Balancing Problem of Stochastic Large-Scale U-Type Assembly Lines Using a Modified Evolutionary Algorithm

U-type assembly lines have become a mainstream mode in manufacturing because of the higher flexibility and productivity compared with straight lines. Since the balancing problem of a large-scale U-type assembly line is known to be NP-hard, effective mathematical model and evolutionary algorithm are needed to solve this problem. This paper reviews the research status of the related literature in recent years and presents a hybrid evolutionary algorithm, namely, modified ant colony optimization inspired by the process of simulated annealing, to reduce the possibility of being trapped in a local optimum for the balancing problem of stochastic large-scale U-type assembly line. A modified mathematical model for this balancing problem considering stochastic properties is formulated. Furthermore, comparisons with genetic algorithm and imperialist competitive algorithm are conducted to evaluate this proposed method. The results indicate that this proposed algorithm outperforms prior methods in this balancing problem.

[1]  Uğur Özcan,et al.  A genetic algorithm for the stochastic mixed-model U-line balancing and sequencing problem , 2011 .

[2]  J. Mukund Nilakantan,et al.  Robotic U-shaped assembly line balancing using particle swarm optimization , 2016 .

[3]  P. Sivasankaran,et al.  Literature review of assembly line balancing problems , 2014 .

[4]  Mohammad Hossein Fazel Zarandi,et al.  Modified genetic algorithm for simple straight and U-shaped assembly line balancing with fuzzy processing times , 2017, J. Intell. Manuf..

[5]  Huiyuan Xiong,et al.  Energy Recovery Strategy Numerical Simulation for Dual Axle Drive Pure Electric Vehicle Based on Motor Loss Model and Big Data Calculation , 2018, Complex..

[6]  Javad Sattarvand,et al.  Long term production planning of open pit mines by ant colony optimization , 2015, Eur. J. Oper. Res..

[7]  윤태혁,et al.  (The) U-line line balancing problem with the moving time of operator = U자형 라인에서 작업자 이동시간을 고려한 라인밸런싱에 관한 연구 , 1996 .

[8]  Liping Zhang,et al.  Minimizing energy consumption and cycle time in two-sided robotic assembly line systems using restarted simulated annealing algorithm , 2016 .

[9]  Murat Sahin,et al.  An efficient grouping genetic algorithm for U-shaped assembly line balancing problems with maximizing production rate , 2017, Memetic Comput..

[10]  Robert L. Carraway,et al.  A dynamic programming approach to stochastic assembly line balancing , 1989 .

[11]  Tianyuan Xiao,et al.  Balancing and sequencing of stochastic mixed-model assembly U-lines to minimise the expectation of work overload time , 2014 .

[12]  Swagatam Das,et al.  Ant colony optimization based enhanced dynamic source routing algorithm for mobile Ad-hoc network , 2015, Inf. Sci..

[13]  Adil Baykasoglu,et al.  Multi-rule Multi-objective Simulated Annealing Algorithm for Straight and U Type Assembly Line Balancing Problems , 2006, J. Intell. Manuf..

[14]  Yan Wang,et al.  A hybrid approach of rough set and case-based reasoning to remanufacturing process planning , 2016, Journal of Intelligent Manufacturing.

[15]  James C. Chen,et al.  Hybrid genetic algorithm to solve resource constrained assembly line balancing problem in footwear manufacturing , 2017, Soft Comput..

[16]  Bilal Toklu,et al.  Balancing of mixed-model two-sided assembly lines , 2009, Comput. Ind. Eng..

[17]  Armin Scholl,et al.  Data of assembly line balancing problems , 1995 .

[18]  MengChu Zhou,et al.  Target Disassembly Sequencing and Scheme Evaluation for CNC Machine Tools Using Improved Multiobjective Ant Colony Algorithm and Fuzzy Integral , 2019, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[19]  Ibrahim Kucukkoc,et al.  New MILP model and station-oriented ant colony optimization algorithm for balancing U-type assembly lines , 2017, Comput. Ind. Eng..

