The method of local linearization for the solution of stochastic innovation diffusion models
Authors: Giovanis, Apostolos 
Skiadas, Christos 
Issue Date: 1-Jan-1999
Journal: Foundations of Computing and Decision Sciences 
Volume: 24
Issue: 3
Abstract: 
This paper implementations of parallel Tabu Search algorithms for solving the problem of scheduling nonpreemtable, independent jobs on parallel, identical machines to minimize the makespan are presented. F our different types of parallel Tabu Search based on Michael J. Flynn , s computer architectural classification scheme are considered. A computational experiment is described performed in two different parallel computer architectures: multiprocessor scalar system with shared memory and scalable supercomputing system with distributed memory .A comparison of results obtained for sequential versions of the algorithm as well as parallel ones in both the architectures is presented. Some conclusions and final remarks are included.
ISSN: 0867-6356
URI: https://uniwacris.uniwa.gr/handle/3000/2506
Type: Article
Department: Department of Business Administration 
School: School of Administrative, Economics and Social Sciences 
Affiliation: University of West Attica (UNIWA) 
Appears in Collections:Articles / Άρθρα

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