Araştırma Makalesi
BibTex RIS Kaynak Göster
Yıl 2021, Cilt: 9 Sayı: 1, 63 - 84, 30.06.2021
https://doi.org/10.17093/alphanumeric.891406

Öz

Kaynakça

  • Agrawal, S., & Tiwari, M. K. (2008). A collaborative ant colony algorithm to stochastic mixed-model U-shaped disassembly line balancing and sequencing problem. International Journal of Production Research. https://doi.org/10.1080/00207540600943985
  • Altekin, F. T. (2017). A comparison of piecewise linear programming formulations for stochastic disassembly line balancing. International Journal of Production Research. https://doi.org/10.1080/00207543.2017.1351639
  • Altekin, F. T., & Akkan, C. (2012). Task-failure-driven rebalancing of disassembly lines. International Journal of Production Research. https://doi.org/10.1080/00207543.2011.616915
  • Altekin, F. T., Bayındır, Z. P., & Gümüşkaya, V. (2016). Remedial actions for disassembly lines with stochastic task times. Computers and Industrial Engineering. https://doi.org/10.1016/j.cie.2016.06.027
  • Altekin, F. T., Kandiller, L., & Ozdemirel, N. E. (2008). Profit-oriented disassembly-line balancing. International Journal of Production Research. https://doi.org/10.1080/00207540601137207
  • Ameli, M., Mansour, S., & Ahmadi-Javid, A. (2019). A simulation-optimization model for sustainable product design and efficient end-of-life management based on individual producer responsibility. Resources, Conservation and Recycling. https://doi.org/10.1016/j.resconrec.2018.02.031
  • Amiri, M., & Mohtashami, A. (2012). Buffer allocation in unreliable production lines based on design of experiments, simulation, and genetic algorithm. International Journal of Advanced Manufacturing Technology. https://doi.org/10.1007/s00170-011-3802-8
  • Avikal, S., Jain, R., & Mishra, P. K. (2014). A Kano model, AHP and M-TOPSIS method-based technique for disassembly line balancing under fuzzy environment. Applied Soft Computing Journal. https://doi.org/10.1016/j.asoc.2014.08.002
  • Avikal, S., Mishra, P. K., & Jain, R. (2013). An AHP and PROMETHEE methods-based environment friendly heuristic for disassembly line balancing problems. Interdisciplinary Environmental Review. https://doi.org/10.1504/ier.2013.054125
  • Avikal, S., Mishra, P. K., & Jain, R. (2014). A Fuzzy AHP and PROMETHEE method-based heuristic for disassembly line balancing problems. International Journal of Production Research. https://doi.org/10.1080/00207543.2013.831999
  • Avikal, S., Mishra, P. K., Jain, R., & Yadav, H. C. (2013). A PROMETHEE Method Based Heuristic for Disassembly Line Balancing Problem. Industrial Engineering and Management Systems. https://doi.org/10.7232/iems.2013.12.3.254
  • Azadivar, F., & Wang, J. (2000). Facility layout optimization using simulation and genetic algorithms. International Journal of Production Research. https://doi.org/10.1080/00207540050205154
  • Bentaha, M. L., Battaiä, O., & Dolgui, A. (2015). An exact solution approach for disassembly line balancing problem under uncertainty of the task processing times. International Journal of Production Research. https://doi.org/10.1080/00207543.2014.961212
  • Bentaha, M. L., Battaïa, O., & Dolgui, A. (2014). A sample average approximation method for disassembly line balancing problem under uncertainty. Computers and Operations Research. https://doi.org/10.1016/j.cor.2014.05.006
  • Bentaha, M. L., Battaïa, O., Dolgui, A., & Hu, S. J. (2015). Second order conic approximation for disassembly line design with joint probabilistic constraints. European Journal of Operational Research. https://doi.org/10.1016/j.ejor.2015.06.019
  • Deniz, N., & Ozcelik, F. (2019). An extended review on disassembly line balancing with bibliometric & social network and future study realization analysis. Journal of Cleaner Production. https://doi.org/10.1016/j.jclepro.2019.03.188
