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Contents 1
Scheduling for assembly line with human-robot collaboration / Kosuke Inoue ; Hideki Aoyama 1
[요약] 1
1. Introduction 1
2. Scheduling Problem Setting 2
2.1. Assembly Line Model to Be Scheduled 2
2.2. Condition Setting for Machine Tool Assembly Line 3
3. Scheduling Method based on GENETIC Algorithm 4
3.1. Gene Expression for Scheduling 4
3.2. Scheduling Process 4
3.3. Chromosome Crossover Method 5
3.4. Chromosome Mutation Method 5
3.5. Chromosome Selection Method 6
3.6. Scheduling Policy 6
3.7. Process Allocation(Dispatching) Policy 6
3.8. Schedule Evaluation : Calculation of Fitness Evaluation Value 7
4. Evaluation Experiment 7
4.1. Experimental Conditions 7
4.2. Scheduling Results and Discussion 9
5. Conclusion 10
REFERENCES 10
[저자소개] 11
번호 | 참고문헌 | 국회도서관 소장유무 |
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1 | Borreguero-Sanchidrián, T., Pulido, R., García-Sánchez, Á., Ortega-Mier, M., (2017), Flexible job shop scheduling with operators in aeronautical manufacturing: A case study, IEEE Access, 6, 224-233. | 미소장 |
2 | Chen, C., Tiong, L. K., Chen, I.-M., (2019), Using a genetic algorithm to schedule the space-constrained AGV-based prefabricated bathroom units manufacturing system, International Journal of Production Research, 57(10), 3003-3019. | 미소장 |
3 | Elmi, A., Topaloglu, S., (2013), A scheduling problem in blocking hybrid flow shop robotic cells with multiple robots, Computers & Operations Research, 40(10), 2543-2555. | 미소장 |
4 | Fu, G., (2004), A method for solving jobshop scheduling problems with limited common buffers, transactions of the institute of systems, Control and Information Engineers, 17(3), 113-121. Japanese | 미소장 |
5 | Gong, G., Deng, Q., Gong, X., Liu, W., Ren, Q., (2018), A new double flexible job-shop scheduling problem integrating processing time, green production, and human factor indicators, Journal of Cleaner Production, 174, 560-576. | 미소장 |
6 | Heger, J., Voss, T., (2018), Optimal scheduling of AGVs in a reentrant blocking job-shop, Procedia Cirp, 67, 41-45. | 미소장 |
7 | Hino, R., Kusumi, T., Yoo, J. K., Shimizu, Y., (2005). Job shop scheduling focusing on role of buffer, Transactions of the Japan Society of Mechanical Engineers, Series C, 71(702), 685-692. Japanese | 미소장 |
8 | Liu, S. Q., Kozan, E., Masoud, M., Zhang, Y., Chan, F. T., (2018), Job shop scheduling with a combination of four buffering constraints, International Journal of Production Research, 56(9), 3274-3293. | 미소장 |
9 | Maleki-Darounkolaei, A., Modiri, M., Tavakkoli-Moghaddam, R., Seyyedi, I., (2012), A three-stage assembly flow shop scheduling problem with blocking and sequence-dependent set up times, Journal of Industrial Engineering International, 8(1), 1-7. | 미소장 |
10 | Matsui, S., Yamada, S., (2007), An empirical performance evaluation of a parameter-free genetic algorithm for job-shop scheduling problem, 2007 IEEE Congress on Evolutionary Computation, 3796-3803. | 미소장 |
11 | Peng, C., Fang, Y., Lou, P., Yan, J., (2018), Analysis of doubleresource flexible job shop scheduling problem based on genetic algorithm, Proceedings of the 2018 IEEE International Conference on Networking, Sensing and Control (ICNSC), 1-6. | 미소장 |
12 | Sawai, H., Kizu, S., (1998), Parameter-free genetic algorithm inspired by “disparity theory of evolution”, Proceedings of the International Conference on Parallel Problem Solving from Nature, 702-711. | 미소장 |
13 | Zeng, C., Tang, J., Yan, C., (2014), Scheduling of no buffer job shop cells with blocking constraints and automated guided vehicles, Applied Soft Computing, 24, 1033-1046. | 미소장 |
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