Based on the bat algorithm (BA), this paper proposes a discrete BA (DBA) approach to optimize the
disassembly sequence planning (DSP) problem, for the purpose of obtaining an optimum disassembly sequence
(ODS) of a product with a high degree of automation and guiding maintenance operation. The BA for solving
continuous problems is introduced, and combining with mathematical formulations, the BA is reformed to be
the DBA for DSP problems. The fitness function model (FFM) is built to evaluate the quality of disassembly
sequences. The optimization performance of the DBA is tested and verified by an application case, and the
DBA is compared with the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and differential
mutation BA (DMBA). Numerical experiments show that the proposed DBA has a better optimization capability
and provides more accurate solutions than the other three algorithms.
JIAO Qinglong (焦庆龙), XU Da (徐达)
. A Discrete Bat Algorithm for Disassembly Sequence Planning[J]. Journal of Shanghai Jiaotong University(Science), 2018
, 23(2)
: 276
-285
.
DOI: 10.1007/s12204-018-1937-6
[1] ZHANG X F, YU G, HU Z Y, et al. Parallel disassemblysequence planning for complex products based onfuzzy-rough sets [J]. The International Journal of AdvancedManufacturing Technology, 2014, 72(1-4): 231-239.
[2] MIN S S, ZHU X J, ZHU X. Mechanical product disassemblyand/or graph construction [C]//InternationalConference on Measuring Technology and MechatronicsAutomation. Changsha, China: IEEE, 2010: 627-631.
[3] PETER M, WANG C G, CHEN J T. Virtual disassemblysequences generation and evaluation [J]. ProcediaCIRP, 2016, 44(1): 347-352.
[4] MAROUA K, MOEZ T, NIZAR A. Disassembly sequenceplanning based on a genetic algorithm [J]. Proceedingsof the Institution of Mechanical Engineers,Part C: Journal of Mechanical Engineering Science,2015, 229(12): 2281-2290.
[5] PORNSING C, WATANASUNGSUIT A. A discreteparticle swarm optimization for disassembly sequenceplanning [C]//IEEE International Conferenceon Management of Innovation and Technology. London,UK: IEEE, 2014: 480-485.
[6] ZHANG X H, TIAN L. Selective disassembly sequenceplanning based on ant colony algorithm [C]//7th InternationalConference on System of Systems Engineering.Genova, Italy: IEEE, 2012: 236-239.
[7] LU C, LIU Y C. A disassembly sequence planning approachwith an advanced immune algorithm [J]. Proceedingsof the Institution of Mechanical Engineers,Part C: Journal of Mechanical Engineer Science, 2012,226(11): 2739-2749.
[8] LIU Z F, YANG D J, GU G G. Disassembly sequenceplanning based on particle swarm-simulated annealingoptimization [J]. Journal of Hefei University of Technology:Natural Science Edition, 2011, 34(2): 161-165(in Chinese).
[9] YEH W C, WEI S C. Simplified swarm optimizationin efficient tool assignment of disassembly sequencingproblem [C]//IEEE Congress on Evolutionary Computation.Cancun, Mexico: IEEE, 2013: 2712-2719.
[10] YEH W C. Simplified swarm optimization in disassemblysequencing problems with learning effects [J].Computers & Operation Research, 2012, 39(9): 2168-2177.
[11] SONG S X, ZHANG W S, ZHANG L. Product disassemblysequence planning based on improved artificialbee colony algorithm [J]. China Mechanical Engineering,2016, 27(17): 2384-2390 (in Chinese).
[12] XIA K, GAO L, LI W D, et al. Disassembly sequenceplanning using a simplified teaching-learning-based optimizationalgorithm [J]. Advanced Engineering Informatics,2014, 28(4): 518-527.
[13] YANG X S. A new metaheuristic bat-inspired algorithm[C]//Nature Inspired Cooperative Strategiesfor Optimization (NICSO 2010). Berlin, German:Springer, 2010: 65-74.
[14] YANG X S, AMIR H G. Bat algorithm: a novel approachfor global engineering optimization [J]. EngineeringComputations, 2012, 29(5): 464-483.
[15] ZHAO Y X, YANG X S, LIU L Q. New meta-heuristicoptimization algorithms [M]. Beijing, China: SciencePress, 2013: 313-314 (in Chinese).
[16] YASSINE S,MOHMMED E R. A novel discrete bat algorithmfor solving the travelling salesman problem [J].Neural Computing & Applications, 2016, 27(7): 1853-1866.
[17] YANG X S, MEHMET K, SIMON F. Bat algorithmfor topology optimization in microelectronic applications[C]//The 1st International Conference on FutureGeneration Communication Technologies. London,UK: IEEE, 2012: 150-155.
[18] ESLAM A H, AHMED I H, ABOUL E H, et al. Adiscrete bat algorithm for the community detectionproblem [J]. Lecture Notes in Computer Science, 2015,9129(1): 188-199.
[19] IWANKOWICZ R R. An efficient evolutionary methodof assembly sequence planning for shipbuilding industry[J]. Assembly Automation, 2016, 36(1): 60-71.
[20] PENG M. Research on assembly sequence planningbased on differential mutation bat algorithm [D]. Xiangtan,China: Xiangtan University, 2014 (in Chinese).
[21] ZENG B, LI M F, ZHANG Y, et al. Research on assemblysequence planning based on firefly algorithm[J]. Journal of Mechanical Engineering, 2013, 49(11):177-184 (in Chinese).
[22] WANG S, SUN Z Z, GUO J W, et al. Assemblysequence planning based on shuffled frog leaping algorithm[J]. Computer Integrated Manufacturing Systems,2014, 20(12): 2991-2999 (in Chinese).
[23] JIAO Q L, XU D, LI C. Product disassembly sequenceplanning based on flower pollination algorithm [J].Computer Integrated Manufacturing Systems, 2016,22(12): 2791-2799 (in Chinese).
[24] LI X. Research on assembly sequence planningbased on the genetic algorithm and application [D].Shenyang, China: Northeastern University, 2011 (inChinese).
[25] LV H G, LU C. A discrete particle swarm optimizationalgorithm for assembly sequence planning [C]//8th InternationalConference on Reliability, Maintainabilityand Safety. Chengdu, China: IEEE, 2009: 1119-1122.
[26] EBERHART R C, KENNEDY J. A new optimizer usingparticle swarm theory [C]//Proceedings of the 6thInternational Symposium on Micro Machine and HumanScience. Piscataway, NJ, USA: IEEE, 1995: 39-43.
