DOI QR코드

DOI QR Code

잉크 색상 변화가 존재하는 인쇄 공정의 스케줄링

Scheduling of Printing Process in which Ink Color Changes Exist

  • 문재경 (한국생산기술연구원 디지털헬스케어연구부문) ;
  • 엄현섭 (한국생산기술연구원 디지털헬스케어연구부문) ;
  • 태현철 (한국생산기술연구원 디지털헬스케어연구부문)
  • Moon, Jae Kyeong (Department of Digital Healthcare Research Korea Institute of Industrial Technology) ;
  • Uhm, Hyun Seop (Department of Digital Healthcare Research Korea Institute of Industrial Technology) ;
  • Tae, Hyun Chul (Department of Digital Healthcare Research Korea Institute of Industrial Technology)
  • 투고 : 2021.10.18
  • 심사 : 2021.12.24
  • 발행 : 2021.12.31

초록

The printing process can have to print various colors with a limited capacity of printing facility such as ink containers that are needed cleaning to change color. In each container, cleaning time exists to assign corresponding inks, and it is considered as the setup cost required to reduce the increasing productivity. The existing manual method, which is based on the worker's experience or intuition, is difficult to respond to the diversification of color requirements, mathematical modeling and algorithms are suggested for efficient scheduling. In this study, we propose a new type of scheduling problem for the printing process. First, we suggest a mathematical model that optimizes the color assignment and scheduling. Although the suggested model guarantees global optimality, it needs a lot of computational time to solve. Thus, we decompose the original problem into sequencing orders and allocating ink problems. An approximate function is used to compute the job scheduling, and local search heuristic based on 2-opt algorithm is suggested for reducing computational time. In order to verify the effectiveness of our method, we compared the algorithms' performance. The results show that the suggested decomposition structure can find acceptable solutions within a reasonable time. Also, we present schematized results for field application.

키워드

과제정보

This research was a part of the project titled 'forest science-technology R&D program (2021383A00-2123-0101)', funded by the Korea Forestry Promotion Institute (Korea National Arboretum), Korea. This research was a part of the R&D reserve project, funded by the Korea Institute of Industrial Technology, Korea.

참고문헌

  1. Artigues, C., Feillet, D., A branch and bound method for the job-shop problem with sequence-dependent setup times, Annals of Operations Research, 2008, Vol. 159, No. 1, pp. 135-159. https://doi.org/10.1007/s10479-007-0283-0
  2. Bellman, R., Dynamic Programming Treatment of the Travelling Salesman Problem, Journal of the ACM, 1962, Vol. 9, No. 1, pp. 61-63. https://doi.org/10.1145/321105.321111
  3. Garfinkel, R.S., Technical Note-On Partitioning the Feasible Set in a Branch-and-Bound Algorithm for the Asymmetric Traveling-Salesman Problem, Operations Research, 1973, Vol. 21, No. 1, pp. 340-343. https://doi.org/10.1287/opre.21.1.340
  4. Glover, F., Tabu Search - Part I ORSA, Journal on Computing, 1989, Vol. 1, No. 3, pp. 190-206.
  5. Glover, F., Tabu Search - Part II ORSA, Journal on Computing, 1990, Vol. 2, No. 1, pp. 4-32.
  6. Gupta, J.N.D., Flowshop Schedules With Sequence Dependent Setup TIMES, Journal of the Operations Research Society of Japan, 1986, Vol. 29, No. 3, pp. 206-219. https://doi.org/10.15807/jorsj.29.206
  7. Joo, C.M., An Improved Ant Colony System for Parallel-Machine Scheduling Problem with Job Release Times and Sequence-Dependent Setup Times, Journal of the Korean Institute of Industrial Engineers, 2009, Vol. 35, No. 4, pp. 218-225.
  8. Kirkpatrick, S., Gelatt, C.D., Vecchi, M.P., Optimization by Simulated Annealing, Science, 1983, Vol. 220, No.4598, pp. 671-680. https://doi.org/10.1126/science.220.4598.671
  9. Laporte, G., The traveling salesman problem: An overview of exact and approximate algorithms, European Journal of Operational Research, 1992, Vol. 59, No. 2, pp. 231-247. https://doi.org/10.1016/0377-2217(92)90138-Y
  10. Lee, J.Y., Jeong, B.J., Heuristic Algorithms for a Two-Machine Flowshop Scheduling Problem with Urgent Jobs and Sequence-Dependent Setup Times, Korean Management Science Review, 2020, Vol. 37, No. 1, pp. 47-60. https://doi.org/10.7737/kmsr.2020.37.1.047
  11. Lin, S., Kernighan, B.W., An effective heuristic algorithm for the traveling-salesman problem, Operations Research, 1973, Vol. 21, No. 2, pp. 498-516. https://doi.org/10.1287/opre.21.2.498
  12. Nadesri, B., Ghomi, S.M.T.F., Aminnayeri, M., A high performing metaheuristic for job shop scheduling with sequence-dependent setup times, Applied Soft Computing, 2010, Vol. 10, No. 3, pp. 703-710. https://doi.org/10.1016/j.asoc.2009.08.039
  13. Rosenkrantz, D.J., Stearns, R.E., Lewis II, P.M., An analysis of several heuristics for the traveling salesman problem, SIAM Journal on Computing, 1977, Vol. 6, No. 3, pp. 563-581. https://doi.org/10.1137/0206041
  14. Shin, H.J., Kim, S.S., Ko, K.S., A Tabu Search Algorithm for Single Machine Scheduling Problem with Job Release Times and Sequence-dependent Setup Times, Journal of the Korean Institute of Industrial Engineers, 2001, Vol. 27, No. 2, pp. 158-168.
  15. Vela, C.R., Varela, R., Gonzalez, M.A., Local search and genetic algorithm for the job shop scheduling problem with sequence dependent setup times, Journal of Heuristics, 2010, Vol. 16, No. 1, pp. 139-165. https://doi.org/10.1007/s10732-008-9094-y
  16. WIKIPEDIA, https://en.wikipedia.org/wiki/2-opt.
  17. Yoo, W.S., Kim, S.J., Kim, K.H., Real-Time Scheduling Scheme based on Reinforcement Learning Considering Minimizing Setup Cost, The Journal of Society for e-Business Studies, Vol. 25, No. 2, pp. 15-27.
  18. Yoo, W.S., Seo, J.H., Lee, D.H., Kim, D.H., Kim, K.H., Scheduling Generation Model on Parallel Machines with Due Date and Setup Cost Based on Deep Learning, The Journal of Society for e-Business Studies, Vol. 24, No. 3, pp. 99-110.
  19. Yu, S.Y., Scheduling of Production Process with Setup Cost depending Job Sequence, Management & Information Systems Review, 2015, Vol. 34, No.2, pp. 67-78. https://doi.org/10.29214/DAMIS.2015.34.2.004