  • Ding, H., Benyoucef, L., & Xie, X. (2003). Simulation Optimization in Manufacturing Analysis: A Simulation-Optimization Approach Using Genetic Search for Supplier Selection. Proceedings of the 35th Conference on Winter Simulation: Driving Innovation.
  • 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. International Journal of Advanced Manufacturing Technology. https://doi.org/10.1007/s00170-009-2303-5
  • Dowsland, K. A., & Thompson, J. M. (2012). Simulated annealing. In Handbook of Natural Computing. https://doi.org/10.1007/978-3-540-92910-9_49
  • Edis, E. B., Ilgin, M. A., & Edis, R. S. (2019). Disassembly line balancing with sequencing decisions: A mixed integer linear programming model and extensions. Journal of Cleaner Production. https://doi.org/10.1016/j.jclepro.2019.117826
  • Eglese, R. W. (1990). Simulated annealing: A tool for operational research. European Journal of Operational Research. https://doi.org/10.1016/0377-2217(90)90001-R
  • Fang, Y., Liu, Q., Li, M., Laili, Y., & Pham, D. T. (2019). Evolutionary many-objective optimization for mixed-model disassembly line balancing with multi-robotic workstations. European Journal of Operational Research. https://doi.org/10.1016/j.ejor.2018.12.035
  • Güçdemir, H., & Selim, H. (2017). Customer centric production planning and control in job shops: A simulation optimization approach. Journal of Manufacturing Systems. https://doi.org/10.1016/j.jmsy.2017.02.004
  • Gungor, A., & Gupta, S. M. (1999). Issues in environmentally conscious manufacturing and product recovery: A survey. Computers and Industrial Engineering. https://doi.org/10.1016/S0360-8352(99)00167-9
  • Güngör, Askiner, & Gupta, S. M. (2001). A solution approach to the disassembly line balancing problem in the presence of task failures. International Journal of Production Research. https://doi.org/10.1080/00207540110052157
  • Güngör, Aşkiner, & Gupta, S. M. (2002). Disassembly line in product recovery. International Journal of Production Research. https://doi.org/10.1080/00207540210135622
  • Ilgin, M. Ali, & Tunali, S. (2007). Joint optimization of spare parts inventory and maintenance policies using genetic algorithms. International Journal of Advanced Manufacturing Technology. https://doi.org/10.1007/s00170-006-0618-z
  • Ilgin, Mehmet Ali. (2019). A DEMATEL-Based Disassembly Line Balancing Heuristic. Journal of Manufacturing Science and Engineering, Transactions of the ASME. https://doi.org/10.1115/1.4041925
  • Ilgin, Mehmet Ali, Akçay, H., & Araz, C. (2017). Disassembly line balancing using linear physical programming. International Journal of Production Research. https://doi.org/10.1080/00207543.2017.1324225
  • Ilgin, Mehmet Ali, & Gupta, S. M. (2010). Environmentally conscious manufacturing and product recovery (ECMPRO): A review of the state of the art. Journal of Environmental Management. https://doi.org/10.1016/j.jenvman.2009.09.037
  • Ilgin, Mehmet Ali, & Taşoǧlu, G. T. (2016). Simultaneous Determination of Disassembly Sequence and Disassembly-to-Order Decisions Using Simulation Optimization. Journal of Manufacturing Science and Engineering, Transactions of the ASME. https://doi.org/10.1115/1.4033603
  • Kalayci, C. B., & Gupta, S. M. (2013a). A particle swarm optimization algorithm with neighborhood-based mutation for sequence-dependent disassembly line balancing problem. International Journal of Advanced Manufacturing Technology. https://doi.org/10.1007/s00170-013-4990-1
  • Kalayci, C. B., & Gupta, S. M. (2013b). Ant colony optimization for sequence-dependent disassembly line balancing problem. Journal of Manufacturing Technology Management. https://doi.org/10.1108/17410381311318909
  • Kalayci, C. B., & Gupta, S. M. (2013c). Artificial bee colony algorithm for solving sequence-dependent disassembly line balancing problem. Expert Systems with Applications. https://doi.org/10.1016/j.eswa.2013.06.067
