How to cite this paper
APA: Chawla, V., Chanda, A & Angra, S. (2018). Sustainable multi-objective scheduling for automatic guided vehicle and flexible manufacturing system by a grey wolf optimization algorithm. International Journal of Data and Network Science, 2(1), 27-40.
Chicago/Turabian: Chawla, V., Chanda, A & Angra, S. 2018. "Sustainable multi-objective scheduling for automatic guided vehicle and flexible manufacturing system by a grey wolf optimization algorithm." International Journal of Data and Network Science 2, no. 1 (2018): 27-40.
AMA: Chawla, V., Chanda, A & Angra, S. Sustainable multi-objective scheduling for automatic guided vehicle and flexible manufacturing system by a grey wolf optimization algorithm. International Journal of Data and Network Science. 2018;2(1):27-40.
References
Abdelmaguid, T. F., Nassef, A. O., Kamal, B. A., & Hassan, M. F. (2004). A hybrid GA/heuristic ap-proach to the simultaneous scheduling of machines and automated guided vehicles. International Journal of Production Research, 42(2), 267-281.
Angra, S., Chanda, A., & Chawla, V. (2018). Comparison and evaluation of job selection dispatching rules for integrated scheduling of multi-load automatic guided vehicles serving in variable sized flex-ible manufacturing system layouts: A simulation study. Management Science Letters, 8(4), 187-200.
Bozorg-Haddad, O. (2017). Advanced Optimization by Nature-Inspired Algorithms.
Chawla, V., Chanda, A., Angra, S., & Chawla, G. (2018a). The sustainable project management: A re-view and future possibilities. Journal of Project Management, 3(3), 157-170.
Chawla, V.K., Chanda, A., & Angra, S. (2018b). A Clonal Selection Algorithm for Minimizing Dis-tance Travel & Back Tracking of Automatic Guided Vehicles in Flexible Manufacturing System. Journal of The Institution of Engineers (India): Series C, DOI: 10.1007/s40032-018-0447-5.
Chawla, V.K., Chanda, A., & Angra, S. (2018c). Scheduling of multi-load AGVs in FMS by modified memetic particle swarm optimization algorithm. Journal of Project Management, 3(1), 39-54.
Chawla, V.K., Chanda, A., & Angra, S. (2018d). Automatic guided vehicles fleet size optimization for flexible manufacturing system by grey wolf optimization algorithm. Management Science Letters, 8(2), 79-90.
Deb, K. (2001). Multi-objective optimization using evolutionary algorithms (Vol. 16). John Wiley & Sons.
Egbelu, P. J., & Tanchoco, J. M. A. (1986). Potentials for bi-directional guide-path for automated guid-ed vehicle-based systems. International Journal of Production Research, 24(5), 1075-1097.
Gaskins, R. J., & Tanchoco, J. M. (1987). Flow path design for automated guided vehicle sys-tems. International Journal of Production Research, 25(5), 667-676.
Giffler, B., & Thompson, G. L. (1960). Algorithms for solving production-scheduling problems. Opera-tions research, 8(4), 487-503.
Gnanavelbabu, A., Jerald, J., Noorul Haq, A., & Asokan, P. (2009). Multi-objective scheduling of jobs, AGVs and AS/RS in FMS using artificial immune system. In Proceedings of National Conference on Emerging trends in Engineering and Sciences (pp. 229-239).
Ho, Y. C., & Liu, H. C. (2009). The performance of load-selection rules and pickup-dispatching rules for multiple-load AGVs. Journal of Manufacturing Systems, 28(1), 1-10.
Haq, A. N., Karthikeyan, T., & Dinesh, M. (2003). Scheduling decisions in FMS using a heuristic ap-proach. The International Journal of Advanced Manufacturing Technology, 22(5-6), 374-379.
Huang, K. L., & Liao, C. J. (2008). Ant colony optimization combined with taboo search for the job shop scheduling problem. Computers & Operations Research, 35(4), 1030-1046.
Jahromi, M. H. M. A., Tavakkoli-Moghaddam, R., Makui, A., & Saghaei, A. (2017). A novel mathe-matical model for a scheduling problem of dynamic machine-tool selection and operation allocation in a flexible manufacturing system: A modified evolutionary algorithm. Scientia Iranica. Transaction E, Industrial Engineering, 24(2), 765.
