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A parallel algorithm for multi-AGV systems

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Abstract

Automated guided vehicles are widely used in various applications, especially in manufacturing. In this paper, we present a novel parallel algorithm for multi-AGV systems. The overall structure is composed of three parts: task assignment, path planning, and vehicle navigation. According to the priorities of AGVs, a greedy method is introduced to assign jobs. For path planning, a mixed-integer programming model of a multi-AGV system is formulated, which can be transformed into a series of sub-problems under certain conditions. Then, an improved routing method with a penalty item is adopted to generate the optimal paths of AGVs. To avoid collisions between vehicles, a simple and effective control method based on resource locking is proposed under the premise of parallelization. Furthermore, we design the experiments according to the warehousing systems. Various practical simulations are performed to illustrate the efficiency and robustness of the new algorithm.

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References

  • Ammar A, Bennaceur H, Châari I, Koubâa A, Alajlan M (2016) Relaxed dijkstra and a with linear complexity for robot path planning problems in large-scale grid environments. Soft Comput 20(10):4149–4171

    Article  Google Scholar 

  • Arslan O, Karaşan OE (2016) A benders decomposition approach for the charging station location problem with plug-in hybrid electric vehicles. Transp Res Part B 93:670–695

    Article  Google Scholar 

  • Beasley JE, Christofides N (1997) Vehicle routing with a sparse feasibility graph. Eur J Oper Res 98(3):499–511

    Article  Google Scholar 

  • Bobanac V, Bogdan S (2008) Routing and scheduling in multi-agv systems based on dynamic banker algorithm. In: 2008 16th Mediterranean conference on control and automation, pp 1168–1173

  • Brandstätter G, Kahr M, Leitner M (2017) Determining optimal locations for charging stations of electric car-sharing systems under stochastic demand. Transp Res Part B 104:17–35

    Article  Google Scholar 

  • Cao X, Chen J, Xiao Y, Sun Y (2010) Building-environment control with wireless sensor and actuator networks: Centralized versus distributed. IEEE Trans Ind Electron 57(11):3596–3605

    Article  Google Scholar 

  • Casal G, Santamarina D, Vázquez-Méndez ME (2017) Optimization of horizontal alignment geometry in road design and reconstruction. Transp Res Part C 74:261–274

    Article  Google Scholar 

  • Davey N, Dunstall S, Halgamuge S (2017) Optimal road design through ecologically sensitive areas considering animal migration dynamics. Transp Res Part C 77:478–494

    Article  Google Scholar 

  • Demesure G, Defoort M, Bekrar A, Trentesaux D, Djemai M (2018) Decentralized motion planning and scheduling of agvs in an fms. IEEE Trans Ind Inform 14(4):1744–1752

    Article  Google Scholar 

  • Digani V, Sabattini L, Secchi C, Fantuzzi C (2014) Hierarchical traffic control for partially decentralized coordination of multi agv systems in industrial environments. In: 2014 IEEE international conference on robotics and automation (ICRA), pp 6144–6149

  • Draganjac I, Miklic D, Kovacic Z, Vasiljevic G, Bogdan S (2016) Decentralized control of multi-agv systems in autonomous warehousing applications. IEEE Trans Autom Sci Eng 13(4):1433–1447

    Article  Google Scholar 

  • Erol R, Sahin C, Baykasoglu A, Kaplanoglu V (2012) A multi-agent based approach to dynamic scheduling of machines and automated guided vehicles in manufacturing systems. Appl Soft Comput 12(6):1720–1732

    Article  Google Scholar 

  • Guzman MCD, Prabhu N, Tanchoco JA (1997) Complexity of the agv shortest path and single-loop guide path layout problems. Int J Prod Res 35(8):2083–2092

    Article  Google Scholar 

  • Hart PE, Nilsson NJ, Raphael B (1968) A formal basis for the heuristic determination of minimum cost paths. IEEE Trans Syst Sci Cybern SSC 4(2):100–107

    Article  Google Scholar 

  • He F, Yin Y, Zhou J (2015) Deploying public charging stations for electric vehicles on urban road networks. Transp Res Part C 60:227–240

    Article  Google Scholar 

  • Hirpa D, Hare W, Lucet Y, Pushak Y, Tesfamariam S (2016) A bi-objective optimization framework for three-dimensional road alignment design. Transp Res Part C 65:61–78

    Article  Google Scholar 

  • Ho YC (2000) A dynamic-zone strategy for vehicle-collision prevention and load balancing in an agv system with a single-loop guide path. Comput Ind 42(2):159–176

    Article  Google Scholar 

  • Ho YC, Liao TW (2009) Zone design and control for vehicle collision prevention and load balancing in a zone control agv system. Comput Ind Eng 56(1):417–432

    Article  Google Scholar 

  • Kabir QS, Suzuki Y (2018) Increasing manufacturing flexibility through battery management of automated guided vehicles. Comput Ind Eng 117:225–236

    Article  Google Scholar 

  • Kehoe B, Patil S, Abbeel P, Goldberg K (2015) A survey of research on cloud robotics and automation. IEEE Trans Autom Sci Eng 12(2):398–409