  • Kalayci, C. B., & Gupta, S. M. (2013d). Balancing a sequencedependent disassembly line using simulated annealing algorithm. Applications of Management Science. https://doi.org/10.1108/S0276-8976(2013)0000016008
  • Kalayci, C. B., & Gupta, S. M. (2014). A tabu search algorithm for balancing a sequence-dependent disassembly line. Production Planning and Control. https://doi.org/10.1080/09537287.2013.782949
  • Kalayci, C. B., Hancilar, A., Gungor, A., & Gupta, S. M. (2015). Multi-objective fuzzy disassembly line balancing using a hybrid discrete artificial bee colony algorithm. Journal of Manufacturing Systems. https://doi.org/10.1016/j.jmsy.2014.11.015
  • Kalayci, C. B., Polat, O., & Gupta, S. M. (2016). A hybrid genetic algorithm for sequence-dependent disassembly line balancing problem. Annals of Operations Research. https://doi.org/10.1007/s10479-014-1641-3
  • 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 Transactions (Institute of Industrial Engineers). https://doi.org/10.1080/07408170802510390
  • Li, Z., Çil, Z. A., Mete, S., & Kucukkoc, I. (2020). A fast branch, bound and remember algorithm for disassembly line balancing problem. International Journal of Production Research, 58(11), 3220-3234.
  • Lin, Y. K., & Lin, H. C. (2015). Bicriteria scheduling problem for unrelated parallel machines with release dates. Computers and Operations Research. https://doi.org/10.1016/j.cor.2015.04.025
  • Liu, J., Zhou, Z., Pham, D. T., Xu, W., Yan, J., Liu, A., … Liu, Q. (2018). An improved multi-objective discrete bees algorithm for robotic disassembly line balancing problem in remanufacturing. International Journal of Advanced Manufacturing Technology. https://doi.org/10.1007/s00170-018-2183-7
  • Mattila, V., & Virtanen, K. (2015). Ranking and selection for multiple performance measures using incomplete preference information. European Journal of Operational Research. https://doi.org/10.1016/j.ejor.2014.10.028
  • McGovern, S. M., & Gupta, S. M. (2007). Combinatorial optimization analysis of the unary NP-complete disassembly line balancing problem. International Journal of Production Research. https://doi.org/10.1080/00207540701476281
  • McGovern, Seamus M., & Gupta, S. M. (2006). Ant colony optimization for disassembly sequencing with multiple objectives. International Journal of Advanced Manufacturing Technology. https://doi.org/10.1007/s00170-005-0037-6
  • McGovern, Seamus M., & Gupta, S. M. (2007). A balancing method and genetic algorithm for disassembly line balancing. European Journal of Operational Research. https://doi.org/10.1016/j.ejor.2005.03.055
  • Ozcan, Y. A., Tànfani, E., & Testi, A. (2017). Improving the performance of surgery-based clinical pathways: a simulation-optimization approach. Health Care Management Science. https://doi.org/10.1007/s10729-016-9371-5
  • Özceylan, E., Kalayci, C. B., Güngör, A., & Gupta, S. M. (2019). Disassembly line balancing problem: a review of the state of the art and future directions. International Journal of Production Research. https://doi.org/10.1080/00207543.2018.1428775
  • Özceylan, E., & Paksoy, T. (2013). Reverse supply chain optimisation with disassembly line balancing. International Journal of Production Research. https://doi.org/10.1080/00207543.2013.784405
  • Özceylan, E., & Paksoy, T. (2014a). Fuzzy mathematical programming approaches for reverse supply chain optimization with disassembly line balancing problem. Journal of Intelligent and Fuzzy Systems. https://doi.org/10.3233/IFS-130875
  • Özceylan, E., & Paksoy, T. (2014b). Interactive fuzzy programming approaches to the strategic and tactical planning of a closed-loop supply chain under uncertainty. International Journal of Production Research. https://doi.org/10.1080/00207543.2013.865852
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Disassembly Line Balancing by Using Simulation Optimization

