Journal of Industrial Engineering Research in Production Systems

Journal of Industrial Engineering Research in Production Systems

Open Shop Scheduling with Assembly Stage: Gray Wolf Algorithm and Lagrangian Relaxation

Document Type : Research Paper

Authors
Abolfazl Yousefi Saeed 1
Javad Behnamian 2
1 Msc, Department of Industrial Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamedan, Iran
2 Professor, Department of Industrial Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamedan, Iran
10.22084/ier.2024.29657.2177
Abstract
In this research, the open shop scheduling problem has been discussed. In this environment, scheduling for jobs and planning for assembly operations are usually considered independently. However, it may not lead to the best results for the entire production system. On the other hand, the problem of assembly planning has many applications in industries and has recently attracted the attention of researchers. Since in the models that were used before, the assembly operation is not integrated in the open shop scheduling, in this research, inspired by the real production units and to bring the model closer to the real world, the assembly operation is included, which is a step after the completion of the production process. To solve this problem, after modeling it, the Lagrangian relaxation method is used to solve problems in medium dimensions and the gray wolf algorithm is used in large dimensions. Next, to check the quality of the results obtained from the gray wolf algorithm, the Lagrangian relaxation method and GAMS outputs in small-size instances and simulated annealing algorithm in large-size instances have been compared. The obtained results show that the solutions obtained from the proposed algorithm are of good quality.
Keywords
Scheduling
Open Shop
Assembly Operations
Gray wolf Algorithm
Lagrangian Relaxation
Subjects
  • Leung, Y. T., (1993) Handbook of Scheduling: Algorithms, Models, and Performance Analysis, CRC Press, Inc.
  • Bai, D., Zhang, Z., & Zhang, Q. (2017) Open shop scheduling problem to minimize total weighted completion time, Engineering Optimization, 49, 98 –112. https://doi.org/10.1080/0305215X.2016.1164854
  • Baptiste P. (2003) On minimizing the weighted number of late jobs in unit execution time open-shops, European Journal of Operational Research, 149 344-354. https://doi.org/10.1016/S0377-2217(02)00759-2
  • Liaw, C.F. (2003) An efficient tabu search approach for the two machine preemptive open shop scheduling problem, Computer Operation Research, 30, 2081–2095. https://doi.org/10.1016/S0305-0548(02)00124-7
  • Zhuang, Z., Huang, Z., Lu, Zh., Guo, L., Cao, Q., & Qin, W. (2019) An improved artificial bee colony algorithm for solving open shop scheduling problem with two sequence-dependent setup times, Procedia, 563-568. https://doi.org/10.1016/j.procir.2019.04.119
  • Zhuang, Z., Huang, Z., Lu, Zh., Guo, L., Cao, Q., & Qin, W. (2019) An improved artificial bee colony algorithm for solving open shop scheduling problem with two sequence-dependent setup times", Procedia, 563-568. https://doi.org/10.1016/j.procir.2019.04.119
  • Kankaya, F., Gelatt, C. & Vecci, M. (2018) Optimization by simulated annealing”, American Association for the Advancement of Science, 220, 4598, 671–680. https://doi.org/10.1126/science.220.4598.671
  • Roshnaei, S.A., Komaki, G.M., & Kayvanfar, V. (2018) Multi objective two-stage assembly flow shop with release time, Computers & Industrial Engineering, 124, 276-292. https://doi.org/10.1016/j.cie.2018.07.023
  • Noori, D., & Goldansaz, S.M. (2018) A hybrid imperialist competitive algorithm for minimizing makespan in multi-procwssor open shop, ASI Press, 1st Edition, Printed In the USA.
  • Azour, M. H., (2020) Robust design and analysis for quality engineering, Chapman & Hall, 1st Edition, Printed In the USA.
  • Jolai, F., & Goldansaz, S.M. (2013) A hybrid imperialist competitive algorithm for minimizing makespan in multi-procwssor open shop, ASI Press, 1st Edition, Printed In the USA. https://doi.org/10.1504/IJOR.2013.054436
  • Shamshirband, H. M., & Ghosn, S. B. (2016) Incorporating multi-criteria decision-making and fuzzy-value functions for flood susceptibility assessment: New generations (pp. 1183-1193). Springer.
  • Danio, B. M., & Ghosn, S. B. (2016) An efficient method for the open-shop scheduling problem using simulated annealing. In Information technology: New generations (pp. 1183-1193). Springer, Cham.‏ https://doi.org/10.1007/978-3-319-32467-8_102
  • MoradiR., Yazdani, D.S., & Sethi R. (2020) The complexity of flowshop and job-shop scheduling, Mathematics of Operations Research, 1(2), 117–129. https://doi.org/10.1287/moor.1.2.117
  • Wu, C.-C. N.-R.-H.-C. (2021) Robust scheduling for a two-stage assembly shop with scenario-dependent processing times, International Journal of Production Research, 59, 17, 5372-5387. https://doi.org/10.1080/00207543.2020.1778208
  • Ming, J. X (2021) Customization of on-site assembly services by integrating the internet of things and BIM technologies in modular integrated construction, Automation in Construction, 126, 103663. https://doi.org/10.1016/j.autcon.2021.103663
  • Daneshamooz, F., Jabbari, M., & Fattahi, P. (2015). A model for job shop scheduling with a parallel assembly stage to minimize makespan. Journal of Industrial Engineering Research in Production Systems, 2(4), 39-53.
  • Cheen W., Lee W., Tang G (2008) Dense open-shop schedules with release times, Theoretical Computer Science, 407, 389-399. https://doi.org/10.1016/j.tcs.2008.07.030
  • Whu A., Alcaide Lopez de Pablo D., Gonzalez-Martin C (2009) A network flow-based method to solve performance cost and makespan open-shop scheduling problems with time-windows, European Journal of Operational Research, 196 140-154. https://doi.org/10.1016/j.ejor.2008.02.031
  • Cheng P., (2003) On minimizing the weighted number of late jobs in unit execution time open-shops, European Journal of Operational Research, 149, 344-354. https://doi.org/10.1016/S0377-2217(02)00759-2
  • Torabi, S. A., Korzebor, M., & Doodman, M. (2021). A Location-Routing Model for Milk Supply Chain Network Design under Disruption Risks and Data Uncertainty. Journal of Industrial Management Perspective, 11(4), 9-35. )In Persian). https://doi.org/10.52547/jimp.11.4.9
  • Nakhaei Rad, Z., Zandhessami, H., & Tolouei Ashlaghi, A. (2021). Improving Collaborative Filtering Recommender System Results and Performance using Combination of Fuzzy Grey Wolf Optimizer Algorithm and Lion Optimization Algorithm. Journal of Industrial Management Perspective, 11(4), 197-222. )In Persian) https://doi.org/10.52547/JIMP.11.4.197.
  • Gholami, H. R., Mehdizadeh, E., & Naderi, B. (2018). Algorithm for Assembly Flowshops. Journal of Industrial Management Perspective, 8(1), 93-111 (In Persian).
Journal of Industrial Engineering Research in Production Systems
Volume 12, Issue 24
September 2024
Pages 133-145