IJBTT

Comparison of Harmony Search Algorithm and Scheduling Methods: A Case Study of Installation Lift Company in Thailand

	International Journal of Engineering Trends and Technology (IJETT)
	© 2021 by IJETT Journal
	Volume-69 Issue-2
	Year of Publication : 2021
	Authors : Lakkana Ruekkasaem, Supalux Jairueng, Anucha Hirunwat, Pasura Aungkulanon
	DOI :  10.14445/22315381/IJETT-V69I2P204

Citation 

MLA Style: Lakkana Ruekkasaem, Supalux Jairueng, Anucha Hirunwat, Pasura Aungkulanon"Comparison of Harmony Search Algorithm and Scheduling Methods: A Case Study of Installation Lift Company in Thailand" International Journal of Engineering Trends and Technology 69.2(2021):25-31. 

APA Style:Lakkana Ruekkasaem, Supalux Jairueng, Anucha Hirunwat, Pasura Aungkulanon. Comparison of Harmony Search Algorithm and Scheduling Methods: A Case Study of Installation Lift Company in Thailand  International Journal of Engineering Trends and Technology, 69(2),25-31.

Abstract
Priority rules guide the order in which jobs should be processed. The earliest due date method (EDDM), first come, first served method (FCFSM), longest processing time method (LPTM), and shortage processing time method (SPTM) are the most common priority rules for sequencing jobs. Different priority rules give different orders of processing jobs. This research proposed an innovative metaheuristic method called the Harmony search algorithm (HSA) and compared it to traditional priority rules. A set of five criteria were considered to evaluate the best priority method. An installation lift company employed the computational simulation. A set of simulation experiments showed that HSA outperformed the traditional priority rules regarding average completion time and utilization.

Reference
[1] M. Jose Framinan, R. Leisten, and R. Ruiz, Overview of Scheduling Methods, Manufacturing Scheduling Systems, Springer-Verlag London, 2014.
[2] V. Suresh, and D. Chaudhuri, Dynamic Scheduling - A Survey of Research, International Journal of Production Economics., 32 (1993) 52 – 63.
[3] S. Leung, and Y. Wu, A Robust Optimization Model for Stochastic Aggregate Production Planning, Production Planning & Control, 15(5) (2004) 502–514.
[4] M.K. Reeja, and C. Rajendran, Dispatching Rules for Scheduling in Assembly Job Shops - Part 1, International Journal of Production Research, 38(9) (2010) 2051-2066.
[5] T. Kaewpaitoon, and J. Teeravaraprug, Comparison of Well-known Scheduling Methodologies: A Case Study, Proceedings of the IMECS 2010, pp. 1-5, Hong Kong, March 17 – 19 2010.
[6] P. Parthanadee, and J. Buddhakulsomsiri, Simulation Modeling and Analysis for Production Scheduling Using Real-Time Dispatching Rules: A Case Study in Canned Fruit Industry,” Computers and Electronics in Agriculture. 70(1) (2010) 245-255.
[7] P. Senra, I. Lopes, and J.A. Oliveira, Supporting Maintenance Scheduling: A Case Study,” Procedia Manufacturing. 11(2017). 2123 – 2130.
[8] S. Kirkpatrick, C. D. Gelatt Jr., and M. P. Vecchi, Optimization by Simulated Annealing. Science. 220(4598)(1983) 671-680.
[9] D. Karaboga, An Idea Based on Honey Bee Swarm for Numerical Optimization, Technical Report-TR06, Department of Computer Engineering, Faculty of Engineering, Erciyes University, Kayseri, Turkey, 2005.
[10] B.Suresh Babu, Real Power Loss Minimization of AC/DC Hybrid Systems with Reactive Power Compensation by using Self Adaptive Firefly Algorithm. IJETT International Journal of Industrial Engineering, 7(1) (2020) 41-48.
[11] K.S. Lee, and Z.W. Geem, A New Meta-heuristic Algorithm for Continuous Engineering Optimisation: Harmony Search Theory and Practice, Computer Methods in Applied Mechanics and Engineering, 194(2004) 3902–3933.
[12] J. H. Kim, Harmony Search Algorithm: A Unique Music-inspired Algorithm, Procedia Engineering, 154 (2016) 1401-1405.
[13] K. S. Lee, and Z. W. Geem, A New Meta-Heuristic Algorithm for Continuous Engineering Optimization: Harmony Search Theory and Practice, Computer Methods in Applied Mechanics and Engineering, 194 36–38 (2005) 3902–3933.
[14] M. Mahdavi, M. Fesanghary, and E. Damangir, An Improved Harmony Search Algorithm for Solving Optimisation Problems, Applied Mathematics and Computation, 188(2007) 1567–1579.
[15] P. Aungkulanon, P. Luangpaiboon, and R. Montemanni, “An Elevator Kinematics Optimization Method for Aggregate Production Planning Based on Fuzzy MOLP Model,” International Journal of Mechanical Engineering and Robotics Research, 7(4), (2018) 22-427.
[16] P. Aungkulanon, B. Phruksaphanrat, and P. Luangpaiboon, Dynamic Maintenance Scheduling with Fuzzy Data via Biogeography-based Optimization Algorithm and Its Hybridizations,” Current Applied Science and Technology, 20(2) (2020) 226-237.
[17] W. Laoraksakiat, and K. Asawarungsaengkul, Bi-objective Hybrid Flow Shop Scheduling with Family Setup Times Using Hybrid Genetic and Migrating Birds Optimization Algorithms, Applied Science and Engineering Progress, 14(1) (2021) 19–30.
[18] P. Aungkulanon, B. Phruksaphanrat, and P. Luangpaiboon, Harmony Search Algorithm with Various Evolutionary Elements for Fuzzy Aggregate Production Planning, Intelligent Control and Innovative Computing. Lecture Notes in Electrical Engineering, Springer, New York, 110 189-201, 201
[19] Hossein Oghab Neshin, Manouchehr Jandaghi Semnani Two-area power system stability analysis by frequency controller with UPFC synchronization and energy storage systems, International Journal of Engineering Trends and Technology 68.1 (2020) 14-29.

Keywords
Priority rules, Harmony search algorithm, Average Completion Time.