The open shop problem with routing at a two-node network and allowed preemption

The open shop problem with routing and allowed preemption is a generalization of the two classical discrete optimization problems: the NP-hard metrical traveling salesman problem and the polynomially solvable scheduling problem, i.e., the open shop with allowed preemption. In the paper, a partial case of this problem is considered when the transportation network consists of two nodes. It is proved that the problem with two machines is polynomially solvable, while the problem is NP-hard in the strong sense in the case of not fixed number of machines.     

On-line scheduling to minimize max flow time: an optimal preemptive algorithm

We investigate the maximum flow time minimization problem of on-line scheduling jobs on m identical parallel machines. When preemption is allowed, we derive an optimal algorithm with competitive ratio 2-1/m. When preemption is not allowed and m=2, we show that the First In First Out heuristic achieves the best possible competitive ratio.     

Competitive analysis of preemptive single-machine scheduling

We give an online algorithm for minimizing the total weighted completion time on a single machine where preemption of jobs is allowed and prove that its competitive ratio is at most 1.57.     

Scheduling Markovian PERT networks to maximize the net present value: New results

We study project scheduling so as to maximize the expected net present value when task durations are exponentially distributed. Based on the structural properties of an optimal solution we show that, even if preemption is allowed, it is not necessary to do so. Next to its managerial importance, this result also allows for a new algorithm which improves on the current state of the art with several orders of magnitude, both in CPU time and in memory usage.     

Discrete-time queues with discretionary priorities

In this paper, we consider a discrete-time two-class discretionary priority queueing model with generally distributed service times and per slot i.i.d. structured inputs in which preemptions are allowed only when the elapsed service time of a lower-class customer being served does not exceed a certain threshold. As the preemption mode of the discretionary priority discipline, we consider the Preemptive Resume, Preemptive Repeat Different, and Preemptive Repeat Identical modes. We derive the Probability Generating Functions (PGFs) and first moments of queue lengths of each class in this model for all the three preemption modes in a unified manner. The obtained results include all the previous works on discrete-time priority queueing models with general service times and structured inputs as their special cases. A numerical example shows that, using the discretionary priority discipline, we can more subtly adjust the system performances than is possible using either the pure non-preemptive or the preemptive priority disciplines.     

Interval Scheduling on identical machines

Interval Scheduling problems (IS) address the situation where jobs with fixed start and fixed end times are to be processed on parallel identical machines. The optimization criteria of interest are the maximization of the number of jobs completed and, in case weights are associated with jobs, the subset of jobs with maximal total weight. We present polynomial solutions to several IS problems and study computational complexity issues in the situation where bounds are imposed on the total operating time of the machines. With this constraint, we show that tractability is achieved again when job preemption is allowed.     

Three stage generalized flowshop: Scheduling civil engineering projects

We model the working of a civil engineering firm concerned with land development as a three stage flexible flowshop with weak chain precedence constraints and where preemption is allowed. The scheduling objective is to minimize the total tardiness for all the projects. Since solving this problem optimally is very hard, we propose a number of heuristic scheduling procedures which are evaluated extensively on real-life data and artificial problem instances.     

On some properties of optimal schedules in the job shop problem with preemption and an arbitrary regular criterion

Optimal schedules in the job shop problem with preemption and with the objective of minimizing an arbitrary regular function of operation completion times are studied. It is shown that for any instance of the problem there always exists an optimal schedule that meets several remarkable properties. Firstly, each changeover date coincides with the completion time of some operation, and so, the number of changeover dates is not greater than the total number of operations, while the total number of interruptions of the operations is no more than the number of operations minus the number of jobs. Secondly, every changeover date is “super-integral”, which means that it is equal to the total processing time of some subset of operations. And thirdly, the optimal schedule with these properties can be found by a simple greedy algorithm under properly defined priorities of operations on machines. It is also shown that for any instance of the job shop problem with preemption allowed there exists a finite set of its feasible schedules which contains at least one optimal schedule for any regular objective function (from the continuum set of regular functions).     

Scheduling with target start times

We address the single-machine problem of scheduling n independent jobs subject to target start times. Target start times are essentially release times that may be violated at a certain cost. The objective is to minimize a bicriteria objective function that is composed of total completion time and maximum promptness, which measures the observance of these target start times. We show that in case of a linear objective function the problem is solvable in O(n⁴) time if preemption is allowed or if total completion time outweighs maximum promptness.     

