In this paper, we study the reactive scheduling problems in a stochastic manufacturing environment. Speci®cally, we test the several scheduling policies under machine breakdowns in a classical job shop system. In addition, we measure the e€ect of system size and type of work allocation (uniform and bottleneck) on the system performance. The performance of the system is measured for the mean tar...

Handling uncertainty in natural inflow is an important part of a hydroelectric scheduling model. In a stochastic programming formulation, natural inflow may be modeled as a random vector with known distribution, but the size of the resulting mathematical program can be formidable. Decomposition-based algorithms take advantage of special structure and provide an attractive approach to such probl...

We consider a stochastic scheduling problem with impatience to the end of service or impatience to the beginning of service. The impatience of a job can be seen as a stochastic due date. Processing times and due dates are random variables. Jobs are processed on a single machine with the objective to minimize the expected weighted number of tardy jobs in the class of static list scheduling polic...

We consider the stochastic identical parallel machine scheduling problem and its online extension, when the objective is to minimize the expected total weighted completion time of a set of jobs that are released over time. We give randomized as well as deterministic online and offline algorithms that have the best known performance guarantees in either setting, online or offline and determinist...

We view dynamic scheduling as a sequential decision problem. Firstly, we introduce a generalized planning operator, the stochastic task model (STM), which predicts the effects of executing a particular task on state, time and reward using a general procedural format (pure stochastic function). Secondly, we show that effective planning under uncertainty can be obtained by combining adaptive hori...

Scheduling is a core activity in the manufacturing business. It assists with the efficient and effective utilisation of capital-intensive resources and increased throughput, thus increasing profitability. Simulation is appealing in manufacturing, as it can realistically imitate dynamic, stochastic processes while being descriptive in predicting the future process. We combined simulation and sch...

We derive the first performance guarantees for a combinatorial online algorithm that schedules stochastic, nonpreemptive jobs on unrelated machines to minimize the expectation of the total weighted completion time. Prior work on unrelated machine scheduling with stochastic jobs was restricted to the offline case, and required sophisticated linear or convex programming relaxations for the assign...

We investigate in this paper the problem of scheduling n jobs on a single machine with general stochastic cost functions, which involves the effects of stochastic due times, and with the stochastic processing times in a class of distributions, which covers the family of exponential distributions, the family of geometrical distributions and some other important distribution families as its speci...

We derive the first performance guarantees for a combinatorial online algorithm that schedules stochastic, nonpreemptive jobs on unrelated machines to minimize the expectation of the total weighted completion time. Prior work on unrelated machine scheduling with stochastic jobs was restricted to the offline case, and required sophisticated linear or convex programming relaxations for the assign...

We consider the problem to minimize the weighted sum of completion times in nonpreemptive parallel machine scheduling. In a landmark paper from 1986, Kawaguchi and Kyan [5] showed that scheduling the jobs according to the WSPT rule –also known as Smith’s rule– has a performance guarantee of 1 2 (1 + √ 2) ≈ 1.207. They also gave an instance to show that this bound is tight. We consider the stoch...