Coexistent scheduling in the tandem flow path configuration of a flexible manufacturing system by using an advanced grey wolf optimizer

Document Type : Article

Authors

1 Department of Mechanical and Automation Engineering, Indira Gandhi Delhi Technical University for Women, Delhi, India

2 Department of Mechanical and Automation Engineering, G.B. Pant Engineering College, Okhla, Delhi, India

3 Department of Mechanical Engineering, The National Institutes of Technology, Kurukshetra, Haryana, India

4 Department of Progress Engineering, Iran University of Science and Technology, Tehran, Iran

Abstract

The use of material handling robots (MHRs) for efficient material handling operations in the flexible manufacturing systems (FMS) has gained wide popularity and acceptability across the automated production industries. The coexistent scheduling between jobs and MHRs improves the overall efficiency of the FMS significantly. In the present study, the coexistent scheduling between the MHRs and the jobs under production in the FMS is carried out by using an advanced grey wolf optimization (AGWO) algorithm. The proposed FMS layout is made up of the tandem flow path configurations for the movements of MHRs. The FMS constitutes six flexible manufacturing cells (FMCs) partitioned in six zones and served by six MHRs deployed in each partitioned zone for efficient material handling operations. To develop the coexistent schedule between MHRs and jobs, a combined objective function is formulated by combining the two diverging objectives and solved by using the AGWO algorithm. The combined objective function yield for coexistent production scheduling in FMS, operating with nineteen work centers (WC) and six MHRs to produce thirty-six types of jobs and sixty-six types of jobs in varying batch production quantities is also reported in the paper.