Yıl 2021, Cilt: 9 Sayı: 1, 63 - 84, 30.06.2021
https://doi.org/10.17093/alphanumeric.891406

Öz

Increasing environmental awareness in today's society and stricter environmental regulations have forced manufacturing firms to take necessary actions for the recovery of end-of-life (EOL) products through different options (e.g., recycling, remanufacturing,). Disassembly is regarded as a critical operation in EOL treatment of used products since all product recovery options require the disassembly of EOL products at certain levels. This critical operation is generally carried out by forming disassembly lines in product recovery facilities. Miscellaneous methodologies based on heuristics, metaheuristics and mathematical programming have been proposed for the balancing of disassembly lines. Majority of those methodologies assume that disassembly line parameters are deterministic by ignoring the fact that a disassembly line involves great deal of uncertainty mainly due to uncertain conditions of arriving EOL products. Considering this high level of uncertainty, simulation modeling can be an effective tool for the modeling of disassembly lines. In this study, a simulation-based disassembly line balancing methodology is proposed for the explicit consideration of stochastic parameters. First, simulation model of a disassembly line is constructed. Since the disassembly line balancing problem has a combinatorial nature, two commonly used metaheuristics (i.e., genetic algorithms (GAs) and simulated annealing (SA)) are integrated with the simulation model in order to balance the disassembly line. The disassembly sequence and task assignments proposed by GA are compared with the sequence and task assignments proposed by SA. This comparison indicates that GA outperforms SA in four of eight performance measures while both algorithms have the same value for line efficiency measure.

