one faster machine; and case II, when machine speeds are all powers of 2 (2-divisible machines). Case I has been widely studied in the literature, while case II is significant in an approach to design so called monotone algorithms for the scheduling problem.We deal with the worst case approximation ratio of the classic list scheduling algorithm ‘Largest Processing Time (LPT)’. We provide an analysis of this ratio $\mathit{Lpt}/\mathit{Opt}$ for both special cases: For ‘one fast machine’, a tight bound of $(\sqrt{3}+1)/2\approx 1.3660$ is given. For 2-divisible machines, we show that in the worst case $1.3673<\mathit{Lpt}/\mathit{Opt}<1.4$. Besides, we prove another lower bound of $955/699>(\sqrt{3}+1)/2$ when LPT breaks ties arbitrarily.To our knowledge, the best previous lower and upper bounds were $(4/3,3/2?1/2m]$ in case I [T. Gonzalez, O.H. Ibarra, S. Sahni, Bounds for LPT schedules on uniform processors, SIAM Journal on Computing 6 (1) (1977) 155–166], respectively $[4/3?1/3m,3/2]$ in case II [R.L. Graham, Bounds on multiprocessing timing anomalies, SIAM Journal on Applied Mathematics 17 (1969) 416–429; A. Kovács, Fast monotone 3-approximation algorithm for scheduling related machines, in: Proc. 13th Europ. Symp. on Algs. (ESA), in: LNCS, vol. 3669, Springer, 2005, pp. 616–627]. Moreover, Gonzalez et al. conjectured the lower bound 4/3 to be tight in the ‘one fast machine’ case [T. Gonzalez, O.H. Ibarra, S. Sahni, Bounds for LPT schedules on uniform processors, SIAM Journal on Computing 6 (1) (1977) 155–166].     

关于总误工损失的两个代理单机排序问题

研究了与总误工损失相关的两个代理的单机排序问题。第一个代理以工件的总误工损失为目标函数,第二个代理以工件的总完工时间或总误工工件数为目标函数。目标是寻找一个排序,使得在第二个代理的目标函数不超过给定的上界的条件下,第一个代理的目标函数值最小。对这两个与总误工损失相关的两个代理的单机排序问题,分别给出它们的拟多项式时间的动态规划算法。     

目标为最小化工件运输时间和的单台机器带一个维修时间段的排序问题的一个改进算法

单台机器带一个维修时间段的排序问题,目标是最小化所有工件的运输时间和.在这篇文章里,重新研究了该问题,并给出了一个时间复杂性为O（n³）的近似算法,将性能比从3/2改进到5/4.     

Minimizing total weighted late work in the resource-constrained project scheduling problem

This paper deals with resource-constrained project scheduling problem under the weighted late work criterion. Late work objective functions estimate the quality of a schedule based on durations of late parts of activities, not taking into account the amount of delay for fully late activities. It is assume that a project contains activities interrelated by finish-to-start type precedence relations with time lag of zero, which require one or more constrained renewable resources. The objective is to schedule each activity such that the total weighted late work is minimized. The problem has been formulated using a linear integer programming model and solved by the CPLEX. Also, a set of priority rules have been designed to quickly generate a set of initial solutions. In order to solve the problem optimally, a depth-first branch-and-bound algorithm is applied based on idea of minimal delaying alternatives. The branching order of nodes that belong to the same level of the search tree is determined on the basis of the developed priority rules. This results in generation six different versions of the branch-and-bound algorithm. Computational results on randomly generated problem sets are provided to analyze the efficiency of the priority rules and the branch-and-bound algorithm.     

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。     

工件具有加工位置上限最小化加权总误工量的单机排序问题

考虑工件具有加工位置上限最小化总加权误工量的单机排序问题.在此排序问题中,每个工件J_j都具有一个加工位置上限k_j.也就是说,如果工件J_j是一个可行排序中的第x个工件,那么就需要满足x ≤ k_j.证明了（i）当工件具有相同工期时,该排序问题是二元NP-难的并且是拟多项式时间可解的,（ii）当工件具有单位权重时,该排序问题是一元NP-难的.