Skip to main content

Advertisement

SpringerLink
Log in

Novel distribution-free model and method for stochastic disassembly line balancing with limited distributional information

  • Published:
Journal of Combinatorial Optimization Aims and scope Submit manuscript

Abstract

Recycling of end-of-life (EOL) products has drawn much attention from both researchers and practitioners over the recent decades due to the environmental protection, sustainable development and economic benefits. For an EOL product recycling system, a core problem is to separate their useful and hazardous parts by an efficient disassembly line in which there exist uncertain factors, such as stochastic task processing time. The corresponding combinatorial optimization problems aim to optimally choose alternative task processes, determine the number of workstations to be opened, and assign the disassembly tasks to the opened workstations. In most existing studies, the probability distribution of task processing time is assumed to be known. However, the complete information of probability distribution is often unavailable due to various factors. In this study, we address a disassembly line balancing problem to minimize the total disassembly cost in which only limited information of probability distribution, i.e., the mean, lower and upper bounds of task processing time, is known. Based on problem analysis, some properties are derived for the construction of a new distribution-free model. Furthermore, an effective second-order cone program approximation-based method is developed to solve the proposed model. Experimental results of benchmark examples and newly generated instances demonstrate the effectiveness and efficiency of the proposed method in dealing with stochastic disassembly line balancing with limited distributional information. Finally, managerial insights and future research are discussed.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

  • Altekin FT (2017) A comparison of piecewise linear programming formulations for stochastic disassembly line balancing. Int J Prod Res 55(24):7412–7434

    Article  Google Scholar 

  • Altekin FT, Kandiller L, Ozdemirel NE (2008) Profit-oriented disassembly-line balancing. Int J Prod Res 46(10):2675–2693

    Article  Google Scholar 

  • Aydemir-Karadag A, Turkbey O (2013) Multi-objective optimization of stochastic disassembly line balancing with station paralleling. Comput Ind Eng 65(3):413–425

    Article  Google Scholar 

  • Bentaha ML, Battaïa O, Dolgui A (2012) A stochastic formulation of the disassembly line balancing problem. In: IFIP international conference on advances in production management systems. Springer, pp 397–404

  • Bentaha ML, Battaïa O, Dolgui A (2013) Chance constrained programming model for stochastic profit–oriented disassembly line balancing in the presence of hazardous parts. In: IFIP international conference on advances in production management systems. Springer, pp 103–110

  • Bentaha ML, Battaïa O, Dolgui A (2014a) A sample average approximation method for disassembly line balancing problem under uncertainty. Comput Oper Res 51:111–122

    Article  MathSciNet  Google Scholar 

  • Bentaha ML, Battaïa O, Dolgui A, Hu SJ (2014b) Dealing with uncertainty in disassembly line design. CIRP Ann 63(1):21–24

    Article  Google Scholar 

  • Bentaha ML, Battaïa O, Dolgui A (2015a) An exact solution approach for disassembly line balancing problem under uncertainty of the task processing times. Int J Prod Res 53(6):1807–1818

    Article  Google Scholar 

  • Bentaha ML, Battaïa O, Dolgui A, Hu SJ (2015b) Second order conic approximation for disassembly line design with joint probabilistic constraints. Eur J Oper Res 247(3):957–967

    Article  MathSciNet  Google Scholar 

  • Bentaha ML, Dolgui A, Battaïa O, Riggs RJ, Hu J (2018) Profit-oriented partial disassembly line design: dealing with hazardous parts and task processing times uncertainty. Int J Prod Res 56(24):7220–7242

    Article  Google Scholar 

  • Cheng J, Lisser A (2012) A second-order cone programming approach for linear programs with joint probabilistic constraints. Oper Res Lett 40(5):325–328

    Article  MathSciNet  Google Scholar 

  • Fang Y, Ming H, Li M, Liu Q, Pham DT (2020) Multi-objective evolutionary simulated annealing optimisation for mixed-model multi-robotic disassembly line balancing with interval processing time. Int J Prod Res 58(3):846–862

    Article  Google Scholar 

  • Gungor A, Gupta SM (1999a) Disassembly line balancing. In: Proceedings of the annual meeting of the northeast decision sciences institute, Newport, Rhode Island, pp 193–195

  • Gungor A, Gupta SM (1999b) Issues in environmentally conscious manufacturing and product recovery: a survey. Comput Ind Eng 36(4):811–853

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Güngör A, Gupta SM (2002) Disassembly line in product recovery. Int J Prod Res 40(11):2569–2589

    Article  Google Scholar 

  • Habibi MK, Battaïa O, Cung VD, Dolgui A (2017) Collection-disassembly problem in reverse supply chain. Int J Prod Econ 183:334–344

    Article  Google Scholar 

  • He J, Chu F, Zheng F, Liu M, Chu C (2020) A multi-objective distribution-free model and method for stochastic disassembly line balancing problem. Int J Prod Res 58(18):5721–5737