Kaynakça

  • Agrawal, S., & Tiwari, M. K. (2008). A collaborative ant colony algorithm to stochastic mixed-model U-shaped disassembly line balancing and sequencing problem. International Journal of Production Research. https://doi.org/10.1080/00207540600943985
  • Altekin, F. T. (2017). A comparison of piecewise linear programming formulations for stochastic disassembly line balancing. International Journal of Production Research. https://doi.org/10.1080/00207543.2017.1351639
  • Altekin, F. T., & Akkan, C. (2012). Task-failure-driven rebalancing of disassembly lines. International Journal of Production Research. https://doi.org/10.1080/00207543.2011.616915
  • Altekin, F. T., Bayındır, Z. P., & Gümüşkaya, V. (2016). Remedial actions for disassembly lines with stochastic task times. Computers and Industrial Engineering. https://doi.org/10.1016/j.cie.2016.06.027
  • Altekin, F. T., Kandiller, L., & Ozdemirel, N. E. (2008). Profit-oriented disassembly-line balancing. International Journal of Production Research. https://doi.org/10.1080/00207540601137207
  • Ameli, M., Mansour, S., & Ahmadi-Javid, A. (2019). A simulation-optimization model for sustainable product design and efficient end-of-life management based on individual producer responsibility. Resources, Conservation and Recycling. https://doi.org/10.1016/j.resconrec.2018.02.031
  • Amiri, M., & Mohtashami, A. (2012). Buffer allocation in unreliable production lines based on design of experiments, simulation, and genetic algorithm. International Journal of Advanced Manufacturing Technology. https://doi.org/10.1007/s00170-011-3802-8
  • Avikal, S., Jain, R., & Mishra, P. K. (2014). A Kano model, AHP and M-TOPSIS method-based technique for disassembly line balancing under fuzzy environment. Applied Soft Computing Journal. https://doi.org/10.1016/j.asoc.2014.08.002
  • Avikal, S., Mishra, P. K., & Jain, R. (2013). An AHP and PROMETHEE methods-based environment friendly heuristic for disassembly line balancing problems. Interdisciplinary Environmental Review. https://doi.org/10.1504/ier.2013.054125
  • Avikal, S., Mishra, P. K., & Jain, R. (2014). A Fuzzy AHP and PROMETHEE method-based heuristic for disassembly line balancing problems. International Journal of Production Research. https://doi.org/10.1080/00207543.2013.831999
  • Avikal, S., Mishra, P. K., Jain, R., & Yadav, H. C. (2013). A PROMETHEE Method Based Heuristic for Disassembly Line Balancing Problem. Industrial Engineering and Management Systems. https://doi.org/10.7232/iems.2013.12.3.254
  • Azadivar, F., & Wang, J. (2000). Facility layout optimization using simulation and genetic algorithms. International Journal of Production Research. https://doi.org/10.1080/00207540050205154
  • Bentaha, M. L., Battaiä, O., & Dolgui, A. (2015). An exact solution approach for disassembly line balancing problem under uncertainty of the task processing times. International Journal of Production Research. https://doi.org/10.1080/00207543.2014.961212
  • Bentaha, M. L., Battaïa, O., & Dolgui, A. (2014). A sample average approximation method for disassembly line balancing problem under uncertainty. Computers and Operations Research. https://doi.org/10.1016/j.cor.2014.05.006
  • Bentaha, M. L., Battaïa, O., Dolgui, A., & Hu, S. J. (2015). Second order conic approximation for disassembly line design with joint probabilistic constraints. European Journal of Operational Research. https://doi.org/10.1016/j.ejor.2015.06.019
  • Deniz, N., & Ozcelik, F. (2019). An extended review on disassembly line balancing with bibliometric & social network and future study realization analysis. Journal of Cleaner Production. https://doi.org/10.1016/j.jclepro.2019.03.188
  • Ding, H., Benyoucef, L., & Xie, X. (2003). Simulation Optimization in Manufacturing Analysis: A Simulation-Optimization Approach Using Genetic Search for Supplier Selection. Proceedings of the 35th Conference on Winter Simulation: Driving Innovation.
  • 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. International Journal of Advanced Manufacturing Technology. https://doi.org/10.1007/s00170-009-2303-5
  • Dowsland, K. A., & Thompson, J. M. (2012). Simulated annealing. In Handbook of Natural Computing. https://doi.org/10.1007/978-3-540-92910-9_49
  • Edis, E. B., Ilgin, M. A., & Edis, R. S. (2019). Disassembly line balancing with sequencing decisions: A mixed integer linear programming model and extensions. Journal of Cleaner Production. https://doi.org/10.1016/j.jclepro.2019.117826
  • Eglese, R. W. (1990). Simulated annealing: A tool for operational research. European Journal of Operational Research. https://doi.org/10.1016/0377-2217(90)90001-R
  • Fang, Y., Liu, Q., Li, M., Laili, Y., & Pham, D. T. (2019). Evolutionary many-objective optimization for mixed-model disassembly line balancing with multi-robotic workstations. European Journal of Operational Research. https://doi.org/10.1016/j.ejor.2018.12.035
