Syllabus (Tentative)
- Introduction (Handout of Chapter 1 and 2 from (Pinedo 95))
- Models
- Notation
- Applications
- NP-completeness, Approximation, Linear Programming
- Minimizing Schedule Length
- Solving P|pmtn|Cmax (McNaughton59) and lower bounds (KSW 2.3.2)
- P||Cmax
- List scheduling (2-approximation)
- LPT (4/3-approximation)
- Polynomial Approximation Scheme (Hochbaum Shmoys 87, KSW 3.3, 6.2)
- P|prec|Cmax (KSW 2.3.4)
- NP-hardness of P|prec,pj=1|Cmax
- List Scheduling for P|prec|Cmax (2-approximation)
- 3-processor Sheduling ??
- R|pmtn|Cmax (LawlerL78) -- introducing Linear programs in scheduling (KSW 4.1)
- R||Cmax (Shmoys Tardos 93) -- using linear program relaxations to get approximation algorithms (KSW 5.1)
- Improvements for R||Cmax (Svensson 2011) using configuration LPs
- Scheduling with Deadlines on One Machine
- 1||Lmax - EDD (KSW 2.1.2)
- 1|rj,pmtn| Lmax - preemptive EDD (introducing release dates) (KSW 2.1.3)
- Approx. algorithms for 1|rj,prec|Lmax and 1|rj|Lmax (Hall Shmoys 89,Hall97) (KSW 6.3.2)
- 1||∑wjUj - Dynamic programming solution, weak NP-completeness (KSW 3.2,6.1)
- Scheduling to Minimize weighted completion time
- 1||∑wjCj - Smith's rule (KSW 2.1.1)
- Exact solutions to R||{∑Cj via linear
programming and matching, specializations to
P||∑Cj (KSW 4.1)
- Dealing with release dates and precedence constraints
- Solving 1|rj,pmtn|Cj via SRPT (KSW 2.1.3)
- Approximations for 1|rj|∑Cj and
P|rj|∑Cj (Phillips Stein Wein 98) -- using
relaxations (KSW 5.2)
- Improvements through randomization for
1|rj|∑Cj (Chekuri et. al. 97)
- Other LPs and roundings P|rj|∑wjCj
( Hall et al 97)
- A PTAS (Afrati et al 99)
- 1 |prec| ∑ wjCj (Chekuri Motwani 1998)
- Minimizing Flow Time
- 1|rj|∑Fj is NP-hard (Kellerer et al 1995)
- Resource augmentation (Kalyanasundaram and Pruhs 95, Phillip et al 97, Cho et al 2007)
- Further improvements (Bansal et al., 2007)
- Energy-Aware Scheduling
-
A scheduling model for reduced CPU energy by Francis Yao, Demers and Shenker, FOCS 1995.
- Speed scaling with an arbitrary power function
by Nikhil Bansal, Ho-Leung Chan and Kirk Pruhs, SODA 2009.
- Hallucination Helps: Energy Efficient Virtual Circuit Routing.
A Antoniadis, et. al. SODA, 1141-1153.
Optimal Power-Down Strategies
by John Augustine, Sandy Irani and Chaitanya Swamy, SICOMP 2008.
-
Algorithms for Power Savings
Sandy Irani, Sandeep Shukla and Rajesh Gupta, SODA 2003 and TALG 2007.
-
Polynomial Time Algorithms for Minimum Energy Scheduling
by Philippe Baptiste, Marek Chroback and Christoph Durr, ESA 2007.