A Mathematical Model for Multiple-Load AGVs in Tandem Layout
Subject Areas : StrategyBehnam Rahimikelarijani 1 , Mohammad Saidi-Mehrabad 2 , Farnaz Barzinpour 3
1 - Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran
2 - Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran
3 - Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran
Keywords: Variable neighborhood search, AGV, Tandem, Multiple-load, Machine-to-loop assignment,
Abstract :
Reducing cost of material handling has been a big challenge for companies. Flexible manufacturing system employed automated guided vehicles (AGV) to maintain efficiency and flexibility. This paper presents a new non-linear mathematical programming model to group n machines into N loops, to make an efficient configuration for AGV system in Tandem layout. The model minimizes both inter-loop, intra-loop flow and use balanced-loops strategy to balance workload in system simultaneously. This paper significantly considers multiple-load AGVs, which has capability of reducing fleet size and waiting time of works. A modified variable neighborhood search method is applied for large size problems, which has good accuracy for small and medium size problems. The results indicate that using multiple load AGV instead of single load AGV will reduce system penalty cost up to 44%.
Aarab, A., Chetto, H. and Radouane, L. (1999) ‘Flow path design for AGV systems’, Studies in Informatics and Control, 8, pp. 97–106.
Bozer, Y. A. and Srinivasan, M. M. (1989) ‘Tandem configurations for AGV systems offer simplicity and flexibility’, Industrial Engineering. American Institute of Industrial Engineers, 21(2), pp. 23–27.
Bozer, Y. A. and Srinivasan, M. M. (1992) ‘Tandem AGV systems: a partitioning algorithm and performance comparison with conventional AGV systems’, European Journal of Operational Research. Elsevier, 63(2), pp. 173–191.
Carlo, H. J., Vis, I. F. A. and Roodbergen, K. J. (2014) ‘Transport operations in container terminals: Literature overview, trends, research directions and classification scheme’, European Journal of Operational Research, 236(1), pp. 1–13. doi: 10.1016/j.ejor.2013.11.023.
Choobineh, F. F., Asef-Vaziri, A. and Huang, X. (2012) ‘Fleet sizing of automated guided vehicles: a linear programming approach based on closed queuing networks’, International Journal of Production Research, 50(12), pp. 3222–3235.
Christofides, N., Mingozzi, A. and Toth, P. (1980) ‘Contributions to the quadratic assignment problem’, European Journal of Operational Research, 4(4), pp. 243–247. doi: http://dx.doi.org/10.1016/0377-2217(80)90108-3.
Das, S. K. and Pasan, M. K. (2016) ‘Design and Methodology of Automated Guided Vehicle-A Review’, IOSR Journal of Mechanical and Civil Engineering (IOSR-JMCE), pp. 29–35.
ElMekkawy, T. Y. and Liu, S. (2009) ‘A new memetic algorithm for optimizing the partitioning problem of tandem AGV systems’, International Journal of Production Economics, 118(2), pp. 508–520.
Fan, X., He, Q. and Zhang, Y. (2015) ‘Zone Design of Tandem Loop AGVs Path with Hybrid Algorithm’, IFAC-PapersOnLine. Elsevier, 48(3), pp. 869–874.
Fazlollahtabar, H. and Saidi-Mehrabad, M. (2015) ‘Methodologies to Optimize Automated Guided Vehicle Scheduling and Routing Problems: A Review Study’, Journal of Intelligent & Robotic Systems, 77(3–4), pp. 525–545. doi: 10.1007/s10846-013-0003-8.
Fazlollahtabar, H., Saidi-mehrabad, M. and Balakrishnan, J. (2015) ‘Mathematical optimization for earliness / tardiness minimization in a multiple automated guided vehicle manufacturing system via integrated heuristic algorithms’, Robotics and Autonomous Systems, 72, pp. 131–138. doi: 10.1016/j.robot.2015.05.002.
Fazlollahtabar, H. and Saidi—Mehrabad, M. (2015) ‘Risk assessment for multiple automated guided vehicle manufacturing network’, Robotics and Autonomous Systems. Elsevier B.V., 74(December 2016), pp. 175–183. doi: 10.1016/j.robot.2015.07.013.
