We consider a model for scheduling under uncertainty. In this model, we combine the main characteristics of online and stochastic scheduling in a simple and natural way. Job processing times are assumed to be stochastic, but in contrast to traditional stochastic scheduling models, we assume that jobs arrive online, and there is no knowledge about the jobs that will arrive in the future. The mod...

<p style='text-indent:20px;'>This paper studies the problem of scheduling <inline-formula><tex-math id="M1">\begin{document}$ n $\end{document}</tex-math></inline-formula> jobs with equal processing times on id="M2">\begin{document}$ m uniform machines to optimize two criteria simultaneously. The main contribution is an id="M3">\begin{document}$ O(n\log m+n^3...

We consider the problem of nonpreemptively scheduling a set of n jobs with equal processing times on m parallel machines so as to minimize the makespan. Each job has a prespecified set of machines on which it can be processed, called its eligible set. We consider the most general case of machine eligibility constraints as well as special cases of nested and inclusive eligible sets. Both online ...

We study semi-online scheduling with a reordering buffer for identical parallel machines. In this problem, jobs arrive one by one and the online algorithm is equipped with a buffer of limited size, which can be used to reorder the jobs when making scheduling decisions. When the buffer is full, one of the jobs in the buffer must be irrevocably assigned to a machine before the next job can be rev...

This paper presents a methodology for automatically generating online scheduling strategies for a complex objective defined by a machine provider. To this end, we assume independent parallel jobs and multiple identical machines. The scheduling algorithm is based on a rule system. This rule system classifies all possible scheduling states and assigns a corresponding scheduling strategy. Each sta...

in this paper, a multi-product single machine scheduling problem with the possibility of producing defected jobs, is considered. we concern rework in the scheduling environment and propose a mixed-integer programming (mip) model for the problem.  based on the philosophy of just-in-time production, minimization of the sum of earliness and tardiness costs is taken into account as the objective fu...

We study the problem of online job-scheduling on parallel machines with di erent network topologies. An online scheduling algorithm schedules a collection of parallel jobs with known resource requirements but unknown running times on a parallel machine. We give an O(plog logN)-competitive algorithm for online scheduling on a two-dimensional mesh of N processors and we prove a matching lower bou...

Many online problems encountered in real-life involve a two-stage decision process: upon arrival of a new request, an irrevocable first-stage decision (the assignment of a specific resource to the request) must be made immediately, while in a second stage process, certain ”subinstances” (that is, the instances of all requests assigned to a particular resource) can be solved to optimality (offli...

scheduling of production in flexible manufacturing systems (fmss) has been extensively investigated over the past years and it continues to attract the interest of both academic researchers and practitioners. the generation of new and modified production schedules is becoming a necessity in today’s complex manufacturing environment. genetic algorithms are used in this paper to obtain an initial...