An Improved Ant Colony Optimized Tabu Search Algorithm for Makespan Improvement in Job Shop
K.Sathya sundari1, V, P, Eshwaramurthy2

1K.Sathya Sundari*, Research Scholar Part time Category – B, Bharathiar University, Coimbatore.
2Dr. V. P. Eshwaramurthy, Asst. Prof. of Computer Science, Komarapalayam Arts and Science College, Komarapalayam. 

Manuscript received on November 13, 2019. | Revised Manuscript received on 24 November, 2019. | Manuscript published on December 10, 2019. | PP: 670-674 | Volume-9 Issue-2, December 2019. | Retrieval Number: B6695129219/2019©BEIESP | DOI: 10.35940/ijitee.B6695.129219
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Abstract: In industries, the completion time of job problems is increased drastically in the production unit. In many existing kinds of research, the completion time i.e. makespan of the job is minimized using straight paths which is time-consuming. In this paper, we addressed this problem using an Improved Ant Colony Optimization and Tabu Search (ACOTS) algorithm by identifying the fault occurrence position exactly to rollback. Also, we used a short term memory-based rollback recovery technique to roll back to its own short term memory to reduce the completion time of the job. Short term memory is used to visit the recent movements in Tabu search. Our proposed ACOTS-Cmax approach is efficient and consumed less completion time compared to the ACO algorithm. 
Keywords: Ant Colony Optimization, Job Shop Scheduling, Short-term Memory, Tabu Search
Scope of the Article: Discrete Optimization