Optimization of Total Holding Cost in Job Shop Scheduling by Using Hybrid Algorithm

Optimization of Total Holding Cost in Job Shop Scheduling by Using Hybrid Algorithm S. Gobinath Kongunadu College of Engineering and Technology C. Arumugam Coimbatore Institute of Technology G. Ramya Sathyabama University M. Chandrasekaran Vels University

The classical job-shop scheduling problem is one of the most difficult combinatorial optimization problems. Scheduling is defined as the art of assigning resources to tasks in order to insure the termination of these tasks in a reasonable amount of time. Job shop scheduling problems vary widely according to specific production tasks but most are NP-hard problems. Mathematical and heuristic methods are the two major methods for resolving JSP. Job shop Scheduling problems are usually solved using heuristics to get optimal or near optimal solutions. In this paper, a Hybrid algorithm combined artificial immune system and sheep flock heredity model algorithm is used for minimizing the total holding cost for different size benchmark problems. The results show that the proposed hybrid algorithm is an effective algorithm that gives better results than other hybrid algorithms compared in literature. The proposed hybrid algorithm is a good technique for scheduling problems.
7 2014 176 179 https://www.scientific.net/PolicyAndEthics/PublishingPolicies https://www.scientific.net/license/TDM_Licenser.pdf 10.4028/www.scientific.net/AMM.591.176 https://www.scientific.net/AMM.591.176 https://www.scientific.net/AMM.591.176.pdf 10.1007/978-3-662-03088-2 Bruker P. (1995), Scheduling Algorithms, 2nd Edn, Springer-Verlag, Berlin. 10.1007/s001700070030 Ponnambalam S. G, Aravindan P, Rajesh S. V, A Tabu Search Algorithm for Job Shop Scheduling. Int J Adv Mfg Tech, 16: 765-771, (2000). Wei-Jun Xia, Zhi-ming Wu., (2005), A hybrid particle swarm optimization approach for the job shop scheduling problem, . Int J Adv Mfg Tech, vol. 4 pp.19-29. 10.1007/s00170-005-2513-4 Yang S, Dingwei Wang, (2001), A new adaptive neural network and heuristic hybrid approach job shop scheduling, Computers and operational research, vol. 28, pp: 955-971. 10.1016/s0305-0548(00)00018-6 Heinonen. J and Pettersson. F (2001), Job shop scheduling and visibility studies with hybrid ACO algorithm, Swam Intelligence focus on Ant and particle swarm opt., pp: 355-372. 10.5772/5113 Gocalves.J. F, Mendes,.J.J. M and Resende M.G.C., (2005), A hybrid genetic algorithm for job shop scheduling problems, Eur. Jou. Of opt. research, Vol. 167, No. 1, PP: 77-75. L. Wang and D. Zheng (2001), An effective hybrid optimization strategy for job shop scheduling problems, Computers and Operations research, Vol. 28, pp: 585-596. 10.1016/s0305-0548(99)00137-9 Ye Li and Yan chen (2010), Hybrid algorithm approach to job shop scheduling problems, Global Journal of Computer science and technology, vol. 10, issue. 10, sep, pp: 55-61. Hiroshi Ohta, Toshihiro Nakatani, A heuristic job-shop scheduling algorithm to minimize the total holding cost of completed and in-process products subject to no tardy jobs. Int J Prod Eco, 101: 19–29, (2006). 10.1016/j.ijpe.2005.05.004 Engin O, Alper Doyen, A new approach to solve hybrid flow shop scheduling problems by artificial immune system. Future Generation Comp Sys, 20: 1083–1095, (2004). 10.1016/j.future.2004.03.014 Chandrasekaran M, Asokan P, Kumanan S, Uma maheshwari S, Multi objective optimization for job shop scheduling problems using SFHM, Int J Mfg Sci and Tech, Vol 9, 2: 47-54, (2007). Lawrence S, Supplement to Resource Constrained Project Scheduling: An Experimental Investigation of Heuristic Scheduling Techniques, Carnegie Mellon University, GSIA, (1984).