Jain, V., & Raj, T. (2013). Evaluation of flexibility in FMS using SAW and WPM. Decision Science Letters, 2(4), 223-230.
Jerald, J., Asokan, P., Prabaharan, G., & Saravanan, R. (2005). Scheduling optimisation of flexible manufacturing systems using particle swarm optimisation algorithm. The International Journal of Ad-vanced Manufacturing Technology, 25(9), 964-971.
Kaban, A. K., Othman, Z., & Rohmah, D. S. (2012). Comparison of dispatching rules in job-shop scheduling problem using simulation: a case study. International Journal of Simulation Modelling, 11(3), 129-140
Kashan, A. H., & Karimi, B. (2009). A discrete particle swarm optimization algorithm for scheduling parallel machines. Computers & Industrial Engineering, 56(1), 216-223.
Kim, S. H., & Hwang, H. (1999). An adaptive dispatching algorithm for automated guided vehicles based on an evolutionary process. International Journal of Production Economics, 60, 465-472.
Lee, D. Y., & Di Cesare, F. (1994). Integrated scheduling of flexible manufacturing systems employing automated guided vehicles. IEEE Transactions on Industrial Electronics, 41(6), 602-610.
Mirjalili, S., Mirjalili, S. M., & Lewis, A. (2014). Grey wolf optimizer. Advances in Engineering Soft-ware, 69, 46-61.
Mirjalili, S., Saremi, S., Mirjalili, S. M., & Coelho, L. D. S. (2016). Multi-objective grey wolf optimizer: a novel algorithm for multi-criterion optimization. Expert Systems with Applications, 47, 106-119.
Moghaddam, B. F., Ruiz, R., & Sadjadi, S. J. (2012). Vehicle routing problem with uncertain demands: An advanced particle swarm algorithm. Computers & Industrial Engineering, 62(1), 306-317.
Prakash, A., Chan, F. T., & Deshmukh, S. G. (2011). FMS scheduling with knowledge based genetic algorithm approach. Expert Systems with Applications, 38(4), 3161-3171.
Rajotia, S., Shanker, K., & Batra, J. L. (1998). A semi-dynamic time window constrained routeing strategy in an AGV system. International Journal of Production Research, 36(1), 35-50.
Sabuncuoglu, I., & Hommertzheim, D. L. (1992). Dynamic dispatching algorithm for scheduling ma-chines and automated guided vehicles in a flexible manufacturing system. The International Journal of Production Research, 30(5), 1059-1079.
Sadjadi, S. J., & Makui, A. (2002). An algorithm to compute the complexity of a static production planning. International Journal of Engineering-Transactions A: Basics, 16(1), 57.
Sadrabadi, M. R., & Sadjadi, S. J. (2009). A new approach to solve multiple objective programming problems. International Journal of Industrial Engineering & Production Research, 20(1), 41-51.
Sen, K., Ghosh, S., & Sarkar, B. (2017). Comparison of Customer Preference for Bulk Material Han-dling Equipment through Fuzzy-AHP Approach. Journal of The Institution of Engineers (India): Se-ries C, 98(3), 367-377
Singh, R., & Khan, B. (2016). Meta-hierarchical-heuristic-mathematical-model of loading problems in flexible manufacturing system for development of an intelligent approach. International Journal of Industrial Engineering Computations, 7(2), 177-190.
Suleyman, K., & Ihsan, S. (1993). Beam search based algorithm for scheduling machines and AGVs in an FMS. In Proceedings of the Industrial Engineering Research Conference (pp. 308-312). Publ by IIE, Norcross, GA, United States
Taghaboni-Dutta, F., & Tanchoco, J. M. A. (1995). Comparison of dynamic routeing techniques for au-tomated guided vehicle system. International Journal of Production Research, 33(10), 2653-2669.
Tiwari, M., & Harding, J. A. (2011). Evolutionary computing in advanced manufacturing (Vol. 73). John Wiley & Sons.
Udhayakumar, P., & Kumanan, S. (2012). Integrated scheduling of flexible manufacturing system us-ing evolutionary algorithms. The International Journal of Advanced Manufacturing Technology, 61(5), 621-635.
