Skip to main content

Advertisement

SpringerLink
Log in

Modeling and optimization for noise-aversion and energy-awareness disassembly sequence planning problems in reverse supply chain

  • Sustainable Supply Chain Network Design
  • Published:
Environmental Science and Pollution Research Aims and scope Submit manuscript

Abstract

Nowadays, the reverse supply chain management receives much attention because of its critical role in environmental protection and economic development. Disassembly is very important in the reverse supply chain. It aims at dismantling valuable components from end-of-life products which are then remanufactured into like-new ones after reprocessing and reassembly operations. To efficiently organize and manage the remanufacturing process from the perspective of sustainable development, this work proposes a stochastic disassembly sequence planning problem with consideration of noise pollution and energy consumption to achieve disassembly profit maximization. A chance-constrained programming model is formulated to describe it mathematically. Then, a discrete marine predators algorithm combined with a stochastic simulation approach is specially designed. By conducting simulation experiments on some real-life instances and comparing the designed approach with two popularly known methods in literature, we mainly find that the proposed model and approach can make better disassembly plan for the investigated problem with maximal profit subject to the given noise pollution and energy consumption constraints. The results demonstrate that the proposed method can efficiently and effectively handle the considered problem, which contributes to reaching the highly reliable and environmentally sustainable disassembly process.

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
Fig. 2
Fig. 3

Similar content being viewed by others

Availability of data and materials

All data generated or analyzed during this study are included in this published article.

References

  • Alkahtani M, Ziout A (2019) Design of a sustainable reverse supply chain in a remanufacturing environment: a case study of proton-exchange membrane fuel cell battery in Riyadh. Advances in Mechanical Engineering 11(4):1–14

    Article  Google Scholar 

  • Ebeed M, Alhejji A, Kamel S, Jurado F (2020) Solving the optimal reactive power dispatch using marine predators algorithm considering the uncertainties in load and wind-solar generation systems. Energies. 13. https://doi.org/10.3390/en13174316

  • Faramarzi A, Heidarinejad M, Mirjalili S, Gandomi AH (2020) Marine predators algorithm: a nature-inspired metaheuristic. Expert Syst Appl 152:113377. https://doi.org/10.1016/j.eswa.2020.113377

    Article  Google Scholar 

  • Fathollahi-Fard AM, Hajiaghaei-Keshteli M (2018a) A stochastic multi-objective model for a closed-loop supply chain with environmental considerations. Appl Soft Comput 69:232–249

    Article  Google Scholar 

  • Fathollahi-Fard AM, Hajiaghaei-Keshteli M (2018b) A tri-level location-allocation model for forward/reverse supply chain. Appl Soft Comput 62:328–346

    Article  Google Scholar 

  • Fathollahi-Fard AM, Hajiaghaei-Keshteli M, Mirjalili S (2018) Multi-objective stochastic closed-loop supply chain network design with social considerations. Appl Soft Comput 71:505–525

    Article  Google Scholar 

  • Feng YX, Zhou MC, Tian GD, Li ZW, Zhang ZF, Zhang Q, Tan JR (2019) Target disassembly sequencing and scheme evaluation for CNC machine tools using improved multiobjective ant colony algorithm and fuzzy integral. IEEE Transactions on Systems, Man, and Cybernetics: Systems 49(12):2438–2451

    Article  Google Scholar 

  • Fu YP, Zhou MC, Guo XW, Qi L (2020a) Stochastic multi-objective integrated disassembly-reprocessing-reassembly scheduling via fruit fly optimization algorithm. J Clean Prod 278:123364. https://doi.org/10.1016/j.jclepro.2020.123364

    Article  Google Scholar 

  • Fu YP, Zhou MC, Guo XW, Qi L (2020b) Scheduling dual-objective stochastic hybrid flow shop with deteriorating jobs via bi-population evolutionary algorithm. IEEE Transactions on Systems, Man, and Cybernetics: Systems 50(12):5037–5048

    Article  Google Scholar 

  • Fu YP, Wang HF, Wang JW, Pu XJ (2020c) Multi-objective modelling and optimization for scheduling a stochastic hybrid flow with maximizing processing quality and minimizing total tardiness. IEEE Syst J:1–12. https://doi.org/10.1109/JSYST.2020.3014093

  • Fu YP, Wu D, Wang Y, Wang HF (2020d) Facility location and capacity planning considering policy preference and uncertain demand under the One Belt One Road initiative. Transportation Research Part A-Policy and Practice 138:172–186

    Article  Google Scholar 

  • Fu YP, Zhou MC, Guo XW, Qi L (2021) Multiverse optimization algorithm for stochastic bi-objective disassembly sequence planning subject to operation failures. IEEE Transactions on Systems, Man, and Cybernetics: Systems:1–11. https://doi.org/10.1109/TSMC.2021.3049323