    Article  Google Scholar 

  • He J, Chu F, Zheng F, Liu M (2020) A green-oriented bi-objective disassembly line balancing problem with stochastic task processing times. Ann Oper Res. https://doi.org/10.1007/s10479-020-03558-z

  • Hezer S, Kara Y (2015) A network-based shortest route model for parallel disassembly line balancing problem. Int J Prod Res 53(6):1849–1865

    Article  Google Scholar 

  • Hoeffding W (1994) Probability inequalities for sums of bounded random variables. In: Fisher NI, Sen PK (eds) The collected works of Wassily Hoeffding. Springer, Berlin, pp 409–426

    Chapter  Google Scholar 

  • 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

    Article  Google Scholar 

  • Lambert A (1999) Linear programming in disassembly/clustering sequence generation. Comput Ind Eng 36(4):723–738

    Article  Google Scholar 

  • Li Z, Çil ZA, Mete S, Kucukkoc I (2020) A fast branch, bound and remember algorithm for disassembly line balancing problem. Int J Prod Res 58(11):3220–3234

    Article  Google Scholar 

  • Liu M, Liu X, Chu F, Zheng F, Chu C (2020) Robust disassembly line balancing with ambiguous task processing times. Int J Prod Res 58(19):5806–5835

    Article  Google Scholar 

  • Liu M, Liu X, Chu F, Zheng F, Chu C (2020) An exact method for disassembly line balancing problem with limited distributional information. Int J Prod Res. https://doi.org/10.1080/00207543.2019.1704092

  • Ma YS, Jun HB, Kim HW, Lee DH (2011) Disassembly process planning algorithms for end-of-life product recovery and environmentally conscious disposal. Int J Prod Res 49(23):7007–7027

    Article  Google Scholar 

  • McGovern S, Gupta S (2007a) Combinatorial optimization analysis of the unary np-complete disassembly line balancing problem. Int J Prod Res 45(18–19):4485–4511

    Article  Google Scholar 

  • McGovern SM, Gupta SM (2007b) A balancing method and genetic algorithm for disassembly line balancing. Eur J Oper Res 179(3):692–708

    Article  Google Scholar 

  • Mete S, Çil ZA, Ağpak K, Özceylan E, Dolgui A (2016) A solution approach based on beam search algorithm for disassembly line balancing problem. J Manuf Syst 41:188–200

    Article  Google Scholar 

  • Mete S, Çil ZA, Özceylan E, Ağpak K, Battaïa O (2018) An optimisation support for the design of hybrid production lines including assembly and disassembly tasks. Int J Prod Res 56(24):7375–7389

    Article  Google Scholar 

  • Ng M (2014) Distribution-free vessel deployment for liner shipping. Eur J Oper Res 238(3):858–862

    Article  MathSciNet  Google Scholar 

  • Özceylan E, Kalayci CB, Güngör A, Gupta SM (2019) Disassembly line balancing problem: a review of the state of the art and future directions. Int J Prod Res 57(15–16):4805–4827

    Article  Google Scholar 

  • Paterson DA, Ijomah WL, Windmill JF (2017) End-of-life decision tool with emphasis on remanufacturing. J Clean Prod 148:653–664

    Article  Google Scholar 

  • Perakis G, Roels G (2008) Regret in the newsvendor model with partial information. Oper Res 56(1):188–203

    Article  MathSciNet  Google Scholar 

  • Riggs RJ, Battaïa O, Hu SJ (2015) Disassembly line balancing under high variety of end of life states using a joint precedence graph approach. J Manuf Syst 37:638–648

    Article  Google Scholar 

  • Tang Y, Zhou M, Zussman E, Caudill R (2002) Disassembly modeling, planning, and application. J Manuf Syst 21(3):200–217

    Article  Google Scholar 

  • Tian G, Ren Y, Feng Y, Zhou M, Zhang H, Tan J (2018) Modeling and planning for dual-objective selective disassembly using and/or graph and discrete artificial bee colony. IEEE Trans Ind Inf 15(4):2456–2468

    Article  Google Scholar 

  • Wang K, Li X, Gao L (2019) A multi-objective discrete flower pollination algorithm for stochastic two-sided partial disassembly line balancing problem. Comput Ind Eng 130:634–649

  • Zheng F, He J, Chu F, Liu M (2018) A new distribution-free model for disassembly line balancing problem with stochastic task processing times. Int J Prod Res 56(24):7341–7353

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Economics and Management, Fuzhou University, Fuzhou, China

    Peng Hu, Feng Chu, Yunfei Fang & Peng Wu

  2. Laboratoire Informatique, Bio-informatique et Systmes Complexes, Univ-Évry, Université Paris-Saclay, Évry, France

    Peng Hu, Feng Chu & Yunfei Fang

Authors
  1. Peng Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Feng Chu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yunfei Fang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Peng Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Peng Wu.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hu, P., Chu, F., Fang, Y. et al. Novel distribution-free model and method for stochastic disassembly line balancing with limited distributional information . J Comb Optim 43, 1423–1446 (2022). https://doi.org/10.1007/s10878-020-00678-x

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10878-020-00678-x

Keywords

Search

Navigation