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Solving Job Scheduling Problem Using Genetic Algorithm

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Part of the Lecture Notes in Networks and Systems book series (LNNS,volume 227)

Abstract

The efficient scheduling of independent computational jobs in a computing environment is an important problem where there are some deadlines for each job to become complete. Finding optimal schedules for such an environment is (in general) an NP-complete problem, and so heuristic approaches must be used. Genetic algorithms are known to give the best solutions to such problems. The purpose of this paper is to propound a solution to a job scheduling problem using genetic algorithms. The experimental results show that the most important factor on the time complexity of the algorithm is the size of the population and the number of generations.

Keyword

  • Job Scheduling
  • Genetic Algorithm
  • Optimal Scheduling

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  • DOI: 10.1007/978-3-030-75078-7_53
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Correspondence to Farshid Hajati .

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Gheisari, S., Rezaee, A., Hajati, F. (2021). Solving Job Scheduling Problem Using Genetic Algorithm. In: Barolli, L., Woungang, I., Enokido, T. (eds) Advanced Information Networking and Applications. AINA 2021. Lecture Notes in Networks and Systems, vol 227. Springer, Cham. https://doi.org/10.1007/978-3-030-75078-7_53

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