Abstract
For environmentally conscious and sustainable manufacturing, manufacturers need to incorporate product recovery by designing manufacturing systems to include reverse manufacturing by considering both assembly and disassembly systems. Just as the assembly line is considered the most efficient way to assemble a product, the disassembly line is seen to be the most efficient way to disassemble a product. While having some similarities to assembly, disassembly is not the reverse of the assembly process. The challenge lies in the fact that it possesses unique characteristics. In this paper, we consider a sequence-dependent disassembly line balancing problem (SDDLBP) that is concerned with the assignment of disassembly tasks to a set of ordered disassembly workstations while satisfying the disassembly precedence constraints and optimizing the effectiveness of several measures considering sequence-dependent part removal time increments. SDDLBP is not a trivial problem since it is proven to be NP-complete. Further complications occur by considering multiple objectives including environmental and economic goals that are often contradictory. Therefore, it is essential that an efficient methodology be developed. A new approach based on the particle swarm optimization algorithm with a neighborhood-based mutation operator is proposed to solve the SDDLBP. Case scenarios are considered, and comparisons with ant colony optimization, river formation dynamics, and tabu search approaches are provided to demonstrate the superior functionality of the proposed algorithm.
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References
Gungor A, Gupta SM (1999) Issues in environmentally conscious manufacturing and product recovery: a survey. Comput Ind Eng 36(4):811–853
Ilgin MA, Gupta SM (2010) Environmentally conscious manufacturing and product recovery (ECMPRO): a review of the state of the art. J Environ Manag 91(3):563–591
Lambert AJ, Gupta SM (2005) Disassembly modeling for assembly, maintenance, reuse, and recycling. CRC Press, Boca Raton, FL
Gungor A, Gupta SM (2001) A solution approach to the disassembly line balancing problem in the presence of task failures. Int J Prod Res 39(7):1427–1467
McGovern SM, Gupta SM (2011) The disassembly line: balancing and modeling. McGraw Hill, New York
Gungor A, Gupta SM (2002) Disassembly line in product recovery. Int J Prod Res 40(11):2569–2589
McGovern SM, Gupta SM (2007) A balancing method and genetic algorithm for disassembly line balancing. Eur J Oper Res 179(3):692–708
Altekin FT, Akkan C (2012) Task-failure-driven rebalancing of disassembly lines. Int J Prod Res 50(18):4955–4976
Altekin FT, Kandiller L, Ozdemirel NE (2008) Profit-oriented disassembly-line balancing. Int J Prod Res 46(10):2675–2693
Koc A, Sabuncuoglu I, Erel E (2009) Two exact formulations for disassembly line balancing problems with task precedence diagram construction using an AND/OR graph. IIE Trans 41(10):866–881
Kalayci CB, Gupta SM A hybrid genetic algorithm approach for disassembly line balancing. Proceedings of the 42nd Annual Meeting of Decision Science Institute (DSI 2011), Boston, MA, USA, Nov 19–22 2011, pp. 2931–2936
McGovern SM (2005) Gupta SM Uninformed and probabilistic distributed agent combinatorial searches for the unary NP-complete disassembly line balancing problem. Proceedings of the SPIE International Conference on Environmentally Conscious Manufacturing V, Boston, MA, USA, pp 81–92
McGovern SM, Gupta SM (2006) Ant colony optimization for disassembly sequencing with multiple objectives. Int J Adv Manuf Technol 30(5):481–496
McGovern SM, Gupta SM (2007) Combinatorial optimization analysis of the unary NP-complete disassembly line balancing problem. Int J Prod Res 45(18–19):4485–4511
Agrawal S, Tiwari MK (2008) A collaborative ant colony algorithm to stochastic mixed-model U-shaped disassembly line balancing and sequencing problem. Int J Prod Res 46(6):1405–1429
Tripathi M, Agrawal S, Pandey MK, Shankar R, Tiwari MK (2009) Real world disassembly modeling and sequencing problem: optimization by algorithm of self-guided ants (ASGA). Robot Comput Integr Manuf 25(3):483–496
Ding L-P, Feng Y-X, Tan J-R, Gao Y-C (2010) A new multi-objective ant colony algorithm for solving the disassembly line balancing problem. Int J Adv Manuf Technol 48(5–8):761–771
Kalayci CB, Gupta SM, Nakashima K A Simulated Annealing Algorithm for Balancing a Disassembly Line. Proceedings of the Seventh International Symposium on Environmentally Conscious Design and Inverse Manufacturing (EcoDesign 2011), Kyoto, Japan, Nov 30–Dec 2 2011. pp 713–718
Kalayci CB, Gupta SM Tabu search for disassembly line balancing with multiple objectives. Proceedings of the 41st International Conference on Computers and Industrial Engineering (CIE41), University of Southern California, Los Angeles, USA, 23–26 October 2011. pp. 477–482
Kalayci CB, Gupta SM, Nakashima K (2011) Bees colony intelligence in solving disassembly line balancing problem. Proceedings of the 2011 Asian Conference of Management Science and Applications (ACMSA2011), Sanya, Hainan, China, Dec 21–22. pp 34–41
Scholl A, Boysen N, Fliedner M (2006) The sequence-dependent assembly line balancing problem. OR Spectr 30(3):579–609
Anonymous (2009) Electronic waste and organized crime-assessing the links. Trends in Organized Crime 12(3–4):352–378
Kennedy J, Eberhart R (2005) Particle swarm optimization. Proceedings of the IEEE International Conference on Neural Networks, volume 4, Perth, Australia, November 27–December 1, 2005. pp 1942–1948
Nearchou AC (2011) Maximizing production rate and workload smoothing in assembly lines using particle swarm optimization. Int J Prod Econ 129(2):242–250
Rahimi-Vahed AR, Mirghorbani SM, Rabbani M (2007) A new particle swarm algorithm for a multi-objective mixed-model assembly line sequencing problem. Soft Comput 11(10):997–1012
Kang Q, He H (2011) A novel discrete particle swarm optimization algorithm for meta-task assignment in heterogeneous computing systems. Microprocess Microsyst 35(1):10–17
Rahimi-Vahed AR, Mirghorbani SM, Rabbani M (2007) A hybrid multi-objective particle swarm algorithm for a mixed-model assembly line sequencing problem. Eng Optim 39(8):877–898
Pan Q-K, Fatih Tasgetiren M, Liang Y-C (2008) A discrete particle swarm optimization algorithm for the no-wait flowshop scheduling problem. Comput Oper Res 35(9):2807–2839
Kashan AH, Karimi B (2009) A discrete particle swarm optimization algorithm for scheduling parallel machines. Comput Ind Eng 56(1):216–223
Gupta SM, Erbis E, McGovern SM (2004) Disassembly sequencing problem: A case study of a cell phone. Proceedings of the SPIE International Conference on Environmentally Conscious Manufacturing IV, Philadelphia, Pennsylvania, October 26–27, 2004. pp 43–52
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Kalayci, C.B., Gupta, S.M. A particle swarm optimization algorithm with neighborhood-based mutation for sequence-dependent disassembly line balancing problem. Int J Adv Manuf Technol 69, 197–209 (2013). https://doi.org/10.1007/s00170-013-4990-1
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DOI: https://doi.org/10.1007/s00170-013-4990-1