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

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.

[1]  Ramachandran Baskaran,et al.  An application perspective evaluation of multi-agent system in versatile environments , 2011, Expert Syst. Appl..

[2]  G. V. Uma,et al.  Multi-agent-based integrated framework for intra-class testing of object-oriented software , 2005, Appl. Soft Comput..

[3]  Dhavachelvan Ponnurangam,et al.  A survey of keyword spotting techniques for printed document images , 2010, Artificial Intelligence Review.

[4]  G. V. Uma,et al.  Reliability Enhancement in Software Testing - An Agent-Based Approach for Complex Systems , 2004, CIT.

[5]  Hong-Zhong Huang,et al.  Grid Service Reliability Modeling and Optimal Task Scheduling Considering Fault Recovery , 2011, IEEE Transactions on Reliability.

[6]  Qian Tao,et al.  A rotary chaotic PSO algorithm for trustworthy scheduling of a grid workflow , 2011, Comput. Oper. Res..

[7]  Jun Zhang,et al.  SamACO: Variable Sampling Ant Colony Optimization Algorithm for Continuous Optimization , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[8]  Dhavachelvan Ponnurangam,et al.  Automating diseases diagnosis in human: a time series analysis , 2010, ICWET.

[9]  D. Y. Sha,et al.  A Multi-objective PSO for job-shop scheduling problems , 2009, 2009 International Conference on Computers & Industrial Engineering.

[10]  Jinung An,et al.  Estimation of particle swarm distribution algorithms: Combining the benefits of PSO and EDAs , 2012, Inf. Sci..

[11]  Hua-Ping Chen,et al.  Two-agent scheduling on a single batch processing machine with non-identical job sizes , 2011, 2011 2nd International Conference on Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC).

[12]  Gautam Das,et al.  Intelligent Information Technology, 7th International Conference on Information Technology, CIT 2004, Hyderabad, India, December 20-23, 2004, Proceedings , 2004, CIT.

[13]  Jun Zhang,et al.  An Efficient Ant Colony System Based on Receding Horizon Control for the Aircraft Arrival Sequencing and Scheduling Problem , 2010, IEEE Transactions on Intelligent Transportation Systems.

[14]  Sea Ling,et al.  Describing Web Service Architectures through Design-by-Contract , 2003, ISCIS.

[15]  Wei-Chang Yeh,et al.  Feature selection with Intelligent Dynamic Swarm and Rough Set , 2010, Expert Syst. Appl..

[16]  Jiangye Yuan,et al.  An improved WM method based on PSO for electric load forecasting , 2010, Expert Syst. Appl..

[17]  S. Sumathi,et al.  PSO and ACO based approach for solving combinatorial Fuzzy Job Shop Scheduling Problem , 2011 .

[18]  R. Tavakkoli-Moghaddam,et al.  A new hybrid multi-objective Pareto archive PSO algorithm for a bi-objective job shop scheduling problem , 2011, Expert Syst. Appl..

[19]  Jing Zhang,et al.  A modified Ant Colony algorithm for the Job Shop Scheduling Problem to minimize makespan , 2010, 2010 International Conference on Mechanic Automation and Control Engineering.

[20]  P. Dhavachelvan,et al.  Metrics based performance control over text mining tools in bioinformatics , 2009, ICAC3 '09.

[21]  Pier Luca Lanzi,et al.  Ant Colony Heuristic for Mapping and Scheduling Tasks and Communications on Heterogeneous Embedded Systems , 2010, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

[22]  Ramachandran Baskaran,et al.  QoS enhancements for global replication management in peer to peer networks , 2012, Future Gener. Comput. Syst..