Keywords


References:
1. Mohapatra, P., Kumar, N., Matta, A., et al. "A nested partitioning-based approach to integrate process planning and scheduling in a flexible manufacturing environment", International Journal of Computer Integrated Manufacturing, 28(10), pp. 1077-1091 (2015).
2. Haq, A.N., Karthikeyan, T., and Dinesh, M. "Scheduling decisions in FMS using a heuristic approach", The International Journal of Advanced Manufacturing Technology, 22(5-6), pp. 374-379 (2003).
3. Chaudhry, I.A., Mahmood, S., and Shami, M. "Simultaneous scheduling of machines and automated guided vehicles in flexible manufacturing systems using genetic algorithms", Journal of the Central South University of Technology, 18(5), p. 1473 (2011).
4. Chawla, V.K., Chanda, A.K., Angra, S., et al. "Simultaneous dispatching and scheduling of multi-load AGVs in FMS-A simulation study", Materials Today: Proceedings, 5(11), pp. 25358-25367 (2018).
5. Chawla, V., Chanda, A., and Angra, S. "The scheduling of automatic guided vehicles for the workload balancing and travel time minimization in the  flexible manufacturing system by the nature-inspired algorithm", Journal of Project Management, 4(1), pp. 19- 30 (2019).
6. Udhayakumar, P. and Kumanan, S. "Integrated scheduling of  flexible manufacturing systems using evolutionary algorithms", The International Journal of Advanced Manufacturing Technology, 61(5 -8), pp. 621-635 (2012).
7. Chawla, V.K., Chanda, A.K., and Angra, S. "Automatic guided vehicle systems in flexible manufacturing system-A review", International Journal of Industrial Engineering: Theory, Applications, and Practice, 26(5), pp. 737-765 (2019a).
8. Bozer, Y.A. and Srinivasan, M.M. "Tandem configurations for automated guided vehicle systems and the analysis of single-vehicle loops", IIE Transactions, 23(1), pp. 72-82 (1991).
9. Bozer, Y.A. and Srinivasan, M.M. "Tandem AGV systems: A partitioning algorithm and performance comparison with conventional AGV systems", European Journal of Operational Research, 63(2), pp. 173- 191 (1992).
10. Angra, S., Chanda, A., and Chawla, V. "Comparison and evaluation of job selection dispatching rules for integrated scheduling of multi-load automatic guided vehicles serving in variable-sized  flexible manufacturing system layouts: A simulation study", Management Science Letters, 8(4), pp. 187-200 (2018).
11. Chawla, V.K., Chanda, A.K., Angra, S., et al. "Effect of nature-inspired algorithms and hybrid dispatching rules on the performance of automatic guided vehicles in the flexible manufacturing system", Journal of the Brazilian Society of Mechanical Sciences and Engineering, 41(10), p. 391 (2019c).
12. Chawla, V., Angra, S., Suri, S., et al. "A synergic framework for cyber-physical production systems in the context of Industry 4.0 and beyond", International Journal of Data and Network Science, 4(2), pp. 237- 244 (2020).
13. Udhayakumar, P. and Kumanan, S. "Task scheduling of AGV in FMS using non-traditional optimization Techniques", International Journal of Simulation Modelling, 9(1), pp. 28-39 (2010).
14. Chawla, V.K., Chanda, A., and Angra, S. "Sustainable multi-objective scheduling for automatic guided vehicles and  flexible manufacturing system by a grey wolf optimization algorithm", International Journal of Data and Network Science, 2(1), pp. 27-40 (2018a).
15. Chawla, V., Chanda, A., and Angra, S. "Material handling robots  fleet size optimization by a heuristic", Journal of Project Management, 4(3), pp. 177-184 (2019b).
16. Akturk, M.S. and Yilmaz, H. "Scheduling of automated guided vehicles in a decision-making hierarchy", International Journal of Production Research, 34(2), pp. 577-591 (1996).
17. Veeravalli, B., Rajesh, G., and Viswanadham, N. "Design and analysis of optimal material distribution policies in flexible manufacturing systems using a single AGV", International Journal of Production Research, 40(12), pp. 2937-2954 (2002).
18. Le-Anh, T. and De Koster, M.B.M. "A review of the design and control of automated guided vehicle systems", European Journal of Operational Research, 171(1), pp. 1-23 (2006).
19. Caumond, A., Lacomme, P., Moukrim, A., et al. "A MILP for scheduling problems in an FMS with one vehicle", European Journal of Operational Research, 199(3), pp. 706-722 (2009).
20. Dumas, Y., Desrosiers, J., and Soumis, F. "The pickup and delivery problem with time windows", European Journal of Operational Research, 54(1), pp. 7-22 (1991).
21. Bilge, U. and Ulusoy, G. "A time window approach to simultaneous scheduling of machines and material handling systems in an FMS", Operations Research, 43(6), pp. 1058-1070 (1995).
22. Rashidi, H. "Scheduling in container terminals using the network simplex algorithm", Journal of Optimization in Industrial Engineering, pp. 9-16 (2010).
23. Fazlollahtabar, H., Saidi-Mehrabad, M., and Balakrishnan, J. "Mathematical optimization for earliness/ tardiness minimization in multiple automated guided vehicle manufacturing systems via integrated heuristic algorithms", Robotics and Autonomous Systems, 72, pp. 131-138 (2015).
24. Rashidi, H. and Tsang, E., Vehicle Scheduling in Port Automation: Advanced Algorithms for Minimum Cost Flow Problems, CRC Press (2015).
25. Jahromi, M.H.M.A., Tavakkoli-Moghaddam, R., Makui, A., et al. "A new mathematical model for a scheduling problem of dynamic machine-tool selection and operation allocation in a flexible manufacturing system: A modified evolutionary algorithm", Scientia Iranica, 24(2), pp. 765-777 (2017).
