A new approach to job shop-scheduling problem

• Autorzy: Mahdavinejad R. A.
• Języki publikacji: EN

Abstrakty

EN

Purpose: Ant colony optimization algorithm, not only promote the ability of this proposed algorithm, but also de- creases the total working time because of decreasing in setup times and modifying the working production line. Design/methodology/approach: In this paper, single-processors jobshop scheduling problems are solved by a heuristic algorithm based on the hybrid of priority dispatching rules according to an ant colony optimization algorithm. Findings: The objective function is to minimize the makespan, i.e. total completion time, in which a simultanous presence of various kinds of ferons is allowed. The process of finding the best solution will be improved by using the suitable hybrid of priority dispatching rules. Research limitations/implications: By solving some problems as samples (i.e. Fisher’s & Tomson’s problems), this algorithm is compared with the others. Practical implications: The utilization of one processor instead of multiple one, merging the industrial control network layer into system management layer and omission of processor execution layer in each axis and optimized using of multi-tasking capability of processor. Originality/value: The results show that when the size of the problem becomes larger, the deviation from lower limit increases, but its rate decreases with the size of the problems, so that it reaches to its limit.

Słowa kluczowe

EN

job shops scheduling; priority dispatching rules; makespan; hybrid heuristic algorithm

PL

plan pracy; zasada prirytetów; algorytm heurystyczny hybrydowy

• Wydawca: International OCSCO World Press
• Czasopismo: Journal of Achievements in Materials and Manufacturing Engineering
• Rocznik: 2010
• Tom: Vol. 41, nr 1-2
• Strony: 200--206
• Opis fizyczny: Bibliogr. 15 poz., rys., tabl.

Twórcy

autor

Mahdavinejad R. A.

• School of Mechanical Engineering, Faculty of Engineering, University of Tehran, Tehran, Iran,

Bibliografia

• 1. V. Genevs, F. Lombardi, V. Dakowski, M. Kuzinowski, Intelligent approach for optimal modeling of manufacturing systems, Journal of Achievements in Materials and Manufacturing Engineering 14 (2006) 97-103.
• 2. I.B. Silva, G.F. Batalha, M. Stipkovik Filho, F.Z. Ceccarelli, J.B. Anjos, M. Fesz, Integrated product and process system with continuous improvement in the auto parts industry, Journal of Achievements in Materials and Manufacturing Engineering 34/2 (2009) 204-210.
• 3. B. Krupińska, D. Szewieczek, L.A. Dobrzański, Computer- aided optimization of technological process, Archives of Materials Science and Engineering 36/2 (2009) 96-102.
• 4. E. Shevtshenko, T. Karaulova, S. Kramarenko, Y. Wang, Manufacturing project management in the conglomerate enterprises supported by IDSS, Journal of Achievements in Materials and Manufacturing Engineering 33/1 (2009) 94-102.
• 5. J. Madejski, Survey of the agent-based approach to intelligent manufacturing, Journal of Achievements in Materials and Manufacturing Engineering 21/1(2007) 67-70.
• 6. K. Metaxiotis, D. Askounis, J. Psarras, An object-oriented analysis and design of a model for production planning and control in industry, International Journal of Advanced Manufacturing Technology 18 (2001) 657-664.
• 7. E. Demirkol, S. Mehta, R. Uzsoy, A computational study of shifting bottleneck procedures for shop scheduling problems, Journal of Heuristic 3/2 (2003) 111-137.
• 8. P. Brucker, J. Hurink, F. Warner, Improving local search heuristic for some scheduling problems part I, Discrete Applied Mathematics 65/1-3 (1996) 97-122.
• 9. G. Shi, A genetic algorithm applied to a classic job-shop scheduling problem, International Journal of System Science 28/1 (1997) 25-32.
• 10. P. Brucker, B. Jurisch, B. Sievers, A branch and bound algorithm for the job- shop scheduling problem, Discrete Applied Mathematics 49 (1994) 109-127.
• 11. E. Demirkol, S. Mehta, R. Uzsoy, A computational study of shifting bottleneck procedures for shop scheduling problems, Journal of Heuristic 3/2 (1997) 111-137.
• 12. A.S. Jain, S. Meeran, Job-shop scheduling using neural networks, International Journal of Production Research 36/5 (1998) 1249-1272.
• 13. T. Yamada, R. Nakano, Scheduling by genetic local search with multi-stepcrossover, Proceedings of the 4th International Conference "Parallel Problem Solving from Nature" PPSN'IV, Berlin, Germany, 1996, 960-969.
• 14. A. Colorni, M. Dorigo, V. Maniezzo, M. Trubian, Ant- system for job-shop scheduling, Belgian Journal of Operations Research, Statistics and Computer Science 34/1 (2002) 39-54.
• 15. T. Yamada, R. Nakano, Job-shop scheduling by simulated annealing combined with deterministic local search, Proceedings of the Metaheuristic International Conference MIC'95, Breckenridge, Colorado, USA, 1995, 344-349