  • Gao MM, Zhou MC, Huang XG, Wu ZM (2003) Fuzzy reasoning petri nets. IEEE Trans Syst Man Cybern Syst Hum 33(3):314–324

    Article  Google Scholar 

  • Gao MM, Zhou MC, Tang Y (2004) Intelligent decision making in disassembly process based on fuzzy reasoning petri nets. IEEE Transactions on Systems, Man and Cybernetics. Part B (Cybernetics) 34:2029–2034

    Article  Google Scholar 

  • Guo XW, Liu SX, Zhou MC, Tian GD (2018) Dual-objective program and scatter search for the optimization of disassembly sequences subject to multiresource constraints. IEEE Trans Autom Sci Eng 15(3):1091–1103

    Article  Google Scholar 

  • Guo J, Zhong JC, Li YB, Du BG, Guo SS (2019) A hybrid artificial fish swam algorithm for disassembly sequence planning considering setup time. Assem Autom 39(1):140–153

    Article  Google Scholar 

  • Guo XW, Zhou MC, Liu SX, Qi L (2020a) Multiresource-constrained selective disassembly with maximal profit and minimal energy consumption. IEEE Trans Autom Sci Eng 18:804–816. https://doi.org/10.1109/TASE.2020.2992220

    Article  Google Scholar 

  • Guo XW, Zhou MC, Liu SX, Qi L (2020b) Lexicographic multiobjective scatter search for the optimization of sequence-dependent selective disassembly subject to multiresource constraints. IEEE Transactions on Cybernetics 50(7):3307–3317

    Article  Google Scholar 

  • Hajiaghaei-Keshteli M, Fathollahi-Fard AM (2019) Sustainable closed-loop supply chain network design with discount supposition. Neural Comput & Applic 31:5343–5377

    Article  Google Scholar 

  • Kennedy J, Eberhart R (1995) Particle swarm optimization. In Proceedings of ICNN'95 - International Conference on Neural Networks 4:1942–1948 Perth, Australia

    Article  Google Scholar 

  • Khan SAR (2019) The nexus between carbon emissions, poverty, economic growth, and logistics operations-empirical evidence from southeast Asian countries. Environ Sci Pollut Res 26:13210–13220

    Article  Google Scholar 

  • Khan SAR, Dong QL (2017a) Impact of green supply chain management practices on firms’ performance: an empirical study from the perspective of Pakistan. Environ Sci Pollut Res 24:16829–16844

    Article  Google Scholar 

  • Khan SAR, Dong QL (2017b) Does national scale economic and environmental indicators spur logistics performance? Evidence from UK. Environ Sci Pollut Res 24:26692–26705

    Article  Google Scholar 

  • Khan SAR, Zhang Y (2020) Assessing the eco-environmental performance: an PLS-SEM approach with practice-based view. Int J Log Res Appl:1–19. https://doi.org/10.1080/13675567.2020.1754773

  • Khan SAR, Dong QL, Wei SB, Zaman K, Zhang Y (2017) Environmental logistics performance indicators affecting per capita income and sectoral growth: evidence from a panel of selected global ranked logistics countries. Environ Sci Pollut Res 24(2):1518–1531

    Article  CAS  Google Scholar 

  • Khan SAR, Zhang Y, Anees M, Golpîra H, Lahmar A, Dong QL (2018) Green supply chain management, economic growth and environment: a GMM based evidence. J Clean Prod 185:588–599

    Article  Google Scholar 

  • Khan SAR, Jian C, Zhang Y, Golpîra H, Kumar A, Sharif A (2019a) Environmental, social and economic growth indicators spur logistics performance: from the perspective of south Asian association for regional cooperation countries. J Clean Prod 214:1011–1023

    Article  Google Scholar 

  • Khan SAR, Sharif A, Golpîra H, Kumar A (2019b) A green ideology in Asian emerging economies: from environmental policy and sustainable development. Sustain Dev 27(6):1063–1075

    Article  Google Scholar 

  • Khan SAR, Zhang Y, Golpîra H, Sharif A, Mardani A (2020a) A state-of-the-art review and meta-analysis on sustainable supply chain management: future research directions. J Clean Prod 278:123357. https://doi.org/10.1016/j.jclepro.2020.123357

    Article  Google Scholar 

  • Khan SAR, Zhang Y, Sharif A, Golpîra H (2020b) Determinants of economic growth and environmental sustainability in South Asian Association for Regional Cooperation: evidence from panel ARDL. Environ Sci Pollut Res 27:45675–45687

