Hybrid Algorithm for Job Scheduling: Combining the Benefits of ACO and Cuckoo Search

Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 177)

Abstract

Job scheduling problem is a combinatorial optimization problem in computer science in which ideal jobs are assigned to resources at particular times. Our approach is based on heuristic principles and has the advantage of both ACO and Cuckoo search. In this paper, we present a Hybrid algorithm, based on ant colony optimization (ACO) and Cuckoo Search which efficiently solves the Job scheduling problem, which reduces the total execution time. In ACO, pheromone is chemical substances that are deposited by the real ants while they walk. When it comes to solving optimization problems it acts as if it lures the artificial ants. To perform a local search, we use Cuckoo Search where there is essentially only a single parameter apart from the population size and it is also very easy to implement.

Keywords

Job Scheduling Ant Colony Optimization Cuckoo Search 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Department of Computer SciencePondicherry UniversityPondicherryIndia
  2. 2.Bharatiyar UniversityCoimbatoreIndia

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