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Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

Parallel and Distributed Genetic Algorithm with Multiple-Objectives to Improve and Develop of Evolutionary Algorithm

Author 1: Khalil Ibrahim Mohammad Abuzanouneh

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Digital Object Identifier (DOI) : 10.14569/IJACSA.2016.070524

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 5, 2016.

  • Abstract and Keywords
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Abstract: In this paper, we argue that the timetabling problem reflects the problem of scheduling university courses, So you must specify the range of time periods and a group of instructors for a range of lectures to check a set of constraints and reduce the cost of other constraints ,this is the problem called NP-hard, it is a class of problems that are informally, it’s mean that necessary operations to solve the problem will increases exponentially and directly proportional to the size of the problem, The construction of timetable is most complicated problem that was facing many universities, and increased by size of the university data and overlapping disciplines between colleges, and when a traditional algorithm (EA) is unable to provide satisfactory results, a distributed EA (dEA), which deploys the population on distributed systems ,it also offers an opportunity to solve extremely high dimensional problems through distributed coevolution using a divide-and-conquer mechanism, Further, the distributed environment allows a dEA to maintain population diversity, thereby avoiding local optima and also facilitating multi-objective search, by employing different distributed models to parallelize the processing of EAs, we designed a genetic algorithm suitable for Universities environment and the constraints facing it when building timetable for lectures.

Keywords: Heterogeneous clusters; NP-hard; evolutionary multi-objective algorithm; parallel algorithms; Real-time scheduling

Khalil Ibrahim Mohammad Abuzanouneh, “Parallel and Distributed Genetic Algorithm with Multiple-Objectives to Improve and Develop of Evolutionary Algorithm” International Journal of Advanced Computer Science and Applications(IJACSA), 7(5), 2016. http://dx.doi.org/10.14569/IJACSA.2016.070524

@article{Abuzanouneh2016,
title = {Parallel and Distributed Genetic Algorithm with Multiple-Objectives to Improve and Develop of Evolutionary Algorithm},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.070524},
url = {http://dx.doi.org/10.14569/IJACSA.2016.070524},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {5},
author = {Khalil Ibrahim Mohammad Abuzanouneh}
}


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