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AIPS
2006
13 years 9 months ago
Combining Stochastic Task Models with Reinforcement Learning for Dynamic Scheduling
We view dynamic scheduling as a sequential decision problem. Firstly, we introduce a generalized planning operator, the stochastic task model (STM), which predicts the effects of ...
Malcolm J. A. Strens
GECCO
2006
Springer
155views Optimization» more  GECCO 2006»
13 years 11 months ago
Comparison of genetic representation schemes for scheduling soft real-time parallel applications
This paper presents a hybrid technique that combines List Scheduling (LS) with Genetic Algorithms (GA) for constructing non-preemptive schedules for soft real-time parallel applic...
Yoginder S. Dandass, Amit C. Bugde
EOR
2007
174views more  EOR 2007»
13 years 7 months ago
A Benders approach for the constrained minimum break problem
This paper presents a hybrid IP/CP algorithm for designing a double round robin schedule with a minimal number of breaks. Both mirrored and non-mirrored schedules with and without ...
Rasmus V. Rasmussen, Michael A. Trick
HEURISTICS
2010
13 years 2 months ago
An evolutionary and constructive approach to a crew scheduling problem in underground passenger transport
Operation management of underground passenger transport systems is associated with combinatorial optimization problems (known as crew and train scheduling and rostering) which bel...
Rafael Elizondo, Víctor Parada, Lorena Prad...
CPAIOR
2005
Springer
14 years 1 months ago
Nondeterministic Control for Hybrid Search
Hybrid algorithms combining local and systematic search often use nondeterminism in fundamentally different ways. They may differ in the strategy to explore the search tree and/o...
Pascal Van Hentenryck, Laurent Michel