A three-layer chromosome genetic algorithm for multi-cell scheduling with flexible routes and machine sharing

Abstract Alternative machines assignment, machine sharing, and inter-cell movements are very common yet difficult to be solved integratedly in modern dynamic Cellular Manufacturing Systems (CMS). In this paper, we incorporate these issues and consider a dynamic cellular scheduling problem with flexible routes and machine sharing. We employ a mixed integer programming scheduling model to minimize both the makespan and the total workload. To solve this new model, we propose a three-layer chromosome genetic algorithm (TCGA). We first compare the performances of the proposed TCGA with the optimal solution obtained by CPLEX. Computational results show that the TCGA performs well within a reasonable amount of time. We further compare our proposed TCGA with the classic genetic algorithm (GA) and the shortest processing time (SPT) rule through numerical experiments. The results reveal that the TCGA significantly improves the performance and effectively balances the workload of machines.

[1]  Hong-Sen Yan,et al.  Integrated production planning and scheduling for a mixed batch job-shop based on alternant iterative genetic algorithm , 2015, J. Oper. Res. Soc..

[2]  Jiadong Yang,et al.  A hybrid harmony search algorithm for the flexible job shop scheduling problem , 2013, Appl. Soft Comput..

[3]  Xiaohang Yue,et al.  A Novel Hybrid Ant Colony Optimization Algorithm for Emergency Transportation Problems During Post-Disaster Scenarios , 2018, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[4]  Zhi-ming Wu,et al.  A genetic algorithm for manufacturing cell formation with multiple routes and multiple objectives , 2000 .

[5]  Sebastián Lozano,et al.  Cell design and multi-period machine loading in cellular reconfigurable manufacturing systems with alternative routing , 2017, Int. J. Prod. Res..

[6]  Kripa Shanker,et al.  Grouping of parts and machines in presence of alternative process routes by genetic algorithm , 2002 .

[7]  Chengkuan Zeng,et al.  Using Lagrangian Relaxation Decomposition With Heuristic to Integrate the Decisions of Cell Formation and Parts Scheduling Considering Intercell Moves , 2014, IEEE Transactions on Automation Science and Engineering.

[8]  Eugene L. Lawler,et al.  Sequencing and scheduling: algorithms and complexity , 1989 .

[9]  Mauricio G. C. Resende,et al.  A biased random-key genetic algorithm for the unequal area facility layout problem , 2015, Eur. J. Oper. Res..

[10]  Joseph Y.-T. Leung,et al.  Solving cell formation and task scheduling in cellular manufacturing system by discrete bacteria foraging algorithm , 2016 .

[11]  Antonio Costa,et al.  A hybrid genetic algorithm for minimizing makespan in a flow-shop sequence-dependent group scheduling problem , 2015, Journal of Intelligent Manufacturing.

[12]  Reza Bashirzadeh,et al.  Concurrent scheduling of manufacturing cells considering sequence-dependent family setup times and intercellular transportation times , 2015 .

[13]  Mohd Khairol Anuar Mohd Ariffin,et al.  A multi-period scheduling method for trading-off between skilled-workers allocation and outsource service usage in dynamic CMS , 2017, Int. J. Prod. Res..

[14]  Wing-Keung Wong,et al.  A genetic-algorithm-based optimization model for scheduling flexible assembly lines , 2008 .

[15]  Manoj Kumar Tiwari,et al.  A methodology to design virtual cellular manufacturing systems , 2011, J. Intell. Manuf..

[16]  Maghsud Solimanpur,et al.  A heuristic to minimize makespan of cell scheduling problem , 2004 .

[17]  Hossein Nouri,et al.  Development of a comprehensive model and BFO algorithm for a dynamic cellular manufacturing system , 2016 .

[18]  Henry Y. K. Lau,et al.  An AIS-based hybrid algorithm with PDRs for multi-objective dynamic online job shop scheduling problem , 2013, Appl. Soft Comput..

[19]  Vahit Kaplanoglu,et al.  An object-oriented approach for multi-objective flexible job-shop scheduling problem , 2016, Expert Syst. Appl..

[20]  Kalyanmoy Deb,et al.  Improving differential evolution through a unified approach , 2013, J. Glob. Optim..

[21]  Maghsud Solimanpur,et al.  A tabu search approach for cell scheduling problem with makespan criterion , 2013 .

[22]  Fawaz S. Al-Anzi,et al.  Using mixed graph coloring to minimize total completion time in job shop scheduling , 2006, Appl. Math. Comput..

[23]  Stefan Helber,et al.  A hierarchical facility layout planning approach for large and complex hospitals , 2014 .

[24]  Patrick McDonnell,et al.  An approach to regulating machine sharing in reconfigurable back-end semiconductor manufacturing , 2004, J. Intell. Manuf..

[25]  Tangbin Xia,et al.  Concurrent design of cell formation and scheduling with consideration of duplicate machines and alternative process routings , 2019, J. Intell. Manuf..

[26]  Mohd Khairol Anuar Mohd Ariffin,et al.  Review on Dynamic Cellular Manufacturing System , 2014 .

[27]  Andrea Rossi,et al.  Flexible job shop scheduling with sequence-dependent setup and transportation times by ant colony with reinforced pheromone relationships , 2014 .

[28]  Suresh P. Sethi,et al.  Parallel-machine scheduling with machine-dependent maintenance periodic recycles , 2017 .

[29]  Muhammad Imran,et al.  Cell formation in a cellular manufacturing system using simulation integrated hybrid genetic algorithm , 2017, Comput. Ind. Eng..

[30]  Manojit Chattopadhyay,et al.  Neuro-genetic impact on cell formation methods of Cellular Manufacturing System design: A quantitative review and analysis , 2013, Comput. Ind. Eng..

[31]  Chengkuan Zeng,et al.  Auction-based cooperation mechanism to parts scheduling for flexible job shop with inter-cells , 2016, Appl. Soft Comput..

[32]  Yan Wang,et al.  Dynamic parts scheduling in multiple job shop cells considering intercell moves and flexible routes , 2013, Comput. Oper. Res..

[33]  Thierry Moyaux,et al.  A bi-objective model in sustainable dynamic cell formation problem with skill-based worker assignment , 2016 .

[34]  Youkyung Won,et al.  Effective two-phase p-median approach for the balanced cell formation in the design of cellular manufacturing system , 2015 .

[35]  Sanja Petrovic,et al.  A multi-objective genetic algorithm for optimisation of energy consumption and shop floor production performance , 2016 .

[36]  Ahad Ali,et al.  A multi-period scheduling of dynamic cellular manufacturing systems in the presence of cost uncertainty , 2016, Comput. Ind. Eng..

[37]  Yazhi Li,et al.  Solving the multi-objective flowline manufacturing cell scheduling problem by hybrid harmony search , 2015, Expert Syst. Appl..

[38]  Christian Bierwirth,et al.  A study on local search neighborhoods for the job shop scheduling problem with total weighted tardiness objective , 2016, Comput. Oper. Res..

[39]  Uday Venkatadri,et al.  A framework for multi-objective facility layout design , 2015, Comput. Ind. Eng..

[40]  Nancy Lea Hyer,et al.  Cellular manufacturing in the U.S. industry: a survey of users , 1989 .

[41]  Adam Lipowski,et al.  Roulette-wheel selection via stochastic acceptance , 2011, ArXiv.