Scheduling Algorithms With Application to Parallel Computing of Aeroacoustics

2000 ◽  
Author(s):  
Alex Povitsky

Abstract In this study we consider one method of parallelization of implicit numerical schemes on multiprocessor systems. Then, the parallel high-order compact numerical algorithm is applied to physics of amplification of sound waves in a non-uniform mean flow. Due to the pipelined nature of this algorithm, its efficient parallelization is based on scheduling of processors for other computational tasks while otherwise the processors stay idle. In turn, the proposed scheduling algorithm is taken as a special case of the general shop scheduling problem and possible extentions and generalizations of the proposed scheduling methodology are discussed. Numerical results are discussed in terms of baroclinic generation of wave-associated vorticity that appear to be a key process in energy transfer between a non-uniform mean flow and a propagating disturbance. The discovered phenomenon leads to significant amplification of sound waves and controls the direction of sound propagation.

Author(s):  
Marco Antonio Cruz-Chavez ◽  
Martin G. Martinez-Rangel ◽  
J.A. Hernandez ◽  
Jose Crispin Zavala-Diaz ◽  
Ocotlan Diaz-Parra

2017 ◽  
Vol 13 (7) ◽  
pp. 6363-6368
Author(s):  
Chandrasekaran Manoharan

The n-job, m-machine Job shop scheduling (JSP) problem is one of the general production scheduling problems. The JSP problem is a scheduling problem, where a set of ‘n’ jobs must be processed or assembled on a set of ‘m’ dedicated machines. Each job consists of a specific set of operations, which have to be processed according to a given technical precedence order. Job shop scheduling problem is a NP-hard combinatorial optimization problem.  In this paper, optimization of three practical performance measures mean job flow time, mean job tardiness and makespan are considered. The hybrid approach of Sheep Flocks Heredity Model Algorithm (SFHM) is used for finding optimal makespan, mean flow time, mean tardiness. The hybrid SFHM approach is tested with multi objective job shop scheduling problems. Initial sequences are generated with Artificial Immune System (AIS) algorithm and results are refined using SFHM algorithm. The results show that the hybrid SFHM algorithm is an efficient and effective algorithm that gives better results than SFHM Algorithm, Genetic Algorithm (GA). The proposed hybrid SFHM algorithm is a good problem-solving technique for job shop scheduling problem with multi criteria.


Sign in / Sign up

Export Citation Format

Share Document