An Effective Discrete Artificial Bee Colony Algorithm for Scheduling an Automatic-Guided-Vehicle in a Linear Manufacturing Workshop

This paper deals with a new automatic guided vehicle (AGV) scheduling problem from the material handling process in a linear manufacturing workshop. The problem is to determine a sequence of Cells for AGV to travel to minimize the standard deviation of the waiting time of the Cells and the total travel distance of AGV. For this purpose, we first propose an integer linear programming model based on a comprehensive investigation. Then, we present an improved nearest-neighbor-based heuristic so as to fast generate a good solution in view of the problem-specific characteristics. Next, we propose an effective discrete artificial bee colony algorithm with some novel and advanced techniques including a heuristic-based initialization, six neighborhood structures and a new evolution strategy in the onlooker bee phase. Finally, the proposed algorithms are empirically evaluated based on several typical instances from the real-world linear manufacturing workshop. A comprehensive and thorough experiment shows that the presented algorithm produces superior results which are also demonstrated to be statistically significant than the existing algorithms.

[1]  GenMitsuo,et al.  Recent advances in hybrid evolutionary algorithms for multiobjective manufacturing scheduling , 2017 .

[2]  Dervis Karaboga,et al.  A comprehensive survey: artificial bee colony (ABC) algorithm and applications , 2012, Artificial Intelligence Review.

[3]  Chengkuan Zeng,et al.  Scheduling of no buffer job shop cells with blocking constraints and automated guided vehicles , 2014, Appl. Soft Comput..

[4]  Jose M. Framiñan,et al.  Effective constructive heuristics and meta-heuristics for the distributed assembly permutation flowshop scheduling problem , 2019, Appl. Soft Comput..

[5]  Qishan Zhang,et al.  A Discrete Artificial Bee Colony Algorithm for the Reverse Logistics Location and Routing Problem , 2017, Int. J. Inf. Technol. Decis. Mak..

[6]  Hamed Fazlollahtabar,et al.  Methodologies to Optimize Automated Guided Vehicle Scheduling and Routing Problems: A Review Study , 2013, Journal of Intelligent & Robotic Systems.

[7]  Enrico Bartolini,et al.  A multi-start local search heuristic for the Green Vehicle Routing Problem based on a multigraph reformulation , 2019, Comput. Oper. Res..

[8]  Liang Gao,et al.  A multi-objective hot-rolling scheduling problem in the compact strip production , 2019, Applied Mathematical Modelling.

[9]  Mariagrazia Dotoli,et al.  A Survey on Petri Net Models for Freight Logistics and Transportation Systems , 2018, IEEE Transactions on Intelligent Transportation Systems.

[10]  Kris Braekers,et al.  The vehicle routing problem: State of the art classification and review , 2016, Comput. Ind. Eng..

[11]  Yosi Agustina Hidayat,et al.  A simulated annealing heuristic for the hybrid vehicle routing problem , 2017, Appl. Soft Comput..

[12]  Ganesan Poonthalir,et al.  A Fuel Efficient Green Vehicle Routing Problem with varying speed constraint (F-GVRP) , 2018, Expert Syst. Appl..

[13]  Yongbo Li,et al.  An improved ant colony optimization algorithm for the multi-depot green vehicle routing problem with multiple objectives , 2019, Journal of Cleaner Production.

[14]  Quan-Ke Pan,et al.  An effective co-evolutionary artificial bee colony algorithm for steelmaking-continuous casting scheduling , 2016, Eur. J. Oper. Res..

[15]  Amir Shafaei,et al.  Stochastic vehicle routing problem with heterogeneous vehicles and multiple prioritized time windows: Mathematical modeling and solution approach , 2019, Comput. Ind. Eng..

[16]  Ling Qiu,et al.  Scheduling and routing algorithms for AGVs: A survey , 2002 .

[17]  Lisa M. Jackson,et al.  Novel methodology for optimising the design, operation and maintenance of a multi-AGV system , 2018, Reliab. Eng. Syst. Saf..

[18]  Michel Gendreau,et al.  A Hybrid Genetic Algorithm for Multidepot and Periodic Vehicle Routing Problems , 2012, Oper. Res..

[19]  Juan Lin,et al.  Hybrid discrete artificial bee colony algorithm with threshold acceptance criterion for traveling salesman problem , 2017, Inf. Sci..

[20]  Houjun Lu,et al.  A study on multi-ASC scheduling method of automated container terminals based on graph theory , 2019, Comput. Ind. Eng..

[21]  Dervis Karaboga,et al.  A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm , 2007, J. Glob. Optim..

[22]  Quan-Ke Pan,et al.  An improved artificial bee colony algorithm for the blocking flowshop scheduling problem , 2012 .

[23]  Jun-Qing Li,et al.  An effective invasive weed optimization algorithm for scheduling semiconductor final testing problem , 2018, Swarm Evol. Comput..