  • Güçdemir, H., & Selim, H. (2017). Customer centric production planning and control in job shops: A simulation optimization approach. Journal of Manufacturing Systems. https://doi.org/10.1016/j.jmsy.2017.02.004
  • Gungor, A., & Gupta, S. M. (1999). Issues in environmentally conscious manufacturing and product recovery: A survey. Computers and Industrial Engineering. https://doi.org/10.1016/S0360-8352(99)00167-9
  • Güngör, Askiner, & Gupta, S. M. (2001). A solution approach to the disassembly line balancing problem in the presence of task failures. International Journal of Production Research. https://doi.org/10.1080/00207540110052157
  • Güngör, Aşkiner, & Gupta, S. M. (2002). Disassembly line in product recovery. International Journal of Production Research. https://doi.org/10.1080/00207540210135622
  • Ilgin, M. Ali, & Tunali, S. (2007). Joint optimization of spare parts inventory and maintenance policies using genetic algorithms. International Journal of Advanced Manufacturing Technology. https://doi.org/10.1007/s00170-006-0618-z
  • Ilgin, Mehmet Ali. (2019). A DEMATEL-Based Disassembly Line Balancing Heuristic. Journal of Manufacturing Science and Engineering, Transactions of the ASME. https://doi.org/10.1115/1.4041925
  • Ilgin, Mehmet Ali, Akçay, H., & Araz, C. (2017). Disassembly line balancing using linear physical programming. International Journal of Production Research. https://doi.org/10.1080/00207543.2017.1324225
  • Ilgin, Mehmet Ali, & Gupta, S. M. (2010). Environmentally conscious manufacturing and product recovery (ECMPRO): A review of the state of the art. Journal of Environmental Management. https://doi.org/10.1016/j.jenvman.2009.09.037
  • Ilgin, Mehmet Ali, & Taşoǧlu, G. T. (2016). Simultaneous Determination of Disassembly Sequence and Disassembly-to-Order Decisions Using Simulation Optimization. Journal of Manufacturing Science and Engineering, Transactions of the ASME. https://doi.org/10.1115/1.4033603
  • Kalayci, C. B., & Gupta, S. M. (2013a). A particle swarm optimization algorithm with neighborhood-based mutation for sequence-dependent disassembly line balancing problem. International Journal of Advanced Manufacturing Technology. https://doi.org/10.1007/s00170-013-4990-1
  • Kalayci, C. B., & Gupta, S. M. (2013b). Ant colony optimization for sequence-dependent disassembly line balancing problem. Journal of Manufacturing Technology Management. https://doi.org/10.1108/17410381311318909
  • Kalayci, C. B., & Gupta, S. M. (2013c). Artificial bee colony algorithm for solving sequence-dependent disassembly line balancing problem. Expert Systems with Applications. https://doi.org/10.1016/j.eswa.2013.06.067
  • Kalayci, C. B., & Gupta, S. M. (2013d). Balancing a sequencedependent disassembly line using simulated annealing algorithm. Applications of Management Science. https://doi.org/10.1108/S0276-8976(2013)0000016008
  • Kalayci, C. B., & Gupta, S. M. (2014). A tabu search algorithm for balancing a sequence-dependent disassembly line. Production Planning and Control. https://doi.org/10.1080/09537287.2013.782949
  • Kalayci, C. B., Hancilar, A., Gungor, A., & Gupta, S. M. (2015). Multi-objective fuzzy disassembly line balancing using a hybrid discrete artificial bee colony algorithm. Journal of Manufacturing Systems. https://doi.org/10.1016/j.jmsy.2014.11.015
  • Kalayci, C. B., Polat, O., & Gupta, S. M. (2016). A hybrid genetic algorithm for sequence-dependent disassembly line balancing problem. Annals of Operations Research. https://doi.org/10.1007/s10479-014-1641-3
  • 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 Transactions (Institute of Industrial Engineers). https://doi.org/10.1080/07408170802510390
  • Li, Z., Çil, Z. A., Mete, S., & Kucukkoc, I. (2020). A fast branch, bound and remember algorithm for disassembly line balancing problem. International Journal of Production Research, 58(11), 3220-3234.
  • Lin, Y. K., & Lin, H. C. (2015). Bicriteria scheduling problem for unrelated parallel machines with release dates. Computers and Operations Research. https://doi.org/10.1016/j.cor.2015.04.025
  • Liu, J., Zhou, Z., Pham, D. T., Xu, W., Yan, J., Liu, A., … Liu, Q. (2018). An improved multi-objective discrete bees algorithm for robotic disassembly line balancing problem in remanufacturing. International Journal of Advanced Manufacturing Technology. https://doi.org/10.1007/s00170-018-2183-7
  • Mattila, V., & Virtanen, K. (2015). Ranking and selection for multiple performance measures using incomplete preference information. European Journal of Operational Research. https://doi.org/10.1016/j.ejor.2014.10.028
  • McGovern, S. M., & Gupta, S. M. (2007). Combinatorial optimization analysis of the unary NP-complete disassembly line balancing problem. International Journal of Production Research. https://doi.org/10.1080/00207540701476281
  • McGovern, Seamus M., & Gupta, S. M. (2006). Ant colony optimization for disassembly sequencing with multiple objectives. International Journal of Advanced Manufacturing Technology. https://doi.org/10.1007/s00170-005-0037-6
