Equitable Scheduling on a Single Machine
AbstractWe introduce a natural but seemingly yet unstudied generalization of the problem of scheduling jobs on a single machine so as to minimize the number of tardy jobs. Our generalization lies in simultaneously considering several instances of the problem at once. In particular, we have n clients over a period of m days, where each client has a single job with its own processing time and deadline per day. Our goal is to provide a schedule for each of the m days, so that each client is guaranteed to have their job meet its deadline in at least k <= m days. This corresponds to an equitable schedule where each client is guaranteed a minimal level of service throughout the period of m days. We provide a thorough analysis of the computational complexity of three main variants of this problem, identifying both efficient algorithms and worst-case intractability results.
How to Cite
Heeger, K., Hermelin, D., Mertzios, G. B., Molter, H., Niedermeier, R., & Shabtay, D. (2021). Equitable Scheduling on a Single Machine. Proceedings of the AAAI Conference on Artificial Intelligence, 35(13), 11818-11825. https://doi.org/10.1609/aaai.v35i13.17404
AAAI Technical Track on Planning, Routing, and Scheduling