[24]  Weifei Guo,et al.  Approach to Integrated Scheduling Problems Considering Optimal Number of Automated Guided Vehicles and Conflict-Free Routing in Flexible Manufacturing Systems , 2019, IEEE Access.

[25]  Jianyong Sun,et al.  A novel hybrid multi-objective artificial bee colony algorithm for blocking lot-streaming flow shop scheduling problems , 2018, Knowl. Based Syst..

[26]  Liang Gao,et al.  A new AGV scheduling algorithm based on harmony search for material transfer in a real-world manufacturing system , 2018 .

[27]  Mohammad Saidi-Mehrabad,et al.  An Ant Colony Algorithm (ACA) for solving the new integrated model of job shop scheduling and conflict-free routing of AGVs , 2015, Comput. Ind. Eng..

[28]  Puca Huachi Vaz Penna,et al.  An Iterated Local Search heuristic for the Heterogeneous Fleet Vehicle Routing Problem , 2013, J. Heuristics.

[29]  Liang Gao,et al.  Tasks assigning and sequencing of multiple AGVs based on an improved harmony search algorithm , 2019, J. Ambient Intell. Humaniz. Comput..

[30]  Toshiyuki Miyamoto,et al.  Local and random searches for dispatch and conflict-free routing problem of capacitated AGV systems , 2016, Comput. Ind. Eng..

[31]  D. Karaboga,et al.  On the performance of artificial bee colony (ABC) algorithm , 2008, Appl. Soft Comput..

[32]  Hamed Fazlollahtabar,et al.  Mathematical optimization for earliness/tardiness minimization in a multiple automated guided vehicle manufacturing system via integrated heuristic algorithms , 2015, Robotics Auton. Syst..

[33]  Jean-François Cordeau,et al.  A parallel iterated tabu search heuristic for vehicle routing problems , 2012, Comput. Oper. Res..

[34]  R. Tavakkoli-Moghaddam,et al.  A hybrid simulated annealing for capacitated vehicle routing problems with the independent route length , 2006, Appl. Math. Comput..

[35]  Hwa Jen Yap,et al.  Multi-objective AGV scheduling in an FMS using a hybrid of genetic algorithm and particle swarm optimization , 2017, PloS one.

[36]  Quan-Ke Pan,et al.  Pareto-based discrete artificial bee colony algorithm for multi-objective flexible job shop scheduling problems , 2011 .

[37]  Ashish Bhaskar,et al.  A self-adaptive evolutionary algorithm for dynamic vehicle routing problems with traffic congestion , 2019, Swarm Evol. Comput..

[38]  Zdenko Kovacic,et al.  Decentralized Control of Multi-AGV Systems in Autonomous Warehousing Applications , 2016, IEEE Transactions on Automation Science and Engineering.

[39]  Nubia Velasco,et al.  A multi-population algorithm to solve the VRP with stochastic service and travel times , 2018, Comput. Ind. Eng..

[40]  Xinyu Li,et al.  A Three-Stage Multiobjective Approach Based on Decomposition for an Energy-Efficient Hybrid Flow Shop Scheduling Problem , 2020, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[41]  Jingjing Li,et al.  An Improved Particle Swarm Optimization Algorithm for Integrated Scheduling Model in AGV-Served Manufacturing Systems , 2018, Journal of Advanced Manufacturing Systems.

[42]  José Brandão,et al.  Iterated local search algorithm with ejection chains for the open vehicle routing problem with time windows , 2018, Comput. Ind. Eng..

[43]  Mehmet Fatih Tasgetiren,et al.  A discrete artificial bee colony algorithm for the lot-streaming flow shop scheduling problem , 2011, Inf. Sci..

[44]  Nurhan Karaboga,et al.  A new design method based on artificial bee colony algorithm for digital IIR filters , 2009, J. Frankl. Inst..

[45]  Iris F. A. Vis,et al.  Survey of research in the design and control of automated guided vehicle systems , 2006, Eur. J. Oper. Res..

[46]  Wenqiang Zhang,et al.  Recent advances in hybrid evolutionary algorithms for multiobjective manufacturing scheduling , 2017, Comput. Ind. Eng..

[47]  Chen Chen,et al.  Using a genetic algorithm to schedule the space-constrained AGV-based prefabricated bathroom units manufacturing system , 2018, International Journal of Production Research.

[48]  C. L. Wang,et al.  Hybrid fruit fly optimization algorithm for solving multi-compartment vehicle routing problem in intelligent logistics , 2018, Advances in Production Engineering & Management.

[49]  Yongsheng Yang,et al.  An integrated scheduling method for AGV routing in automated container terminals , 2018, Comput. Ind. Eng..

[50]  Ying Tan,et al.  Improving Metaheuristic Algorithms With Information Feedback Models , 2019, IEEE Transactions on Cybernetics.