Hybrid algorithm for job scheduling: Combining the benefits of ACO and Cuckoo search

14Citations
Citations of this article
7Readers
Mendeley users who have this article in their library.
Get full text

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. © 2013 Springer-Verlag.

Cite

CITATION STYLE

APA

Babukarthik, R. G., Raju, R., & Dhavachelvan, P. (2013). Hybrid algorithm for job scheduling: Combining the benefits of ACO and Cuckoo search. In Advances in Intelligent Systems and Computing (Vol. 177 AISC, pp. 479–490). Springer Verlag. https://doi.org/10.1007/978-3-642-31552-7_49

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free