Online scheduling with multi‐state machines
Abstract
In this paper, we propose a general framework for online scheduling problems in which each machine has multiple states that lead to different processing times. For these problems, in addition to deciding how to assign jobs to machines, we also need to set the states of the machines each time they are assigned jobs. For a wide range of machine environments, job processing characteristics and constraints, and cost functions, we develop a ‐competitive deterministic online algorithm and a ‐competitive randomized online algorithm. The online weighted traveling repairman problem belongs to this general framework, and both our deterministic and randomized online algorithms lead to lower competitive ratios than the current existing ones in the literature. In addition, we include a complete proof that the online algorithm (reoptimizing the route of the repairman whenever a new request is released) is almost surely asymptotically optimal for a probabilistic version of this problem.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Dec 20, 2017
- Source ID
- 10.1002/net.21799
Entities
People
- Dawsen Hwang
- Patrick Jaillet
Organizations
- Air Force Office of Scientific Research
- Massachusetts Institute of Technology
- Office of Naval Research