Equitable scheduling on a single machine

Heeger, K.; Hermelin, D.; Mertzios, G.B.; Molter, H.; Niedermeier, R.; Shabtay, D.

Abstract

We 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.

Citation

Heeger, K., Hermelin, D., Mertzios, G., Molter, H., Niedermeier, R., & Shabtay, D. (2021, February). Equitable scheduling on a single machine. Presented at 35th AAAI Conference on Artificial Intelligence (AAAI), Vancouver, Canada

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 35th AAAI Conference on Artificial Intelligence (AAAI)
• Start Date: Feb 2, 2021
• End Date: Feb 9, 2021
• Acceptance Date: Dec 2, 2020
• Online Publication Date: May 18, 2021
• Publication Date: 2021
• Deposit Date: Dec 3, 2020
• Publicly Available Date: Dec 4, 2020
• Series Number: 13
• Series ISSN: 2159-5399,2374-3468
• DOI: https://doi.org/10.1609/aaai.v35i13.17404
• Public URL: https://durham-repository.worktribe.com/output/1139339