[20]  Zhiwu Li,et al.  Operation patterns analysis of automotive components remanufacturing industry development in China , 2017 .

[21]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[22]  Joaquín Bautista,et al.  Ant algorithms for a time and space constrained assembly line balancing problem , 2007, Eur. J. Oper. Res..

[23]  Ihsan Sabuncuoglu,et al.  Ant colony optimization for the single model U-type assembly line balancing problem , 2009 .

[24]  Feng Xia,et al.  Mobility Dataset Generation for Vehicular Social Networks Based on Floating Car Data , 2018, IEEE Transactions on Vehicular Technology.

[25]  M. H. Alavidoost,et al.  An interactive fuzzy programming approach for bi-objective straight and U-shaped assembly line balancing problem , 2016, Appl. Soft Comput..

[26]  Parviz Fattahi,et al.  A mathematical model and ant colony algorithm for multi-manned assembly line balancing problem , 2011 .

[27]  Mostafa Zandieh,et al.  Balancing of stochastic U-type assembly lines: an imperialist competitive algorithm , 2011 .

[28]  Feng Xia,et al.  LoTAD: long-term traffic anomaly detection based on crowdsourced bus trajectory data , 2017, World Wide Web.

[29]  Xiaojuan Sun,et al.  Primary resonance analysis and vibration suppression for the harmonically excited nonlinear suspension system using a pair of symmetric viscoelastic buffers , 2018, Nonlinear Dynamics.

[30]  Chaoyong Zhang,et al.  Balancing stochastic two-sided assembly line with multiple constraints using hybrid teaching-learning-based optimization algorithm , 2017, Comput. Oper. Res..

[31]  MengChu Zhou,et al.  Disassembly Sequence Planning Considering Fuzzy Component Quality and Varying Operational Cost , 2018, IEEE Transactions on Automation Science and Engineering.

[32]  Venkatesh Jonnalagedda,et al.  Application of Simple Genetic Algorithm to U-Shaped Assembly Line Balancing Problem of Type II , 2014 .

[33]  B. Suman,et al.  A survey of simulated annealing as a tool for single and multiobjective optimization , 2006, J. Oper. Res. Soc..

[34]  Wang Shilong,et al.  An ant colony algorithm for job shop scheduling problem with tool flow , 2014 .

[35]  Talip Kellegöz,et al.  Assembly line balancing problems with multi-manned stations: a new mathematical formulation and Gantt based heuristic method , 2017, Ann. Oper. Res..

[36]  Yong Peng,et al.  Investigation on the injuries of drivers and copilots in rear-end crashes between trucks based on real world accident data in China , 2017, Future Gener. Comput. Syst..

[37]  Yixiong Feng,et al.  Data-driven accurate design of variable blank holder force in sheet forming under interval uncertainty using sequential approximate multi-objective optimization , 2017, Future generations computer systems.

[38]  Namhun Kim,et al.  Analytical Modeling of Human Choice Complexity in a Mixed Model Assembly Line Using Machine Learning-Based Human in the Loop Simulation , 2017, IEEE Access.

[39]  Feng Xia,et al.  Vehicular Social Networks: A survey , 2018, Pervasive Mob. Comput..

[40]  Wen-Chyuan Chiang,et al.  An optimal piecewise-linear program for the U-line balancing problem with stochastic task times , 2006, Eur. J. Oper. Res..

[41]  I. Sabuncuoglu,et al.  Stochastic assembly line balancing using beam search , 2005 .

[42]  Zhiwu Li,et al.  Two-agent stochastic flow shop deteriorating scheduling via a hybrid multi-objective evolutionary algorithm , 2018, Journal of Intelligent Manufacturing.

[43]  Bing-Hai Zhou,et al.  Multi-objective optimization of material delivery for mixed model assembly lines with energy consideration , 2018, Journal of Cleaner Production.

[44]  N. Metropolis,et al.  Equation of State Calculations by Fast Computing Machines , 1953, Resonance.