  • McGovern, Seamus M., & Gupta, S. M. (2007). A balancing method and genetic algorithm for disassembly line balancing. European Journal of Operational Research. https://doi.org/10.1016/j.ejor.2005.03.055
  • Ozcan, Y. A., Tànfani, E., & Testi, A. (2017). Improving the performance of surgery-based clinical pathways: a simulation-optimization approach. Health Care Management Science. https://doi.org/10.1007/s10729-016-9371-5
  • Özceylan, E., Kalayci, C. B., Güngör, A., & Gupta, S. M. (2019). Disassembly line balancing problem: a review of the state of the art and future directions. International Journal of Production Research. https://doi.org/10.1080/00207543.2018.1428775
  • Özceylan, E., & Paksoy, T. (2013). Reverse supply chain optimisation with disassembly line balancing. International Journal of Production Research. https://doi.org/10.1080/00207543.2013.784405
  • Özceylan, E., & Paksoy, T. (2014a). Fuzzy mathematical programming approaches for reverse supply chain optimization with disassembly line balancing problem. Journal of Intelligent and Fuzzy Systems. https://doi.org/10.3233/IFS-130875
  • Özceylan, E., & Paksoy, T. (2014b). Interactive fuzzy programming approaches to the strategic and tactical planning of a closed-loop supply chain under uncertainty. International Journal of Production Research. https://doi.org/10.1080/00207543.2013.865852
  • Paksoy, T., Güngör, A., Özceylan, E., & Hancilar, A. (2013). Mixed model disassembly line balancing problem with fuzzy goals. International Journal of Production Research. https://doi.org/10.1080/00207543.2013.795251
  • Seidi, M., & Saghari, S. (2016). The balancing of disassembly line of automobile engine using Genetic Algorithm (GA) in fuzzy environment. Industrial Engineering and Management Systems. https://doi.org/10.7232/iems.2016.15.4.364
  • Tasoglu, G., & Yildiz, G. (2019). Simulated annealing based simulation optimization method for solving integrated berth allocation and quay crane scheduling problems. Simulation Modelling Practice and Theory. https://doi.org/10.1016/j.simpat.2019.101948
  • Tuncel, E., Zeid, A., & Kamarthi, S. (2014). Solving large scale disassembly line balancing problem with uncertainty using reinforcement learning. Journal of Intelligent Manufacturing. https://doi.org/10.1007/s10845-012-0711-0
  • Wang, K., Li, X., & Gao, L. (2019). Modeling and optimization of multi-objective partial disassembly line balancing problem considering hazard and profit. Journal of Cleaner Production. https://doi.org/10.1016/j.jclepro.2018.11.114
  • Wang, S., Guo, X., & Liu, J. (2019). An efficient hybrid artificial bee colony algorithm for disassembly line balancing problem with sequence-dependent part removal times. Engineering Optimization. https://doi.org/10.1080/0305215X.2018.1564918
  • Xiao, S., Wang, Y., Yu, H., & Nie, S. (2017). An entropy-based adaptive hybrid particle swarm optimization for disassembly line balancing problems. Entropy. https://doi.org/10.3390/e19110596
  • Yin, P. Y., Wu, T. H., & Hsu, P. Y. (2017). Simulation based risk management for multi-objective optimal wind turbine placement using MOEA/D. Energy. https://doi.org/10.1016/j.energy.2017.09.103
  • Zeng, Q., Diabat, A., & Zhang, Q. (2015). A simulation optimization approach for solving the dual-cycling problem in container terminals. Maritime Policy and Management. https://doi.org/10.1080/03088839.2015.1043362
  • Zhang, Z., Wang, K., Zhu, L., & Wang, Y. (2017). A Pareto improved artificial fish swarm algorithm for solving a multi-objective fuzzy disassembly line balancing problem. Expert Systems with Applications. https://doi.org/10.1016/j.eswa.2017.05.053
  • Zhou, Y., Guo, X., & Li, D. (2020). A dynamic programming approach to a multi-objective disassembly line balancing problem. Annals of Operations Research, 1-24.
  • Zhu, L., Zhang, Z., & Wang, Y. (2018). A Pareto firefly algorithm for multi-objective disassembly line balancing problems with hazard evaluation. International Journal of Production Research. https://doi.org/10.1080/00207543.2018.1471238
  • Wang, K., Li, X., Gao, L., Li, P., & Sutherland, J. W. (2021). A Discrete Artificial Bee Colony Algorithm for Multiobjective Disassembly Line Balancing of End-of-Life Products. IEEE Transactions on Cybernetics, (Basım süresince).
Toplam 64 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Endüstri Mühendisliği
Bölüm Makaleler
Yazarlar

Muhammet Enes Akpınar 0000-0003-0328-6107

Mehmet Ali Ilgın 0000-0003-1765-2470

Hüseyin Aktaş 0000-0002-0580-4644

Yayımlanma Tarihi 30 Haziran 2021
Gönderilme Tarihi 4 Mart 2021
Yayımlandığı Sayı Yıl 2021 Cilt: 9 Sayı: 1

Kaynak Göster

APA Akpınar, M. E., Ilgın, M. A., & Aktaş, H. (2021). Disassembly Line Balancing by Using Simulation Optimization. Alphanumeric Journal, 9(1), 63-84. https://doi.org/10.17093/alphanumeric.891406

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