    Article  Google Scholar 

  • Khan SAR, Zhang Y, Kumar A, Zavadskas E, Streimikiene D (2020c) Measuring the impact of renewable energy, public health expenditure, logistics, and environmental performance on sustainable economic growth. Sustain Dev 28(4):833–843

    Article  Google Scholar 

  • Khan SAR, Zhang Y, Sarwat S, Godil DI, Amin S, Shujaat S (2021) The role of block chain technology in circular economy practices to improve organisational performance. Int J Log Res Appl:1–18. https://doi.org/10.1080/13675567.2021.1872512

  • Lambert AJD (2007) Optimizing disassembly processes subjected to sequence-dependent cost. Comput Oper Res 34(2):536–551

    Article  Google Scholar 

  • Liu JY, Zhou ZD, Pham DT, Xu WJ, Ji CQ, Liu Q (2017) Robotic disassembly sequence planning using enhanced discrete bees algorithm in remanufacturing. Int J Prod Res 56(9):3134–3151

    Article  Google Scholar 

  • Lu C, Gao L, Li XY, Zheng J, Gong WY (2018) A multi-objective approach to welding shop scheduling for makespan, noise pollution and energy consumption. J Clean Prod 196:773–787

    Article  Google Scholar 

  • Lu C, Gao L, Pan QK, Li XY, Zheng J (2019) A multi-objective cellular grey wolf optimizer for hybrid flowshop scheduling problem considering noise pollution. Applied Soft Computing Journal 75:728–749

    Article  Google Scholar 

  • Meng K, Lou PH, Peng XH, Prybutok V (2016) An improved co-evolutionary algorithm for green manufacturing by integration of recovery option selection and disassembly planning for end-of-life products. Int J Prod Res 54(18):5567–5593

    Article  Google Scholar 

  • Özceylan E, Paksoy T (2013) Reverse supply chain optimisation with disassembly line balancing. Int J Prod Res 51(20):5985–6001

    Article  Google Scholar 

  • Pistolesi F, Lazzerini B (2019) TeMA: a tensorial memetic algorithm for many-objective parallel disassembly sequence planning in product refurbishment. IEEE Transactions on Industrial Informatics 15(6):3743–3753

    Article  Google Scholar 

  • Ren YP, Tian GD, Zhao F, Yu DY, Zhang CY (2017a) Selective cooperative disassembly planning based on multi-objective discrete artificial bee colony algorithm. Eng Appl Artif Intell 64:415–431

    Article  Google Scholar 

  • Ren YP, Yu DY, Zhang CY, Tian GD, Meng LL, Zhou XQ (2017b) An improved gravitational search algorithm for profit-oriented partial disassembly line balancing problem. Int J Prod Res 55(24):7302–7316

    Article  Google Scholar 

  • Ren YP, Jin HY, Zhao F, Qu T, Meng LL, Zhang CY, Zhang B, Wang G, Sutherland JW (2020) A multiobjective disassembly planning for value recovery and energy conservation from end-of-life products. IEEE Trans Autom Sci Eng 18:791–803. https://doi.org/10.1109/TASE.2020.2987391

    Article  Google Scholar 

  • Ruan JJ, Hu J, Xu ZM, Zhang JW (2016) Exposure risks of noise and heavy metals in dismantling lines for recovering waste televisions. J Clean Prod 112:4469–4476

    Article  CAS  Google Scholar 

  • Shaheen MAM, Yousri D, Fathy A, Hasanien HM, Alkuhayli A, Muyeen SM (2020) A novel application of improved marine predators algorithm and particle swarm optimization for solving the ORPD problem. Energies. 13. https://doi.org/10.3390/en13215679

  • Smith S, Hsu LY, Smith GC (2016) Partial disassembly sequence planning based on cost-benefit analysis. J Clean Prod 139:729–739

    Article  Google Scholar 

  • Tang Y, Zhou MC (2006) A systematic approach to design and operation of disassembly lines. IEEE Trans Autom Sci Eng 3(3):324–329

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Tian GD, Zhou MC, Chu JW, Liu YM (2012) Probability evaluation models of product disassembly cost subject to random removal time and different removal labor cost. IEEE Trans Autom Sci Eng 9(2):288–295

    Article  Google Scholar 

  • Tian GD, Zhou MC, Chu JW (2013) A chance constrained programming approach to determine the optimal disassembly sequence. IEEE Trans Autom Sci Eng 10(4):1004–1013

    Article  Google Scholar 

  • Tian GD, Zhou MC, Li PG (2018) Disassembly sequence planning considering fuzzy component quality and varying operational cost. IEEE Trans Autom Sci Eng 15(2):748–760

