An ACO-inspired algorithm for minimizing weighted flowtime in cloud-based parameter sweep experiments

2013 ◽  
Vol 56 ◽  
pp. 38-50 ◽  
Author(s):  
Cristian Mateos ◽  
Elina Pacini ◽  
Carlos García Garino
Keyword(s):  
Weighted Flowtime

Preemptive multiprocessor order scheduling to minimize total weighted flowtime

2008 ◽  
Vol 190 (1) ◽  
pp. 40-51 ◽  
Author(s):  
Joseph Y.-T. Leung ◽  
C.Y. Lee ◽  
C.W. Ng ◽  
G.H. Young
Keyword(s):  
Order Scheduling ◽  
Weighted Flowtime

scholarly journals Probabilistic analysis of the minimum weighted flowtime scheduling problem

1992 ◽  
Vol 11 (2) ◽  
pp. 67-71 ◽  
Author(s):  
Alberto Marchetti Spaccamela ◽  
Wan Soo Rhee ◽  
Leen Stougie ◽  
Sara van de Geer
Keyword(s):  
Probabilistic Analysis ◽  
Scheduling Problem ◽  
Weighted Flowtime

On the optimality of static priority policies in stochastic scheduling on parallel machines

1987 ◽  
Vol 24 (02) ◽  
pp. 430-448 ◽  
Author(s):  
Thomas Kämpke
Keyword(s):  
Optimal Policy ◽  
Parallel Machines ◽  
Random Variables ◽  
Stochastic Scheduling ◽  
Sufficient Condition ◽  
Exponential Random Variables ◽  
Holding Cost ◽  
Special Case ◽  
Weighted Flowtime

n jobs are to be preemptively scheduled for processing on n machines. The machines may have differing speeds and the jobs have processing requirements which are distributed as independent exponential random variables with different means. Holding cost g(U) is incurred per unit time that the set of uncompleted jobs is U and it is desired to minimize the total expected holding cost which is incurred until all jobs are complete. We show that if g satisfies certain simple conditions then the optimal policy is one which takes the jobs in the order 1, 2, ···, n and assigns each uncompleted job in turn to the fastest available machine. In the special case in which the objective is to minimize the expected weighted flowtime, where there is a holding cost of wi while job i is incomplete, the sufficient condition is simply w1 ≧ … ≧ wn and λ1 w1 ≧ … ≧ λn wn .

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