Scheduling a single mobile robot for part-feeding tasks of production lines

Journal of Intelligent Manufacturing

Volumn 25, Issue 6, 2014, Pages 1271-1287

  Dang, Quang Vinh ^a   Nielsen, Izabela ^a   Steger Jensen, Kenn ^a   Madsen, Ole ^a  

^a AALBORG UNIVERSITY   (Denmark)

Author keywords

Genetic algorithm; MIP; Mobile robot; Part feeding; Scheduling

Indexed keywords

FEEDING; GENETIC ALGORITHMS; HEURISTIC PROGRAMMING; INTEGER PROGRAMMING; MOBILE ROBOTS; SCHEDULING;

COMPUTATIONAL EXPERIMENT; INVENTORY SYSTEMS; MIXED INTEGER PROGRAMMING MODEL; NEAR-OPTIMAL SOLUTIONS; PART FEEDING; PERFORMANCE CRITERION; PLANNING HORIZONS; PRODUCTION LINE;

ROBOT PROGRAMMING;

EID: 84912031695     PISSN: 09565515     EISSN: 15728145     Source Type: Journal    
DOI: 10.1007/s10845-013-0729-y     Document Type: Article

References (43)

1. Ascheuer, N., Escudero, L. F., Grotschel, M., & Stoer, M. A. (1993). Cutting plane approach to the sequential ordering problem (with application to job scheduling in manufacturing). SIAM Journal of Optimization, 3(1), 25–42.
2. Askin, R. G., & Stanridge, C. R. (1993). Modeling and analysis of manufacturing systems. New York: Wiley.
3. Carlton, W. B., & Barnes, J. W. (1996). Solving the traveling salesman problem with time windows using tabu search. IIE Transactions, 28(8), 617–629.
4. Carpaneto, G., & Toth, P. (1980). Some new branching and bounding criteria for the asymmetric travelling salesman problem. Management Science, 26(7), 736–743.
5. Carpaneto, G., Dell’Amico, M., & Toth, P. (1995). Exact solution of large-scale, asymmetric traveling salesman problems. ACM Transactions on Mathematical Software, 21(4), 394–409.
6. Chatterjee, S., Carrera, C., & Lynch, L. A. (1996). Genetic algorithms and traveling salesman problems. European Journal of Operational Research, 9, 490–510.
7. Chen, S. M., & Chien, C. Y. (2011). Solving the traveling salesman problem based on the genetic simulated annealing ant colony system with particle swarm optimization techniques. Expert Systems with Applications, 38(12), 14439–14450.
8. Chen, C., & Tseng, C. (1996). The path and location planning of workpieces by genetic algorithms. Journal of Intelligent Manufacturing, 7(1), 69–76.
9. Choi, I. C., Kim, S. I., & Kim, H. S. (2003). A genetic algorithm with a mixed region search for the asymmetric traveling salesman problem. Computers and Operations Research, 30(5), 773–786.
10. Crama, Y., Kats, V., van de Klundert, J., & Levner, E. (2000). Cyclic scheduling in robotic flow shops. Annals of Operations Research, 96(1–4), 97–124.
11. Dang, Q. V., Nielsen, I., & Steger-Jensen, K. (2011). Scheduling a single mobile robot for feeding tasks in a manufacturing cell. In Proceedings of international conference advances in production management systems, Stavanger, Norway
12. Dang, Q. V., Nielsen, I., & Bocewicz, G. (2012a). Trends in PAAMS, AISC 157. In J. M. C. Rodríguez (Ed.), A genetic algorithm-based heuristic for part-feeding mobile robot scheduling problem (pp. 85–92). Berlin, Heidelberg: Springer.
13. Dang, Q. V., Nielsen, I., & Steger-Jensen, K. (2012b). Ecoproduction & logistics—new trends and business practices. In P. Golinska (Ed.), Scheduling a single mobile robot incorporated into production environment (pp. 185–201). Berlin, Heidelberg: Springer.
14. Edan, Y., Flash, T., Peiper, U. M., Shmullevich, I., & Sarig, Y. (1991). Near-minimum-time task planning for fruit-picking robots. IEEE Transactions on Robotics and Automation, 7(1), 48–55.
15. Geng, X., Chen, Z., Yang, W., Shi, D., & Zhao, K. (2011). Solving the travelling salesman problem based on an adaptive simulated annealing algorithm with greedy search. Applied Soft Computing, 11(4), 3680–3689.
16. Germs, R., Goldengorin, B., & Turkensteen, M. (2012). Lower tolerance-based branch and bound algorithms for the ATSP. Computer and Operations Research, 39(2), 291–298.
17. Goldberg, D. E. (1989). Genetic algorithms in search, optimization, and machine learning. New York: Addison-Wesley.
18. Han, M. H., McGinnis, L. F., Shieh, J. S., & White, J. A. (1987). On sequencing retrievals in an automated storage/retrieval system. IIE Transactions, 19(1), 56–66.
19. Hasegawa, M., & Ikeguchi, T. (2002). Solving large scale traveling salesman problems by chaotic neurodynamics. Neural Networks, 15(2), 271–283.