26. Rashidi Komijan, A., Tavakkoli-Moghaddam, R., and Dalil, S.A. "A mathematical model for an integrated airline  fleet assignment and crew scheduling problem solved by vibration damping optimization", Scientia Iranica, 28(2), pp. 970-984 (2021).
27. Habibi, F., Barzinpour, F., and Sadjadi, S.J. "A mathematical model for project scheduling and material ordering problem with sustainability considerations: A case study in Iran", Computers & Industrial Engineering, 128, pp. 690-710 (2019).
28. Sharma, N., Chawla, V., and Ram, N. "Comparison of machine learning algorithms for the automatic programming of a computer numerical control machine", International Journal of Data and Network Science, 4(1), pp. 1-14 (2020).
29. Savelsbergh, M.W. and Sol, M. "The general pickup and delivery problem", Transportation Science, 29(1), pp. 17-29 (1995).
30. Meersmans, P.J.M. "Optimization of container handling systems (No. 271)", Tinbergen Institute Research Series (2002).
31. Yang, J., Jaillet, P., and Mahmassani, H. "Real-time multivehicle truckload pickup and delivery problems", Transportation Science, 38(2), pp. 135-148 (2004).
32. Ab Rashid, M.F.F., Tiwari, A., and Hutabarat, W. "Comparison of sequential and integrated optimization approaches for ASP and ALB", Procedia CIRP, 63, pp. 505-510 (2017).
33. Chawla, V.K., Chanda, A.K., and Angra, S. "Multiload AGVs scheduling by application of modified memetic particle swarm optimization algorithm", Journal of the Brazilian Society of Mechanical Sciences and Engineering, 40(9), p. 436 (2018b).
34. Jerald, J., Asokan, P., Saravanan, R., et al. "Simultaneous scheduling of parts and automated guided vehicles in an FMS environment using an adaptive genetic algorithm", The International Journal of Advanced Manufacturing Technology, 29(5-6), pp. 584- 589 (2006).
35. Chanda, A., Angra, S., and Chawla, V. "A modified memetic particle swarm optimization algorithm for sustainable multi-objective scheduling of automatic guided vehicles in a  flexible manufacturing system", International Journal of Computer-Aided Manufacturing, 4(1), pp. 33-47 (2018).
36. Buddala, R. and Mahapatra, S.S. "An integrated approach for scheduling flexible job-shop using teachinglearning- based optimization method", Journal of Industrial Engineering International, 15(1), pp. 181-192 (2019).
37. Correa, A.I., Langevin, A., and Rousseau, L.M. "Scheduling and routing of automated guided vehicles: A hybrid approach", Computers & Operations Research, 34(6), pp. 1688-1707 (2007).
38. Joshi, S. and Smith, J.S., Computer Control of flexible Manufacturing Systems: Research and Development, Springer Science & Business Media (2012). 
39. Chawla, V.K., Chanda, A.K., and Angra, S. "Evaluationof tool selection rules in the flexible manufacturing system", International Journal of Industrial Engineering & Production Research, 31(1), pp. 131- 142 (2020a).
40. Gamberi, M., Manzini, R., and Regattieri, A. "A new approach for the automatic analysis and control of material handling systems: integrated layout  flow analysis (ILFA)", The International Journal of Advanced Manufacturing Technology, 41(1-2), p. 156 (2009).
41. Fazlollahtabar, H. and Saidi-Mehrabad, M. "Methodologies to optimize automated guided vehicle scheduling and routing problems: a review study", Journal of Intelligent & Robotic Systems, 77(3-4), pp. 525-545 (2015).
42. Nishi, T., Hiranaka, Y., and Grossmann, I.E. "A bilevel decomposition algorithm for simultaneous production scheduling and conflict-free routing for automated guided vehicles", Computers & Operations Research, 38(5), pp. 876-888 (2011).
43. NageswaraRao, M., NarayanaRao, K., and Ranaga Janardhana, G. "Hybrid meta heuristic algorithm for simultaneous scheduling of machines and AGVs in flexible manufacturing environment", Canadian Journal of Basic and Applied Sciences, 3(02), pp. 29-44 (2015).
44. Umar, U.A., Ariffin, M.K.A., Ismail, N., et al. "Hybrid multi-objective genetic algorithms for integrated dynamic scheduling and routing of jobs and automatedguided vehicles (AGV) in flexible manufacturing systems (FMS) environment", The International Journal of Advanced Manufacturing Technology, 81(9-12), pp. 2123-2141 (2015).
45. Mallikarjuna, K., Veeranna, V., and Reddy, K.H. "A new meta-heuristics for optimum design of loop layout in a flexible manufacturing system with integrated scheduling", The International Journal of Advanced Manufacturing Technology, 84(9-12), pp. 1841-1860 (2016).
46. Zheng, Y., Xiao, Y., and Seo, Y. "A hybrid heuristic algorithm for the integrated problem of machine scheduling and unidirectional  flow path design", International Journal of Industrial Engineering, 22(6) (2015).
47. Mirjalili, S., Mirjalili, S.M., Lewis, A., et al. "Advances in engineering software", Renewable and Sustainable Energy Reviews, pp. 46-61 (2014). 48. Mirjalili, S., Saremi, S., Mirjalili, S.M., et al. "Multiobjective grey wolf optimizer: a novel algorithm for multi-criterion optimization", Expert Systems with Applications, 47, pp. 106-119 (2016).
49. Bozorg-Haddad, O., Advanced Optimization by Nature-Inspired Algorithms, Singapore, Springer (2018).
50. Nawaz, M., Enscore Jr, E.E., and Ham, I. "A heuristic algorithm for the m-machine, n-job  flow-shop sequencing problem", Omega, 11(1), pp. 91-95 (1983).