Abstract

Given the characteristics of decommissioning product diversity, wear difference, and structural complexity, we analyzed the disassembly line balance problems of minimum disassembly workstation, station load balancing, priority disassembly of high-demand parts and the lowest cost of invalid operations, and further considered the influence of random factors on actual disassembly operations. The purpose of this paper is to establish a model of sequence-dependent stochastic mixed-flowed partial disassembly line balancing problem and propose an adaptive hybrid particle swarm genetic algorithm to solve the model. The algorithm replaces the fixed value genetic operator with an adaptive crossover and mutation operator to improve the global optimization ability. The introduction of adaptive weighted particles leads to improved local optimization ability of the algorithm so that the algorithm has strong global and regional optimization ability to improve algorithm accuracy. The effectiveness of the proposed algorithm is verified by solving the classic disassembly line balancing problem with different scales and comparing it with the solution results of underlying genetic and particle swarm optimization algorithm. Meanwhile, the proposed model and algorithm are applied to the mixed-flow disassembly engineering project of a 25-task reducer. The results indicate that the proposed model is superior to the control group in terms of minimal disassembly workstation, station load balancing, invalid operation cost, and overall performance of the disassembly line, which verifies the validity of the model.

References

References
1.
Rabbani
,
M.
,
Ahmadzadeh
,
K.
, and
Farrokhi-Asl
,
H.
,
2019
, “
Remanufacturing Models Under Technology Licensing With Consideration of Environmental Issues
,”
Process Integr. Optim. Sustainability
,
3
, pp.
383
401
. 10.1007/s41660-019-00085-8
2.
Geda
,
M. W.
,
Kwong
,
C. K.
, and
Jiang
,
H.
,
2018
, “
Fastening Method Selection With Simultaneous Consideration of Product Assembly and Disassembly From a Remanufacturing Perspective
,”
Int. J. Adv. Manuf. Technol.
,
101
(
5–8
), pp.
1481
1493
. 10.1007/s00170-018-3027-1
3.
Andrés
,
C.
,
Lozano
,
S.
, and
Adenso Díaz
,
B.
,
2007
, “
Disassembly Sequence Planning in a Disassembly Cell Context
,”
Rob. Comput. Integr. Manuf.
,
23
(
6
), pp.
690
695
. 10.1016/j.rcim.2007.02.012
4.
Guo
,
X.
,
Liu
,
S.
,
Zhou
,
M. C.
, and
Tian
,
G.
,
2016
, “
Disassembly Sequence Optimization for Large-Scale Products With Multiresource Constraints Using Scatter Search and Petri Nets
,”
IEEE Trans. Cybern.
,
46
(
11
), pp.
2435
2446
. 10.1109/TCYB.2015.2478486
5.
Kim
,
H. W.
, and
Lee
,
D. H.
,
2018
, “
A Sample Average Approximation Algorithm for Selective Disassembly Sequencing With Abnormal Disassembly Operations and Random Operation Times
,”
Int. J. Adv. Manuf. Technol.
,
96
(
1–4
), pp.
1341
1354
. 10.1007/s00170-018-1667-9
6.
Yixiong
,
F.
,
Yicong
,
G.
,
Guangdong
,
T.
, and
Zhiwu
,
L.
,
2018
, “
Flexible Process Planning and End-of-Life Decision-Making for Product Recovery Optimization Based on Hybrid Disassembly
,”
IEEE Trans. Autom. Sci. Eng.
,
16
(
1
), pp.
311
326
. 10.1109/TASE.2018.2840348
7.
Gungor
,
A.
, and
Gupta
,
S. M.
,
2001
, “
A Solution Approach to the Disassembly Line Balancing Problem in the Presence of Task Failures
,”
Int. J. Prod. Res.
,
39
(
7
), pp.
1427
1467
. 10.1080/00207540110052157
8.
Mcgovern
,
S. M.
, and
Gupta
,
S. M.
,
2007
, “
A Balancing Method and Genetic Algorithm for Disassembly Line Balancing
,”
Eur. J. Oper. Res.
,
179
(
3
), pp.
692
708
. 10.1016/j.ejor.2005.03.055
9.
Mete
,
S.
,
Çil
,
Z. A.
,
Ağpak
,
K.
,
Özceylan
,
E.
, and
Dolgui
,
A.
,
2016
, “
A Solution Approach Based on Beam Search Algorithm for Disassembly Line Balancing Problem
,”
J. Manuf. Syst.
,
41
, pp.
188
200
. 10.1016/j.jmsy.2016.09.002
10.
Alshibli
,
M.
,
El Sayed
,
A.
,
Kongar
,
E.
,
Sobh
,
T. M.
, and
Gupta
,
S. M.
,
2016
, “
Disassembly Sequencing Using Tabu Search
,”
J. Intell. Rob. Syst.
,
82
(
1
), pp.
69
79
. 10.1007/s10846-015-0289-9
11.
Kalayci
,
C. B.
,
Polat
,
O.
, and
Gupta
,
S. M.
,
2015
, “
A Variable Neighbourhood Search Algorithm for Disassembly Lines
,”
J. Manuf. Technol. Manage
,