    Article  Google Scholar 

  • Tian GD, Ren YP, Feng YX, Zhou MC, Zhang HH, Tan JR (2019) Modeling and planning for dual-objective selective disassembly using AND/OR graph and discrete artificial bee colony. IEEE Transactions on Industrial Informatics 15(4):2456–2468

    Article  Google Scholar 

  • Tseng HE, Chang CC, Lee SC, Huang YM (2017) A block-based genetic algorithm for disassembly sequence planning. Expert Syst Appl 96:492–505

    Article  Google Scholar 

  • Tseng HE, Huang YM, Chang CC, Lee SC (2020) Disassembly sequence planning using a flatworm algorithm. J Manuf Syst 57:416–428

    Article  Google Scholar 

  • Wang KP, Li XY, 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

    Article  Google Scholar 

  • Xia K, Gao L, Li WD, Chao KM (2014) Disassembly sequence planning using a simplified teaching–learning-based optimization algorithm. Adv Eng Inform 28(4):518–527

    Article  Google Scholar 

  • Yin LJ, Li XY, Gao L, Lu C, Zhang Z (2017) A novel mathematical model and multi-objective method for the low-carbon flexible job shop scheduling problem. Sustainable Computing: Informatics and Systems 13:15–30

    Google Scholar 

  • Yu JP, Yang JT, Jiang ZG, Zhang H, Wang Y (2020) Emergy based sustainability evaluation of spent lead acid batteries recycling. J Clean Prod 250:119467. https://doi.org/10.1016/j.jclepro.2019.119467

    Article  Google Scholar 

  • Zhang Y, Khan SAR (2021) Evolutionary game analysis of green agricultural product supply chain financing system: COVID-19 pandemic. Int J Log Res Appl:1–21. https://doi.org/10.1080/13675567.2021.1879752

  • Zhang HC, Kuo TC, Lu H, Huang SH (1997) Environmentally conscious design and manufacturing: a state-of-the-art survey. J Manuf Syst 16(5):352–371

    Article  Google Scholar 

  • Zhang Y, Khan SAR, Kumar A, Golpîra H, Sharif A (2019) Is Tourism really affected by logistical operations and environmental degradation? An empirical study from the perspective of Thailand. J Clean Prod 227:158–166

    Article  Google Scholar 

  • Zhang Y, Tianshan M, Khan SAR (2020) Investigating the effect of government subsidies on end-of-life vehicle recycling. Waste Management & Research: The Journal for a Sustainable Circular Economy:1–21. https://doi.org/10.1080/13675567.2021.1879752

  • Zhang Y, Razzaq A, Rehman A, Shah A, Jameel K, Mor RS (2021) Disruption in global supply chain and socio-economic shocks: a lesson from COVID-19 for sustainable production and consumption. Oper Manag Res. https://doi.org/10.1007/s12063-021-00179-y

  • Zhu JF, Xu ZG, Su KY, Dong SH (2020) Asynchronous parallel disassembly sequence planning for multi-manipulator based on improved shuffled frog leaping algorithm. SN Applied Sciences 2. https://doi.org/10.1007/s42452-020-2680-9

  • Zussman E, Zhou MC (1999) A methodology for modeling and adaptive planning of disassembly processes. IEEE Trans Robot Autom 15(1):190–194

    Article  Google Scholar 

Download references

Funding

This work is supported in part by the National Natural Science Foundation of China under Grant No. 61703220, China Postdoctoral Science Foundation Funded Project under Grant No. 2019T120569, and Shandong Province Outstanding Youth Innovation Team Project of Colleges and Universities of China under Grant No. 2020RWG011.

Author information

Authors and Affiliations

  1. School of Business, Qingdao University, Qingdao, 266071, China

    Pei Liang & Yaping Fu

  2. College of Civil Engineering and Architecture, Qingdao Agricultural University, Qingdao, 266109, China

    Songyuan Ni

  3. School of Business Administration, Zhejiang Gongshang University, Hangzhou, 310018, China

    Bing Zheng

Authors
  1. Pei Liang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yaping Fu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Songyuan Ni
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Bing Zheng
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

PL was the main contributor and writer of the paper’s ideas and experimental design. YPF supervised the work and made much improvement about the method and experimental work. SYN and BZ did some experimental work, result analysis, and verification and contributed to the revision of this paper. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Yaping Fu.

Ethics declarations

Ethics approval

Not applicable.

Consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Responsible Editor: Eyup Dogan

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

Liang, P., Fu, Y., Ni, S. et al. Modeling and optimization for noise-aversion and energy-awareness disassembly sequence planning problems in reverse supply chain. Environ Sci Pollut Res (2021). https://doi.org/10.1007/s11356-021-14124-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11356-021-14124-w

Keywords

Search

Navigation