Evolutionary many-objective optimization for mixed-model disassembly line balancing with multi-robotic workstations

Abstract In the remanufacturing industries, automated disassembly becomes one of the most promising solution in achieving economic benefit. Robotic disassembly line balancing is a key problem that enables automated disassembly to be implemented at industrial scale. This paper focuses on evolutionary many-objective optimization for mixed-model disassembly line balancing with multi-robotic workstations. In each workstation, multiple skilled robots perform different tasks belonging to the different end-of-life products or subassemblies simultaneously. Based on the transformed AND/OR graph and parallel disassembly, a mathematical programming model is proposed to minimize the cycle time, the total energy consumption, the peak workstation energy consumption, and the number of robots being used simultaneously. Furthermore, a problem knowledge-leveraging evolutionary algorithm, including encoding/decoding scheme, initialization approach and problem-specific variation operators, is developed to deal with the above problem. Comprehensive experiments are conducted based on 8 product models and 63 problem instances generated in this study. In particular, a comparative study of our proposed algorithm and 5 representative evolutionary algorithms selected from the 3 classes of approaches of dealing with many-objective problems are provided. Then some insights with respect to the design of evolutionary algorithms for our problem are gained from the investigation.

[1]  Hua Xu,et al.  Multiobjective Flexible Job Shop Scheduling Using Memetic Algorithms , 2015, IEEE Transactions on Automation Science and Engineering.

[2]  Surendra M. Gupta,et al.  A balancing method and genetic algorithm for disassembly line balancing , 2007, Eur. J. Oper. Res..

[3]  Shengxiang Yang,et al.  Pareto or Non-Pareto: Bi-Criterion Evolution in Multiobjective Optimization , 2016, IEEE Transactions on Evolutionary Computation.

[4]  Eren Özceylan,et al.  An optimisation support for the design of hybrid production lines including assembly and disassembly tasks , 2018, Int. J. Prod. Res..

[5]  J. J. Bartholdi,et al.  Balancing two-sided assembly lines: a case study , 1993 .

[6]  Feifeng Zheng,et al.  A new distribution-free model for disassembly line balancing problem with stochastic task processing times , 2018, Int. J. Prod. Res..

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

[8]  Surendra M. Gupta,et al.  A hybrid genetic algorithm for sequence-dependent disassembly line balancing problem , 2016, Ann. Oper. Res..

[9]  Davide Giglio,et al.  Simulated annealing algorithms for the multi-manned assembly line balancing problem: minimising cycle time , 2017, Int. J. Prod. Res..

[10]  Alexandre Dolgui,et al.  A bibliographic review of production line design and balancing under uncertainty , 2015 .

[11]  Alfred J.D. Lambert,et al.  Linear programming in disassembly/clustering sequence generation , 1999 .

[12]  Ayyuce Aydemir-Karadag,et al.  Multi-objective optimization of stochastic disassembly line balancing with station paralleling , 2013, Comput. Ind. Eng..

[13]  Beatrice Lazzerini,et al.  EMOGA: A Hybrid Genetic Algorithm With Extremal Optimization Core for Multiobjective Disassembly Line Balancing , 2018, IEEE Transactions on Industrial Informatics.

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

[15]  Wenjun Xu,et al.  An improved multi-objective discrete bees algorithm for robotic disassembly line balancing problem in remanufacturing , 2018, The International Journal of Advanced Manufacturing Technology.

[16]  Peter Nielsen,et al.  Multi-objective co-operative co-evolutionary algorithm for minimizing carbon footprint and maximizing line efficiency in robotic assembly line systems , 2017 .

[17]  Surendra M. Gupta,et al.  Multi-objective fuzzy disassembly line balancing using a hybrid discrete artificial bee colony algorithm , 2015 .

[18]  Manoj Kumar Tiwari,et al.  A collaborative ant colony algorithm to stochastic mixed-model U-shaped disassembly line balancing and sequencing problem , 2008 .

[19]  Alexandre Dolgui,et al.  Profit-oriented partial disassembly line design: dealing with hazardous parts and task processing times uncertainty , 2018, Int. J. Prod. Res..

[20]  Alexandre Dolgui,et al.  An exact solution approach for disassembly line balancing problem under uncertainty of the task processing times , 2015 .

[21]  Alexandre Dolgui,et al.  Second order conic approximation for disassembly line design with joint probabilistic constraints , 2015, Eur. J. Oper. Res..

[22]  Qingfu Zhang,et al.  Multiobjective Optimization Problems With Complicated Pareto Sets, MOEA/D and NSGA-II , 2009, IEEE Transactions on Evolutionary Computation.

[23]  Eckart Zitzler,et al.  Indicator-Based Selection in Multiobjective Search , 2004, PPSN.

[24]  MengChu Zhou,et al.  Disassembly modeling, planning, and application , 2002 .

[25]  H.-J. Bullinger,et al.  Computer-aided depicting of precedence diagrams—A step towards efficient planning in assembly , 1984 .