20. Ho, W., & Ji, P. (2004). A hybrid genetic algorithm for component sequencing and feeder arrangement. Journal of Intelligent Manufacturing, 15(3), 307–315.
21. Hurink, J., & Knust, S. (2002). A tabu search algorithm for scheduling a single robot in a job-shop environment. Discrete Applied Mathematics, 119(1–2), 181–203.
22. Landrieu, A., Mati, Y., & Binder, Z. (2001). A tabu search heuristic for the single vehicle pickup and delivery problem with time windows. Journal of Intelligent Manufacturing, 12(5–6), 497–508.
23. Lin, L., Shinn, S. W., Gen, M., & Hwang, H. (2006). Network model and effective evolutionary approach for AGV dispatching in manufacturing system. Journal of Intelligent Manufacturing, 17(4), 465–477.
24. Liu, F., & Zeng, G. (2009). Study of genetic algorithm with reinforcement learning to solve the TSP. Expert Systems with Applications, 36(3), 6995–7001.
25. López-Ibáñez, M., & Blum, C. (2010). Beam-ACO for the travelling salesman problem with time windows. Computers and Operations Research, 37(9), 1570–1583.
26. Maimon, O., Braha, D., & Seth, V. (2000). A neural network approach for a robot task sequencing problem. Artificial Intelligence in Engineering, 14(2), 175–189.
27. Miller, D. L., & Pekny, J. F. (1991). Exact solution of large asymmetric traveling salesman problems. Science, 251(4995), 754–761.
28. Moon, C., Kim, J., Choi, G., & Seo, Y. (2002). An efficient genetic algorithm for the traveling salesman problem with precedence constraints. European Journal of Operational Research, 140(3), 606–617.
29. Moon, C., Seo, Y., Yun, Y., & Gen, M. (2006). Adaptive genetic algorithm for advanced planning in manufacturing supply chain. Journal of Intelligent Manufacturing, 17(4), 509–522.
30. Ohlmann, J. W., & Thomas, B. W. (2007). A compressed-annealing heuristic for the traveling salesman problem with time windows. INFORMS Journal on Computing, 19(1), 80–90.
31. Potvin, J. Y. (1996). Genetic algorithms for the traveling salesman problem. Annals of Operation Research, 63(3), 339–370.
32. Ratliff, H. D., & Rosenthal, A. S. (1983). Order-picking in a rectangular warehouse: A solvable case of the traveling salesman problem. Operations Research, 31(3), 507–521.
33. Reuther, H., Simon, B. & Mads, H. (2010). 3D simulation used for evaluating the use and implementation of the mobile manipulator ”Little Helper” at Grundfos A/S. In H. Hvolby (Ed.), Proceedings of the 12th international modern information technology in the innovation processes of the industrial enterprises ( MITIP) conference, 29–31 August 2010 (pp. 9–18). Aalborg: Centre for Logistics, Aalborg University.
34. Silver, E. A., Pyke, D. F., & Peterson, R. (1998). Inventory management and production planning and scheduling. New York: Wiley.
35. Snyder, L. V., & Daskin, M. S. (2006). A random-key genetic algorithm for the generalized traveling salesman problem. European Journal of Operational Research, 174(1), 38–53.
36. Suárez, R., & Rosell, J. (2005). Feeding sequence selection in a manufacturing cell with four parallel machines. Robotics and Computer-Integrated Manufacturing, 21(3), 185–195.
37. Syslo, M. M., Deo, N., & Kowalik, J. S. (1983). Discrete optimization algorithms: With Pascal programs. New Jersey: Prentice-Hall.
38. Toth, P., & Vigo, D. (2002). The vehicle routing problem. Philadelphia: SIAM.
39. Tsai, C. F., Tsai, C. W., & Tseng, C. C. (2004). A new hybrid heuristic approach for solving large traveling salesman problem. Information Sciences, 166(1–4), 67–81.
40. Tsujimura, Y., & Gen, M. (1999). Parts loading scheduling in a flexible forging machine using an advanced genetic algorithm. Journal of Intelligent Manufacturing, 10(2), 149–159.
41. Turkensteen, M., Ghosh, D., Goldengorin, B., & Sierksma, G. (2008). Tolerance-based branch and bound algorithms for the ATSP. European Journal of Operational Research, 189(3), 775–788.
42. Xing, L. N., Chen, Y. W., Yang, K. W., Hou, F., Shen, X. S., & Cai, H. P. (2008). A hybrid approach combining an improved genetic algorithm and optimization strategies for the asymmetric traveling salesman problem. Engineering Applications of Artificial Intelligence, 21(8), 1370–1380.
43. Zacharia, P Th, & Aspragathos, N. A. (2005). Optimal robot task scheduling based on genetic algorithms. Robotics and Computer-Integrated Manufacturing, 21(1), 67–79.