Ulusoy, G., & Bilge, Ü. (1993). Simultaneous scheduling of machines and automated guided vehicles. The International Journal of Production Research, 31(12), 2857-2873.
Wang, Y. C., Chen, T., Chiang, H., & Pan, H. C. (2016). A simulation analysis of part launching and order collection decisions for a flexible manufacturing system. Simulation Modeling Practice and Theory, 69, 80-91.
Xia, W. J., & Wu, Z. M. (2006). A hybrid particle swarm optimization approach for the job-shop sched-uling problem. The International Journal of Advanced Manufacturing Technology, 29(3), 360-366.
Angra, S., Chanda, A., & Chawla, V. (2018). Comparison and evaluation of job selection dispatching rules for integrated scheduling of multi-load automatic guided vehicles serving in variable sized flex-ible manufacturing system layouts: A simulation study. Management Science Letters, 8(4), 187-200.
Bozorg-Haddad, O. (2017). Advanced Optimization by Nature-Inspired Algorithms.
Chawla, V., Chanda, A., Angra, S., & Chawla, G. (2018a). The sustainable project management: A re-view and future possibilities. Journal of Project Management, 3(3), 157-170.
Chawla, V.K., Chanda, A., & Angra, S. (2018b). A Clonal Selection Algorithm for Minimizing Dis-tance Travel & Back Tracking of Automatic Guided Vehicles in Flexible Manufacturing System. Journal of The Institution of Engineers (India): Series C, DOI: 10.1007/s40032-018-0447-5.
Chawla, V.K., Chanda, A., & Angra, S. (2018c). Scheduling of multi-load AGVs in FMS by modified memetic particle swarm optimization algorithm. Journal of Project Management, 3(1), 39-54.
Chawla, V.K., Chanda, A., & Angra, S. (2018d). Automatic guided vehicles fleet size optimization for flexible manufacturing system by grey wolf optimization algorithm. Management Science Letters, 8(2), 79-90.
Deb, K. (2001). Multi-objective optimization using evolutionary algorithms (Vol. 16). John Wiley & Sons.
Egbelu, P. J., & Tanchoco, J. M. A. (1986). Potentials for bi-directional guide-path for automated guid-ed vehicle-based systems. International Journal of Production Research, 24(5), 1075-1097.
Gaskins, R. J., & Tanchoco, J. M. (1987). Flow path design for automated guided vehicle sys-tems. International Journal of Production Research, 25(5), 667-676.
Giffler, B., & Thompson, G. L. (1960). Algorithms for solving production-scheduling problems. Opera-tions research, 8(4), 487-503.
Gnanavelbabu, A., Jerald, J., Noorul Haq, A., & Asokan, P. (2009). Multi-objective scheduling of jobs, AGVs and AS/RS in FMS using artificial immune system. In Proceedings of National Conference on Emerging trends in Engineering and Sciences (pp. 229-239).
Ho, Y. C., & Liu, H. C. (2009). The performance of load-selection rules and pickup-dispatching rules for multiple-load AGVs. Journal of Manufacturing Systems, 28(1), 1-10.
Haq, A. N., Karthikeyan, T., & Dinesh, M. (2003). Scheduling decisions in FMS using a heuristic ap-proach. The International Journal of Advanced Manufacturing Technology, 22(5-6), 374-379.
Huang, K. L., & Liao, C. J. (2008). Ant colony optimization combined with taboo search for the job shop scheduling problem. Computers & Operations Research, 35(4), 1030-1046.
Jahromi, M. H. M. A., Tavakkoli-Moghaddam, R., Makui, A., & Saghaei, A. (2017). A novel mathe-matical model for a scheduling problem of dynamic machine-tool selection and operation allocation in a flexible manufacturing system: A modified evolutionary algorithm. Scientia Iranica. Transaction E, Industrial Engineering, 24(2), 765.
Jain, V., & Raj, T. (2013). Evaluation of flexibility in FMS using SAW and WPM. Decision Science Letters, 2(4), 223-230.
Jerald, J., Asokan, P., Prabaharan, G., & Saravanan, R. (2005). Scheduling optimisation of flexible manufacturing systems using particle swarm optimisation algorithm. The International Journal of Ad-vanced Manufacturing Technology, 25(9), 964-971.