26
(
2
), pp.
182
194
. 10.1108/JMTM-11-2013-0168
12.
Ding
,
L. P.
,
Feng
,
Y. X.
,
Tan
,
J. R.
, and
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
), pp.
761
771
. 10.1007/s00170-009-2303-5
13.
Ren
,
Y.
,
Yu
,
D.
,
Zhang
,
C.
,
Tian
,
G.
,
Meng
,
L.
, and
Zhou
,
X.
,
2017
, “
An Improved Gravitational Search Algorithm for Profit-Oriented Partial Disassembly Line Balancing Problem
,”
Int. J. Prod. Res.
,
55
(
24
), pp.
7302
7316
. 10.1080/00207543.2017.1341066
14.
Zhang
,
Z.
,
Wang
,
K.
,
Zhu
,
L.
, and
Wang
,
Y.
,
2017
, “
A Pareto Improved Artificial Fish Swarm Algorithm for Solving a Multi-Objective Fuzzy Disassembly Line Balancing Problem
,”
Expert Syst. Appl.
,
86
, pp.
165
176
. 10.1016/j.eswa.2017.05.053
15.
Kalayci
,
C. B.
,
Polat
,
O.
, and
Gupta
,
S. M.
,
2016
, “
A Hybrid Genetic Algorithm for Sequence-Dependent Disassembly Line Balancing Problem
,”
Ann. Oper. Res.
,
242
(
2
), pp.
321
354
. 10.1007/s10479-014-1641-3
16.
Kalayci
,
C. B.
,
Hancilar
,
A.
,
Gungor
,
A.
, and
Gupta
,
S. M.
,
2014
, “
Multi-objective Fuzzy Disassembly Line Balancing Using a Hybrid Discrete Artificial Bee Colony Algorithm
,”
J. Manuf. Syst.
,
37
(
3
), pp.
672
682
. 10.1016/j.jmsy.2014.11.015
17.
Kannan
,
D.
,
Garg
,
K.
,
Jha
,
P. C.
, and
Diabat
,
A.
,
2017
, “
Integrating Disassembly Line Balancing in the Planning of a Reverse Logistics Network From the Perspective of a Third Party Provider
,”
Ann. Oper. Res.
,
253
(
1
), pp.
353
376
. 10.1007/s10479-016-2272-7
18.
Jiayi
,
L.
,
Zude
,
Z.
,
Truong
,
P. D.
,
Wenjun
,
X.
,
Junwei
,
Y.
,
Aiming
,
L.
,
Chunqian
,
J.
, and
Quan
,
L.
,
2018
, “
An Improved Multi-Objective Discrete Bees Algorithm for Robotic Disassembly Line Balancing Problem in Remanufacturing
,”
Int. J. Adv. Manuf. Technol.
,
97
(
9–12
), pp.
3937
3962
. 10.1007/s00170-018-2183-7
19.
Jianhua
,
C.
,
Xuhui
,
X.
,
Lei
,
W.
,
Zelin
,
Z.
, and
Xiang
,
L.
,
2019
, “
A Novel Multi-Eciency Optimization Method for Disassembly Line Balancing Problem
,”
Sustainability
,
11
(
24
), p.
6969
. 10.3390/su11246969
20.
Kaipu
,
W.
,
Xinyu
,
L.
, and
Liang
,
G.
,
2019
, “
A Multi-Objective Discrete Flower Pollination Algorithm for Stochastic Two-Sided Partial Disassembly Line Balancing Problem
,”
Comput. Ind. Eng.
,
130
, pp.
634
649
. 10.1016/j.cie.2019.03.017
21.
Agrawal
,
S.
, and
Tiwari
,
M. K.
,
2008
, “
A Collaborative Ant Colony Algorithm to Stochastic Mixed-Flow U-Shaped Disassembly Line Balancing and Sequencing Problem
,”
Int. J. Prod. Res.
,
46
(
6
), pp.
1405
1429
. 10.1080/00207540600943985
22.
Kalayci
,
C. B.
, and
Gupta
,
S. M.
,
2013
, “
A Particle Swarm Optimization Algorithm With Neighborhood-Based Mutation for Sequence-Dependent Disassembly Line Balancing Problem
,”
Int. J. Adv. Manuf. Technol.
,
69
(
1–4
), pp.
197
209
. 10.1007/s00170-013-4990-1
23.
Bentaha
,
M. L.
,
Battaïa
,
O.
, and
Dolgui
,
A.
,
2015
, “
An Exact Solution Approach for Disassembly Line Balancing Problem Under Uncertainty of the Task Processing Times
,”
Int. J. Prod. Res.
,
53
(
6
), pp.
1807
1818
. 10.1080/00207543.2014.961212
24.
Zheng
,
F.
,
He
,
J.
,
Chu
,
F.
, and
Liu
,
M.
,
2018
, “
A new Distribution-Free Model for Disassembly Line Balancing Problem With Stochastic Task Processing Times
,”
Int. J. Prod. Res.
,
56
(
24
), pp.
7341
7353
. 10.1080/00207543.2018.1430909
25.
Kalayci
,
C. B.
, and
Gupta
,
S. M.
,
2013
, “
Ant Colony Optimization for Sequence-Dependent Disassembly Line Balancing Problem
,”
J. Manuf. Technol. Manage.
,
24
(
3
), pp.
413
427
. 10.1108/17410381311318909
26.
Wang
,
Y.
,
Li
,
K.
, and
Li
,
K.
,
2019
, “
Dynamic Data Allocation and Task Scheduling on Multiprocessor Systems With NVM-Based SPM
,”
IEEE Access
,
7
, pp.
1548
1559
. 10.1109/ACCESS.2018.2887024
27.
Kalayci
,
C. B.
, and
Gupta
,
S. M.
,
2011
, “
A Hybrid Genetic Algorithm Approach for Disassembly Line Balancing
,”
Proceedings of the 42nd Annual Meeting of Decision Science Institute
,
Boston, MA
,
Nov. 19–22
, pp.
2142
2148
.
28.
Mcgovern
,
S. M.
, and
Gupta
,
S. M.
,
2006
, “
Ant Colony Optimization for Disassembly Sequencing With Multiple Objectives
,”
Int. J. Adv. Manuf. Technol.
,
30
(
5–6
), pp.
481
496
. 10.1007/s00170-005-0037-6
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