Abstract
The design of optimal job schedules on parallel machines with finite time is a combinatorial optimization problem and plays a crucial role in manufacturing and production facilities. In this work, we evaluate the performance of two recently proposed computational intelligence techniques, Grey Wolf Optimizer (GWO) and JAYA on ten datasets arising from five job shop scheduling problems with parallel machines. The computational results have shown GWO to be efficient than the JAYA algorithm for problems with higher number of orders and machines.
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References
V. Jain and I. E. Grossmann, “Algorithms for Hybrid MILP/CP Models for a Class of Optimization Problems,” INFORMS J. on Computing, vol. 13, pp. 258–276, 2001.
P. R. Kotecha, M. Bhushan, and R. D. Gudi, “Constraint Programming and Genetic Algorithm,” in Stochastic Global Optimization: Techniques and Applications in Chemical Engineering, G. P. Rangaiah, Ed., ed: World Scientific, 2010.
A. Husseinzadeh Kashan, “League Championship Algorithm (LCA): An algorithm for global optimization inspired by sport championships,” Applied Soft Computing, vol. 16, pp. 171–200, 2014.
A. H. Gandomi, X.-S. Yang, and A. H. Alavi, “Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems,” Engineering with Computers, vol. 29, pp. 17–35, 2013.
V. Punnathanam and P. Kotecha, “Yin-Yang-pair Optimization: A novel lightweight optimization algorithm,” Engineering Applications of Artificial Intelligence, vol. 54, pp. 62–79, 2016.
S. Mirjalili, S. M. Mirjalili, and A. Lewis, “Grey Wolf Optimizer,” Advances in Engineering Software, vol. 69, pp. 46–61, 2014.
R. Rao, “Jaya: A simple and new optimization algorithm for solving constrained and unconstrained optimization problems,” International Journal of Industrial Engineering Computations, vol. 7, pp. 19–34, 2016.
V. Punnathanam, R. Kommadath, and P. Kotecha, “Extension and performance evaluation of recent optimization techniques on mixed integer optimization problems,” in 2016 IEEE Congress on Evolutionary Computation (CEC), pp. 4390–4397, 2016.
P. R. Kotecha, M. D. Kapadi, M. Bhushan, and R. D. Gudi, “Multi-objective optimization issues in short-term batch scheduling,” in 17th IFAC World Congress, Seoul, Korea, 2008.
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Maharana, D., Kotecha, P. (2019). Optimization of Job Shop Scheduling Problem with Grey Wolf Optimizer and JAYA Algorithm. In: Panigrahi, B., Trivedi, M., Mishra, K., Tiwari, S., Singh, P. (eds) Smart Innovations in Communication and Computational Sciences. Advances in Intelligent Systems and Computing, vol 669. Springer, Singapore. https://doi.org/10.1007/978-981-10-8968-8_5
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DOI: https://doi.org/10.1007/978-981-10-8968-8_5
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