Kaban, A. K., Othman, Z., & Rohmah, D. S. (2012). Comparison of dispatching rules in job-shop scheduling problem using simulation: a case study. International Journal of Simulation Modelling, 11(3), 129-140
Kashan, A. H., & Karimi, B. (2009). A discrete particle swarm optimization algorithm for scheduling parallel machines. Computers & Industrial Engineering, 56(1), 216-223.
Kim, S. H., & Hwang, H. (1999). An adaptive dispatching algorithm for automated guided vehicles based on an evolutionary process. International Journal of Production Economics, 60, 465-472.
Lee, D. Y., & Di Cesare, F. (1994). Integrated scheduling of flexible manufacturing systems employing automated guided vehicles. IEEE Transactions on Industrial Electronics, 41(6), 602-610.
Mirjalili, S., Mirjalili, S. M., & Lewis, A. (2014). Grey wolf optimizer. Advances in Engineering Soft-ware, 69, 46-61.
Mirjalili, S., Saremi, S., Mirjalili, S. M., & Coelho, L. D. S. (2016). Multi-objective grey wolf optimizer: a novel algorithm for multi-criterion optimization. Expert Systems with Applications, 47, 106-119.
Moghaddam, B. F., Ruiz, R., & Sadjadi, S. J. (2012). Vehicle routing problem with uncertain demands: An advanced particle swarm algorithm. Computers & Industrial Engineering, 62(1), 306-317.
Prakash, A., Chan, F. T., & Deshmukh, S. G. (2011). FMS scheduling with knowledge based genetic algorithm approach. Expert Systems with Applications, 38(4), 3161-3171.
Rajotia, S., Shanker, K., & Batra, J. L. (1998). A semi-dynamic time window constrained routeing strategy in an AGV system. International Journal of Production Research, 36(1), 35-50.
Sabuncuoglu, I., & Hommertzheim, D. L. (1992). Dynamic dispatching algorithm for scheduling ma-chines and automated guided vehicles in a flexible manufacturing system. The International Journal of Production Research, 30(5), 1059-1079.
Sadjadi, S. J., & Makui, A. (2002). An algorithm to compute the complexity of a static production planning. International Journal of Engineering-Transactions A: Basics, 16(1), 57.
Sadrabadi, M. R., & Sadjadi, S. J. (2009). A new approach to solve multiple objective programming problems. International Journal of Industrial Engineering & Production Research, 20(1), 41-51.
Sen, K., Ghosh, S., & Sarkar, B. (2017). Comparison of Customer Preference for Bulk Material Han-dling Equipment through Fuzzy-AHP Approach. Journal of The Institution of Engineers (India): Se-ries C, 98(3), 367-377
Singh, R., & Khan, B. (2016). Meta-hierarchical-heuristic-mathematical-model of loading problems in flexible manufacturing system for development of an intelligent approach. International Journal of Industrial Engineering Computations, 7(2), 177-190.
Suleyman, K., & Ihsan, S. (1993). Beam search based algorithm for scheduling machines and AGVs in an FMS. In Proceedings of the Industrial Engineering Research Conference (pp. 308-312). Publ by IIE, Norcross, GA, United States
Taghaboni-Dutta, F., & Tanchoco, J. M. A. (1995). Comparison of dynamic routeing techniques for au-tomated guided vehicle system. International Journal of Production Research, 33(10), 2653-2669.
Tiwari, M., & Harding, J. A. (2011). Evolutionary computing in advanced manufacturing (Vol. 73). John Wiley & Sons.
Udhayakumar, P., & Kumanan, S. (2012). Integrated scheduling of flexible manufacturing system us-ing evolutionary algorithms. The International Journal of Advanced Manufacturing Technology, 61(5), 621-635.
Ulusoy, G., & Bilge, Ü. (1993). Simultaneous scheduling of machines and automated guided vehicles. The International Journal of Production Research, 31(12), 2857-2873.
Wang, Y. C., Chen, T., Chiang, H., & Pan, H. C. (2016). A simulation analysis of part launching and order collection decisions for a flexible manufacturing system. Simulation Modeling Practice and Theory, 69, 80-91.
Xia, W. J., & Wu, Z. M. (2006). A hybrid particle swarm optimization approach for the job-shop sched-uling problem. The International Journal of Advanced Manufacturing Technology, 29(3), 360-366.