[26]  Yixiong Feng,et al.  An Energy-Saving Optimization Method of Dynamic Scheduling for Disassembly Line , 2018 .

[27]  Chaoyong Zhang,et al.  An improved gravitational search algorithm for profit-oriented partial disassembly line balancing problem , 2017, Int. J. Prod. Res..

[28]  Yi Wang,et al.  A Pareto improved artificial fish swarm algorithm for solving a multi-objective fuzzy disassembly line balancing problem , 2017, Expert Syst. Appl..

[29]  Alexandre Dolgui,et al.  A taxonomy of line balancing problems and their solutionapproaches , 2013 .

[30]  Arthur C. Sanderson,et al.  AND/OR graph representation of assembly plans , 1986, IEEE Trans. Robotics Autom..

[31]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[32]  Levent Kandiller,et al.  Profit-oriented disassembly-line balancing , 2008 .

[33]  Nils Boysen,et al.  A classification of assembly line balancing problems , 2007, Eur. J. Oper. Res..

[34]  Sotirios G. Dimitriadis,et al.  Assembly line balancing and group working: A heuristic procedure for workers' groups operating on the same product and workstation , 2006, Comput. Oper. Res..

[35]  Xiaomin Zhu,et al.  A multi-objective algorithm for task scheduling and resource allocation in cloud-based disassembly , 2016 .

[36]  Manoj Kumar Tiwari,et al.  Constraint-based simulated annealing (CBSA) approach to solve the disassembly scheduling problem , 2012 .

[37]  S. G. Ponnambalam,et al.  An investigation on minimizing cycle time and total energy consumption in robotic assembly line systems , 2015 .

[38]  Eren Özceylan,et al.  A solution approach based on beam search algorithm for disassembly line balancing problem , 2016 .

[39]  Ihsan Sabuncuoglu,et al.  Two exact formulations for disassembly line balancing problems with task precedence diagram construction using an AND/OR graph , 2009 .

[40]  Alfred J. D. Lambert,et al.  Optimizing disassembly processes subjected to sequence-dependent cost , 2007, Comput. Oper. Res..

[41]  Mehmet Ali Ilgin,et al.  Disassembly line balancing using linear physical programming , 2017, Int. J. Prod. Res..

[42]  Xin Yao,et al.  Many-Objective Evolutionary Algorithms , 2015, ACM Comput. Surv..

[43]  Hui Yu,et al.  An Entropy-Based Adaptive Hybrid Particle Swarm Optimization for Disassembly Line Balancing Problems , 2017, Entropy.

[44]  Dong-Ho Lee,et al.  Disassembly process planning algorithms for end-of-life product recovery and environmentally conscious disposal , 2011 .

[45]  Turan Paksoy,et al.  Interactive fuzzy programming approaches to the strategic and tactical planning of a closed-loop supply chain under uncertainty , 2014 .

[46]  Surendra M. Gupta,et al.  Disassembly line in product recovery , 2002 .

[47]  Yixiong Feng,et al.  A new multi-objective ant colony algorithm for solving the disassembly line balancing problem , 2010 .

[48]  Peter J. Fleming,et al.  Methods for multi-objective optimization: An analysis , 2015, Inf. Sci..

[49]  Turan Paksoy,et al.  Mixed model disassembly line balancing problem with fuzzy goals , 2013 .

[50]  Alfred J.D. Lambert.  Optimal disassembly of complex products , 1994 .

[51]  Peter J. Fleming,et al.  Preference-inspired co-evolutionary algorithms using weight vectors , 2015, Eur. J. Oper. Res..

[52]  Supachai Vongbunyong,et al.  Disassembly Automation: Automated Systems with Cognitive Abilities , 2015 .

[53]  Can Akkan,et al.  Task-failure-driven rebalancing of disassembly lines , 2012 .

[54]  Surendra M. Gupta,et al.  A particle swarm optimization algorithm with neighborhood-based mutation for sequence-dependent disassembly line balancing problem , 2013, The International Journal of Advanced Manufacturing Technology.

[55]  Yi Wang,et al.  A Pareto firefly algorithm for multi-objective disassembly line balancing problems with hazard evaluation , 2018, Int. J. Prod. Res..

[56]  Yakup Kara,et al.  A network-based shortest route model for parallel disassembly line balancing problem , 2015 .

[57]  S. Jack Hu,et al.  Disassembly line balancing under high variety of end of life states using a joint precedence graph approach , 2015 .

[58]  Lothar Thiele,et al.  Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach , 1999, IEEE Trans. Evol. Comput..

[59]  Surendra M. Gupta,et al.  A tabu search algorithm for balancing a sequence-dependent disassembly line , 2014 .

[60]  Turan Paksoy,et al.  Reverse supply chain optimisation with disassembly line balancing , 2013 .

[61]  Eren Özceylan,et al.  Disassembly line balancing problem: a review of the state of the art and future directions , 2019, Int. J. Prod. Res..

[62]  Askiner Gungor,et al.  A solution approach to the disassembly line balancing problem in the presence of task failures , 2001 .