Equitable Scheduling on a Single Machine
| Autor: | Klaus Heeger, Danny Hermelin, George B. Mertzios, Hendrik Molter, Rolf Niedermeier, Dvir Shabtay |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
FOS: Computer and information sciences
Discrete Mathematics (cs.DM) Artificial Intelligence Computer Science - Data Structures and Algorithms General Engineering Data Structures and Algorithms (cs.DS) General Medicine Management Science and Operations Research Software Computer Science - Discrete Mathematics |
| Zdroj: | 35th AAAI Conference on Artificial Intelligence (AAAI), Vancouver, Canada, 2-9 February 2021 [Conference proceedings] |
| Popis: | 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 $k \le m$ 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|