    Article  Google Scholar 

  • Lacomme P, Larabi M, Tchernev N (2013) Job-shop based framework for simultaneous scheduling of machines and automated guided vehicles. Int J Prod Econ 143(1):24–34

    Article  Google Scholar 

  • Laporte G, Ortega FA, Pozo MA, Puerto J (2017) Multi-objective integration of timetables, vehicle schedules and user routings in a transit network. Transp Res Part B 98:94–112

    Article  Google Scholar 

  • Le-Anh T, De Koster MBM (2006) A review of design and control of automated guided vehicle systems. Eur J Oper Res 171(1):1–23

    Article  MathSciNet  Google Scholar 

  • Lu S, Xu C, Zhong RY, Wang L (2017) A rfid-enabled positioning system in automated guided vehicle for smart factories. J Manuf Syst 44:179–190

    Article  Google Scholar 

  • Małopolski W (2018) A sustainable and conflict-free operation of agvs in a square topology. Comput Ind Eng 126:472–481

    Article  Google Scholar 

  • Martínez-Barberá H, Herrero-Pérez D (2010) Autonomous navigation of an automated guided vehicle in industrial environments. Robot Comput Integr Manuf 26(4):296–311

    Article  Google Scholar 

  • Nishi T, Hiranaka Y, Grossmann IE (2011) A bilevel decomposition algorithm for simultaneous production scheduling and conflict-free routing for automated guided vehicles. Comput Oper Res 38(5):876–888

    Article  MathSciNet  Google Scholar 

  • Olmi R, Secchi C, Fantuzzi C (2011) An efficient control strategy for the traffic coordination of agvs. In: 2011 IEEE/RSJ international conference on intelligent robots and systems, pp 4615–4620

  • Rashidi H, Tsang EPK (2011) A complete and an incomplete algorithm for automated guided vehicle scheduling in container terminals. Comput Math Appl 61(3):630–641

    Article  MathSciNet  Google Scholar 

  • Reddy BSP, Rao CSP (2006) A hybrid multi-objective ga for simultaneous scheduling of machines and agvs in fms. Int J Adv Manuf Technol 31(5):602–613

    Article  Google Scholar 

  • Roy D, Krishnamurthy A, Heragu S, Malmborg C (2015) Queuing models to analyze dwell-point and cross-aisle location in autonomous vehicle-based warehouse systems. Eur J Oper Res 242(1):72–87

    Article  Google Scholar 

  • Saidi-Mehrabad M, Dehnavi-Arani S, Evazabadian F, Mahmoodian V (2015) An ant colony algorithm (aca) for solving the new integrated model of job shop scheduling and conflict-free routing of agvs. Comput Ind Eng 86:2–13

    Article  Google Scholar 

  • Secchi C, Olmi R, Fantuzzi C, Casarini M (2014) Trafcon—traffic control of agvs in automatic warehouses. Gearing up and accelerating cross-fertilization between academic and industrial robotics research in Europe. Springer, Berlin, pp 85–105

    Google Scholar 

  • Sedeñ-noda A, Colebrook M (2019) A biobjective dijkstra algorithm. Eur J Oper Res 276(1):106–118

    Article  MathSciNet  Google Scholar 

  • Smolic-Rocak N, Bogdan S, Kovacic Z, Petrovic T (2010) Time windows based dynamic routing in multi-agv systems. IEEE Trans Autom Sci Eng 7(1):151–155

    Article  Google Scholar 

  • Umar UA, Ariffin MKA, Ismail N, Tang SH (2015) Hybrid multiobjective genetic algorithms for integrated dynamic scheduling and routing of jobs and automated-guided vehicle (agv) in flexible manufacturing systems (fms) environment. Int J Adv Manuf Technol 81(9):2123–2141

    Article  Google Scholar 

  • Vis IFA (2006) Survey of research in the design and control of automated guided vehicle systems. Eur J Oper Res 170(3):677–709

    Article  MathSciNet  Google Scholar 

  • Yang Y, Zhong M, Dessouky Y, Postolache O (2018) An integrated scheduling method for agv routing in automated container terminals. Comput Ind Eng 126:482–493

    Article  Google Scholar 

  • Yan R, Jackson LM, Dunnett SJ (2017) Automated guided vehicle mission reliability modelling using a combined fault tree and petri net approach. Int J Adv Manuf Technol 92(5):1825–1837

    Article  Google Scholar 

  • Yıldız B, Olcaytu E, Şen A (2019) The urban recharging infrastructure design problem with stochastic demands and capacitated charging stations. Transp Res Part B 119:22–44

    Article  Google Scholar 

  • Zhang Y, Zhu Z, Lv J (2018) Cps-based smart control model for shopfloor material handling. IEEE Trans Ind Inform 14(4):1764–1775

    Article  Google Scholar 

Download references

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Correspondence to Kewei Liang.

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Yu, D., Hu, X., Liang, K. et al. A parallel algorithm for multi-AGV systems. J Ambient Intell Human Comput 13, 2309–2323 (2022). https://doi.org/10.1007/s12652-021-02987-3

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