Please use this identifier to cite or link to this item: https://idr.l3.nitk.ac.in/jspui/handle/123456789/8048
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dc.contributor.authorDani, V.-
dc.contributor.authorSarswat, A.-
dc.contributor.authorSwaroop, V.-
dc.contributor.authorDomanal, S.-
dc.contributor.authorRam Mohana Reddy, Guddeti-
dc.date.accessioned2020-03-30T10:18:02Z-
dc.date.available2020-03-30T10:18:02Z-
dc.date.issued2017-
dc.identifier.citationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2017, Vol.10597 LNCS, , pp.282-288en_US
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/8048-
dc.description.abstractJob Shop Scheduling problem has wide range of applications. However it being a NP-Hard optimization problem, always finding an optimal solution is not possible in polynomial amount of time. In this paper we propose a heuristic approach to find near optimal solution for Job Shop Scheduling Problem in predetermined amount of time using Cat Swarm Optimization. Novelty in our approach is our non-conventional way of representing position of cat in search space that ensures advantage of spatial locality is taken. Further while exploring the search space using randomization, we never explore an infeasible solution. This reduces search time. Our proposed approach outperforms some of the conventional algorithms and achieves nearly 86% accuracy, while restricting processing time to one second. � 2017, Springer International Publishing AG.en_US
dc.titleFast Convergence to Near Optimal Solution for Job Shop Scheduling Using Cat Swarm Optimizationen_US
dc.typeBook chapteren_US
Appears in Collections:2. Conference Papers

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