A semi-preemptive priority scheduling discipline: Performance analysis

In this paper, we present an in-depth analytical study of a semi-preemptive priority scheduling discipline. This discipline eliminates the deficits of both the full- and non-preemptive versions. Under the non-preemptive category, in particular, higher-priority customers may have to wait even when the service of a lower-priority customer has just started, while under the full-preemptive discipline, the almost completed service of a lower-priority customer may be interrupted due to the arrival of higher-priority customers, possibly causing a large extra delay. For fixed low-priority service times, the semi-preemptive priority scheduling discipline shows a performance gain of up to 6% compared to the full- and non-preemptive versions.     

A competitive magnet-based genetic algorithm for solving the resource-constrained project scheduling problem

This paper presents a genetic algorithm for solving the resource-constrained project scheduling problem. The innovative component of the algorithm is the use of a magnet-based crossover operator that can preserve up to two contiguous parts from the receiver and one contiguous part from the donator genotype. For this purpose, a number of genes in the receiver genotype absorb one another to have the same order and contiguity they have in the donator genotype. The ability of maintaining up to three contiguous parts from two parents distinguishes this crossover operator from the powerful and famous two-point crossover operator, which can maintain only two contiguous parts, both from the same parent. Comparing the performance of the new procedure with that of other procedures indicates its effectiveness and competence.     

Thek-partitioning problem

Thek-partitioning problem is defined as follows: Given a set of items {I ₁,I ₂,...,I _n} where itemIj is of weightwj 0, find a partitionS ₁,S ₂,...,S _m of this set with ¦S _i ¦ =k such that the maximum weight of all subsetsS _i is minimal,k-partitioning is strongly related to the classical multiprocessor scheduling problem of minimizing the makespan on identical machines. This paper provides suitable tools for the construction of algorithms which solve exactly the problem. Several approximation algorithms are presented for this NP-hard problem. The worst-case behavior of the algorithms is analyzed. The best of these algorithms achieves a performance bound of 4/3.     

Large Deviations of Queues Sharing a Randomly Time-Varying Server

We consider a discrete-time model where multiple queues, each with its own exogenous arrival process, are served by a server whose capacity varies randomly and asynchronously with respect to different queues. This model is primarily motivated by the problem of efficient scheduling of transmissions of multiple data flows sharing a wireless channel. We address the following problem of controlling large deviations of the queues: find a scheduling rule, which is optimal in the sense of maximizing

The ratio of the extreme to the sum in a random sequence

For X ₁ , X ₂ , ..., X _n a sequence of non-negative independent random variables with common distribution function F(t), X _(n) denotes the maximum and S _n denotes the sum. The ratio variate R _n  = X _(n) / S _n is a quantity arising in the analysis of process speedup and the performance of scheduling. O’Brien (J. Appl. Prob. 17:539–545, 1980) showed that as n → ∞, R _n →0 almost surely iff is finite. Here we show that, provided either (1) is finite, or (2) 1 − F (t) is a regularly varying function with index ρ < − 1, then . An integral representation for the expected ratio is derived, and lower and upper asymptotic bounds are developed to obtain the result. Since is often known or estimated asymptotically, this result quantifies the rate of convergence of the ratio’s expected value. The result is applied to the performance of multiprocessor scheduling.      

New Linear Program Performance Bounds for Queueing Networks

We obtain new linear programs for bounding the performance and proving the stability of queueing networks. They exploit the key facts that the transition probabilities of queueing networks are shift invariant on the relative interiors of faces and the cost functions of interest are linear in the state. A systematic procedure for choosing different quadratic functions on the relative interiors of faces to serve as surrogates of the differential costs in an inequality relaxation of the average cost function leads to linear program bounds. These bounds are probably better than earlier known bounds. It is also shown how to incorporate additional features, such as the presence of virtual multi-server stations to further improve the bounds. The approach also extends to provide functional bounds valid for all arrival rates.     

一个可中断两台可拒绝同型机半在线排序问题

讨论一个两台可拒绝同型机半在线排序问题的近似算法．设有两台同型机,工件逐个到达,可以被接收加工,消耗一定的加工时间tj,也可以被拒绝,但要付出一定的罚值Pj,目标是使被加工工件集的最大完工时间（makespan）和被拒绝工件集的罚值之和最小．此外,进一步假定每个工件的罚值和加工长度事先形成固定的比例α∈[0,＋∞）,即Pi=atj,针对工件加工可中断情形,设计出近似算法PRH,证明其竞争比．同时又给出该问题的下界,它们均为α的分段函数,且算法PRH在a∈[0,√2/2）∪[5/6＋∞）达到最优．     

带机器准备时间的已知工件总加工时间半在线问题

考虑带机器准备时间的已知工件总加工时间半在线问题。首先考虑P2,ri|sum|Cmin问题,给出Prsum算法并证明此算法的竞争比为23,且是最优算法;然后考虑Q2,ri|sum|Cmax问题,给出Qrsum算法并证明此算法的竞争比为2,同时给出此问题的一个下界1+3～(1/2)/2。显然Qrsum算法的竞争比与最     

基于资源随机中断的反应性多模式项目调度优化

资源中断是项目实施过程中一种常见现象,它会导致项目进度计划的变更并引起额外的成本。本文研究资源随机中断下的项目调度问题,目标是对基准进度计划进行合理的调整,以最小化由此所造成的额外成本。作者首先对研究问题进行界定,随后构建问题的优化模型。针对模型的NP-hard属性,设计禁忌搜索启发式算法。最后以基准列表算法和随机生成算法为参照,在随机生成的标准算例集合上对算法进行测试,得到如下结论:在可接受的计算时间范围内,禁忌搜索获得的满意解质量明显高于其他两种启发式算法;算法的平均计算时间随着项目活动数的增加而增加,随着网络复杂度、资源强度或资源中断次数的增加而减小;满意解的平均目标函数值,随着项目活动数或网络复杂度的增加而增加,随着资源中断次数的增加而减小,与资源强度无明显关系。