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| Content Provider | Springer Nature Link |
|---|---|
| Author | Even, Guy Halldórsson, Magnús M. Kaplan, Lotem Ron, Dana |
| Copyright Year | 2008 |
| Abstract | We consider the following problem of scheduling with conflicts (swc): Find a minimum makespan schedule on identical machines where conflicting jobs cannot be scheduled concurrently. We study the problem when conflicts between jobs are modeled by general graphs.Our first main positive result is an exact algorithm for two machines and job sizes in {1,2}. For jobs sizes in {1,2,3}, we can obtain a $\frac{4}{3}$ -approximation, which improves on the $\frac{3}{2}$ -approximation that was previously known for this case. Our main negative result is that for jobs sizes in {1,2,3,4}, the problem is APX-hard.Our second contribution is the initiation of the study of an online model for swc, where we present the first results in this model. Specifically, we prove a lower bound of $2-\frac{1}{m}$ on the competitive ratio of any deterministic online algorithm for m machines and unit jobs, and an upper bound of 2 when the algorithm is not restricted computationally. For three machines we can show that an efficient greedy algorithm achieves this bound. For two machines we present a more complex algorithm that achieves a competitive ratio of $2-\frac{1}{7}$ when the number of jobs is known in advance to the algorithm. |
| Starting Page | 199 |
| Ending Page | 224 |
| Page Count | 26 |
| File Format | |
| ISSN | 10946136 |
| Journal | Journal of Scheduling |
| Volume Number | 12 |
| Issue Number | 2 |
| e-ISSN | 10991425 |
| Language | English |
| Publisher | Springer US |
| Publisher Date | 2008-10-28 |
| Publisher Place | Boston |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Scheduling with conflicts Mutual exclusion scheduling Approximation algorithms Online algorithms Production/Logistics Artificial Intelligence (incl. Robotics) Optimization Calculus of Variations and Optimal Control; Optimization Operations Research/Decision Theory |
| Content Type | Text |
| Resource Type | Article |
| Subject | Artificial Intelligence Management Science and Operations Research Engineering Software |
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