Gilmore, P. C. (1962) ‘Optimal and suboptimal algorithms for the quadratic assignment problem’, Journal of the Society for Industrial & Applied Mathematics. SIAM, 10(2), pp. 305–313.
Gutta, P. R. et al. (2018) ‘A Review On Facility Layout Design Of An Automated Guided Vehicle In Flexible Manufacturing System’, Materials Today: Proceedings. Elsevier, 5(2), pp. 3981–3986.
Hansen, P. and Mladenovi, N. (2001) ‘Variable neighborhood search : Principles and applications’, 130.
Ho, Y.-C., Liu, H.-C. and Yih, Y. (2012) ‘A multiple-attribute method for concurrently solving the pickup-dispatching problem and the load-selection problem of multiple-load AGVs’, Journal of manufacturing systems, 31(3), pp. 288–300. doi: http://dx.doi.org/10.1016/j.jmsy.2012.03.002.
Ho *, Y.-C. and Hsieh, P.-F. (2004) ‘A machine-to-loop assignment and layout design methodology for tandem AGV systems with multiple-load vehicles’, International Journal of Production Research. Taylor & Francis, 42(4), pp. 801–832. doi: 10.1080/00207540310001602874.
Kim, K., Chung, B. and Jae, M. (2003) ‘A design for a tandem AGVS with multi-load AGVs’, The International Journal of Advanced Manufacturing Technology, 22(9), pp. 744–752.
Kim, K. S. and Chung, B. Do (2007) ‘Design for a tandem AGV system with two-load AGVs’, Computers & Industrial Engineering, 53(2), pp. 247–251.
Kumar, R. et al. (2015) ‘Automated guided vehicle configurations in flexible manufacturing systems: a comparative study’, International Journal of Industrial and Systems Engineering. Inderscience Publishers (IEL), 21(2), pp. 207–226.
Liu, Z. et al. (2018) ‘A co-evolutionary design methodology for complex AGV system’, Neural Computing and Applications. Springer, 29(4), pp. 959–974.
Meer, J. R. van der (2000) Operational control of internal transport. Erasmus University Rotterdam.
MS.Bazaraa, H. S. (1993) Nonlinear programming. Second edn. Wiley, NY.
Ozden, M. (1988) ‘A simulation study of multiple-load-carrying automated guided vehicles in a flexible manufacturing system’, The International Journal Of Production Research. Taylor & Francis, 26(8), pp. 1353–1366.
R.Tavakkoli-Moghaddam H.Kazemipoor, A.Salehipour, M. B. A. (2008) ‘Partitioning machines in tandem AGV systems based on “balanced flow strategy” by simulated annealing’, The International Journal of Advanced Manufacturing Technology. Springer-Verlag, 38(3–4), pp. 355–366. doi: 10.1007/s00170-007-1094-9.
Rezapour, S., Zanjirani-Farahani, R. and Miandoabchi, E. (2010) ‘A machine-to-loop assignment and layout design methodology for tandem AGV systems with single-load vehicles’, International Journal of Production Research. Taylor & Francis, 49(12), pp. 3605–3633. doi: 10.1080/00207543.2010.489056.
Salehipour, A., Kazemipoor, H. and Moslemi Naeini, L. (2011) ‘Locating workstations in tandem automated guided vehicle systems’, The International Journal of Advanced Manufacturing Technology, 52(1), pp. 321–328.
Shalaby, M. A., El Mekkawy, T. Y. and Fahmy, S. A. (2006) ‘Zones formation algorithm in tandem AGV systems: a comparative study’, International Journal of Production Research, 44(3), pp. 505–521.
Talbi, E.-G. (2009) Metaheuristics: from design to implementation. John Wiley & Sons.
Vis, I. F. A. (2006) ‘Survey of research in the design and control of automated guided vehicle systems’, 170, pp. 677–709. doi: 10.1016/j.ejor.2004.09.020.
Yu, W. and Egbelu, P. J. (2001) ‘Design of a variable path tandem layout for automated guided vehicle systems’, Journal of manufacturing systems, 20(5), pp. 305–319.
Zanjirani Farahani, R. et al. (2008) ‘Designing efficient methods for the tandem AGV network design problem using tabu search and genetic algorithm’, The International Journal of Advanced Manufacturing Technology, 36(9), pp. 996–1009.