Multiprocessor scheduling under precedence constraints: Polyhedral results

We consider the problem of scheduling a set of tasks related by precedence constraints to a set of processors, so as to minimize their makespan. Each task has to be assigned to a unique processor and no preemption is allowed. A new integer programming formulation of the problem is given and strong valid inequalities are derived. A subset of the inequalities in this formulation has a strong combinatorial structure, which we use to define the polytope of partitions into linear orders. The facial structure of this polytope is investigated and facet defining inequalities are presented which may be helpful to tighten the integer programming formulation of other variants of multiprocessor scheduling problems. Numerical results on real-life problems are presented.     

Analysis of preemptive loss priority queues with preemption distance

In a queueing system with preemptive loss priority discipline, customers disappear from the system immediately when their service is preempted by the arrival of another customer with higher priority. Such a system can model a case in which old requests of low priority are not worthy of deferred service. This paper is concerned with preemptive loss priority queues in which customers of each priority class arrive in a Poisson process and have general service time distribution. The strict preemption in the existing model is extended by allowing the preemption distance parameterd such that arriving customers of only class 1 throughp — d can preempt the service of a customer of classp. We obtain closed-form expressions for the mean waiting time, sojourn time, and queue size from their distributions for each class, together with numerical examples. We also consider similar systems with server vacations.     

Online makespan minimization in MapReduce-like systems with complex reduce tasks

In the MapReduce processing, since map tasks output key-value pairs, and reduce tasks take the pairs output by the map tasks and compute the final results. Therefore, reduce tasks are unknown until their map tasks are finished. Also, we assume that map tasks are preemptive and parallelizable, but reduce tasks are non-parallelizable. With these assumptions, we study the scheduling of minimizing makespan. Both preemptive and non-preemptive reduce tasks are considered. We prove that no matter if preemption is allowed or not, any algorithm has a competitive ratio at least \(2-\frac{1}{h}\), we then give two optimal algorithms for these two versions.     

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$\frac{27}{25}$。     

两台可拒绝同型机半在线排序问题

本文讨论一个两台可拒绝同型机半在线排序问题.当工件到达时,可以被拒绝,但要付出一定的罚值,也可以被接收加工,消耗一定的加工时间.其目标是要使所有加工工件生成的makespan和被拒绝工件的总罚值之和最小.加工不允许中断.进一步,机器带有两个并行处理子系统,可以提供两种排序方案,最后选取较好的一种.这是第一个在可拒绝同型机排序模型中使用半在线信息,我们设计出一个近似算法,其竞争比为3/2,另外又给出一个√3+1/2≈1.366的下界.     

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$\frac{27}{25}$。     

Two-machine open shop scheduling with special transportation times

The paper considers a problem of scheduling n jobs in a two-machine open shop to minimise the makespan, provided that preemption is not allowed and the interstage transportation times are involved. In general, this problem is known to be NP-hard. We present a linear time algorithm that finds an optimal schedule if no transportation time exceeds the smallest of the processing times. We also describe an algorithm that creates a heuristic solution to the problem with job-independent transportation times. Our algorithm provides a worst-case performance ratio of 8/5 if the transportation time of a job depends on the assigned processing route. The ratio reduces to 3/2 if all transportation times are equal.     

Threshold-based interventions to optimize performance in preemptive priority queues

This paper studies a single-server priority queueing model in which preemptions are allowed during the early stages of service. Once enough service effort has been rendered, however, further preemptions are blocked. The threshold where the change occurs is either a proportion of the service requirement, or time-based. The Laplace–Stieltjes transform and mean of each class sojourn time are derived for a model which employs this hybrid preemption policy. Both preemptive resume and preemptive repeat service disciplines are considered. Numerical examples show that it is frequently the case that a good combination of preemptible and nonpreemptible service performs better than both the standard preemptive and nonpreemptive queues. In a number of these cases, the thresholds that optimize performance measures such as overall average sojourn time are determined. This revised version was published online in June 2006 with corrections to the Cover Date.     

Scheduling with unexpected machine breakdowns

We investigate an online version of a basic scheduling problem where a set of jobs has to be scheduled on a number of identical machines so as to minimize the makespan. The job processing times are known in advance and preemption of jobs is allowed. Machines are non-continuously available, i.e., they can break down and recover at arbitrary time instances not known in advance. New machines may be added as well. Thus machine availabilities change online. We first show that no online algorithm can construct optimal schedules. We also show that no online algorithm can achieve a bounded competitive ratio if there may be time intervals where no machine is available. Then we present an online algorithm that constructs schedules with an optimal makespan of C_max^OPT if a lookahead of one is given, i.e., the algorithm always knows the next point in time when the set of available machines changes. Finally, we give an online algorithm without lookahead that constructs schedules with a nearly optimal makespan of C_max^OPT+, for any >0, if at any time at least one machine is available. Our results demonstrate that not knowing machine availabilities in advance is of little harm.