A dynamic parameter controlled harmony search algorithm for assembly sequence planning

Li, Xinyu; Qin, Kai; Zeng, Bing; Gao, Liang; Wang, Lijian

doi:10.1007/s00170-017-0352-8

Cited by 13 publications

(7 citation statements)

References 37 publications

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“…Input: the interference matrix IM 10+ of the EOL product, the disassembly component sequence X, and its corresponding disassembly direction sequence D Output: an improved disassembly sequence Update D by modifying the disassembly direction of c. Finally, a new component sequence X new (3,5,1,4,2,6,8,7) and its corresponding direction sequence D new (+x, +y, +x, -x, -x, +z, +x, +y) are generated.…”

Section: Nsomentioning

confidence: 99%

“…Firstly, in Section 4.1, a vise [6] with 11 components and a ball valve [7] with 17 components are used to verify the effectiveness of the modified strategies in MGWO.…”

Section: Case Studies and Industrial Applicationmentioning

confidence: 99%

“…Although the DSP problem needs to be solved urgently, most of the existing research focuses on assembly sequence planning [3][4][5][6][7]. The research on DSP is relatively few.…”

Section: Introductionmentioning

confidence: 99%

“…The pseudo-code of NSOFig.4provides a schematic diagram of NSO. Firstly, selecting component 1 to change its position and disassembly direction in the original component sequence X original(3,5,4,2,1,6,8,7). Secondly,…”

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confidence: 99%

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Disassembly sequence planning based on a modified grey wolf optimizer

Xie

Gao

2021

Int J Adv Manuf Technol

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Disassembly sequence planning (DSP) can effectively increase the disassembly efficiency, shorten the disassembly cycle, reduce disassembly costs and reduce environmental hazards of end-oflife (EOL) products, playing an important role in manufacturing industries. Thus, it is urgent to propose an approach to solve the DSP problem. DSP is a famous NP-hard combinatorial optimization problem.As the size of components increases, exact algorithms can hardly obtain the optimal disassembly sequence. Therefore, we proposes a promising intelligence algorithm, modified grey wolf optimizer (MGWO), for solving the DSP problem. MGWO inherits the main idea of the hierarchy and hunting mechanism of the original grey wolf optimizer (GWO). Three new operators are designed in MGWO to ensure the feasibility of solutions under the complex constraint of disassembly precedence. The feasible solution generator (FSG) is designed to obtain feasible disassembly sequences, the neighborhood search operator (NSO) is developed to make wolves (solutions) self-evolving, and the guided search operator (GSO) is used to make the wolf group guided by three leaders of wolves. Two engineering cases are applied to validate the effectiveness of the proposed operators. Then, they and one real-world application are used to compare the MGWO with other reported methods. The results demonstrate that MGWO can solve the DSP problem effectively.

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Section: Nsomentioning

confidence: 99%

“…Firstly, in Section 4.1, a vise [6] with 11 components and a ball valve [7] with 17 components are used to verify the effectiveness of the modified strategies in MGWO.…”

Section: Case Studies and Industrial Applicationmentioning

confidence: 99%

“…Although the DSP problem needs to be solved urgently, most of the existing research focuses on assembly sequence planning [3][4][5][6][7]. The research on DSP is relatively few.…”

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Disassembly sequence planning based on a modified grey wolf optimizer

Xie

Gao

2021

Int J Adv Manuf Technol

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“…Nature-motivated algorithms such as the metaheuristic algorithm (MA) are most widely used for optimization as they have many advantages over conventional algorithms. MAs are diverse, including genetic algorithm, simulated annealing, ant and bee algorithm, particle swarm optimization (PSO) [23][24][25][26], harmony search algorithm (HSA) [27], and cuckoo search.…”

Section: Introductionmentioning

confidence: 99%

Realizing a Novel Friction Stir Processing-Enabled FWTPET Process for Strength Enhancement Using Firefly and PSO Methods

et al. 2020

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The friction welding of tube to tube plate using an external tool (FWTPET) is widely deployed in several industrial applications, such as aerospace, automotive, and power plants. Moreover, for achieving a better tensile strength and hardness in the weld zone, the friction stir processing (FSP) technique was incorporated into the FWTPET process for joining aluminum alloys (AA6063 tube, AA6061 tube plate). Furthermore, it has to be noted that FWTPET was applied for joining the AA6063 tube to the AA6061 tube plate, and FSP was deployed for reinforcing the weld zone with carbon nanotube (CNT) and silicon nitride (Si3N4) particles, thereby attaining the desirable mechanical properties. Subsequently, the Taguchi L25 orthogonal array was used for identifying the most influential input and output FWTPET + FSP process parameters. Furthermore, particle swarm optimization (PSO) and the firefly algorithm (FFA) were deployed for determining the optimized input and output FWTPET + FSP process parameters. The input process parameters include CNT, Si3N4, rotational tool speed, and depth. Furthermore, the tensile strength of the welded joint was considered as the output process parameter. The process parameters predicted by PSO and FFA were compared with the experimental values. It was witnessed that deviation between the predicted and experimental values was minimal. Moreover, it was found that FFA provided a superior tensile strength prediction than PSO.

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Harmony Search Algorithm with Dynamic Adjustment of PAR Values for Asymmetric Traveling Salesman Problem

Szwarc

Boryczka

2020

Intelligent Information and Database Systems

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A dynamic parameter controlled harmony search algorithm for assembly sequence planning

Cited by 13 publications

References 37 publications

Disassembly sequence planning based on a modified grey wolf optimizer

Disassembly sequence planning based on a modified grey wolf optimizer

Realizing a Novel Friction Stir Processing-Enabled FWTPET Process for Strength Enhancement Using Firefly and PSO Methods

Harmony Search Algorithm with Dynamic Adjustment of PAR Values for Asymmetric Traveling Salesman Problem

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