Online Scheduling & Project Scheduling
نویسنده
چکیده
This thesis presents new and improved scheduling algorithms for a number of scheduling problems. The first part of the thesis deals with two online-list scheduling problems, both with the objective to minimize the makespan. In these problems, the jobs arrive one by one and the decision maker has to irrevocably schedule the arriving job before the next job becomes known. In the second part, a new solution methodology for the time-constrained project scheduling problem is developed, and a decomposition method for the time-constrained project scheduling problem with adjacent resources is presented. The first online problem considered, is online-list scheduling of parallel jobs with the objective to minimize the makespan, and some of its special cases. In these problems there is a set of identical machines to process a set of parallel jobs. In contrast to the jobs in classical machine scheduling problems, parallel jobs require a number of machines simultaneously for their processing. For this problem, a 6.6623-competitive online algorithm and a lower bound of 2.43 on the competitive ratio of any online algorithm are presented. Both results are also applicable to the online orthogonal strip packing problem. Besides the tight lower bound of 2 on the competitive ratio of the problem with exactly two machines, also improved online algorithms for the case with exactly three machines and the semi-online case where jobs appear in non-increasing order of machine requirement are given. The second online problem covered, is the online-list batch scheduling problem with the objective to minimize the makespan. In this problem, there is one machine with a given batch capacity that processes the jobs in a parallel batching manner. Parallel batching means that all jobs in one batch receive processing at the same time. A complete classification of the tractability of this online problem is given; with respect to the competitive ratio an optimal online algorithm for any capacity
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