An Improved Shuffled Frog Leaping Algorithm for Assembly Sequence Planning of Remote Handling Maintenance in Radioactive Environment

Guo, Jianwen; Tang, Hong Mei; Sun, Zhuo; Wang, Song; Jia, Xuejun; Chen, Haibin; Zhang, Zhicong

doi:10.1155/2015/516470

Cited by 6 publications

(6 citation statements)

References 53 publications

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“…Up to now, many researchers have focused on different traditional algorithms to obtain the optimal solution for ASP problem. Researchers [12][13][14][15] have applied new emerging algorithms like breakout local search (BLS), frog leaping algorithm (FLA), gravitational search algorithm (GSA) and imperialist competitive algorithm (ICA) to solve ASP problem for achieving the optimal solution. In these, BLS algorithm is a recent development to solve complex engineering optimization problems.…”

Section: New Emerging Algorithmsmentioning

confidence: 99%

See 1 more Smart Citation

Assembly sequence planning using soft computing methods: A review

Deepak

Murali

Bahubalendruni³

et al. 2018

Proceedings of the Institution of Mechanical Engineers, Part E:

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The implementation of artificial intelligence techniques is increasing rapidly in recent years to solve numerous engineering problems. Assembly sequence planning is one of the prominent complex combinatorial problem draw attention of industrial engineers to economize the overall manufacturing cost by minimizing the assembly time and energy. Due to large search space and multiple assembly predicate criteria, researchers are motivated towards efficient utilization of AI techniques to address the problem. Literature review on various artificial intelligence techniques for obtaining the optimal assembly sequence planning are analyzed and the limitations of the existed methodologies are discussed in detail. This review provides an outlook for the researchers on various artificial intell1igent techniques which will be useful to carry out research for obtaining the optimum assembly sequence planning while qualifying various assembly predicate criteria.

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Section: New Emerging Algorithmsmentioning

confidence: 99%

“…Many AI techniques are used by the researchers, but most of them failed to achieve global optimum feasible assembly sequence because of premature convergence at local optimum solution. The recent AI techniques [12][13][14][15] attracted the engineers to solve ASP efficiently due to their flexibility in implementation.…”

Section: Introductionmentioning

confidence: 99%

Assembly sequence planning using soft computing methods: A review

Deepak

Murali

Bahubalendruni³

et al. 2018

Proceedings of the Institution of Mechanical Engineers, Part E:

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“…Various researchers are currently actively searching for solutions to this problem using artificial intelligence algorithms. For example, Guo et al [13] proposed an approach based on the shuffled frog leaping algorithm to optimise the ASP of maintenance activities in radioactive environments. In their proposed approach, the geometrical feasibility of the assembly sequences is tested with the help of interference matrices along six axes.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimum Assembly Sequence Planning System Using Discrete Artificial Bee Colony Algorithm

Özmen

Batbat

Özen

et al. 2018

Mathematical Problems in Engineering

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Assembly refers both to the process of combining parts to create a structure and to the product resulting therefrom. The complexity of this process increases with the number of pieces in the assembly. This paper presents the assembly planning system design (APSD) program, a computer program developed based on a matrix-based approach and the discrete artificial bee colony (DABC) algorithm, which determines the optimum assembly sequence among numerous feasible assembly sequences (FAS). Specifically, the assembly sequences of three-dimensional (3D) parts prepared in the computer-aided design (CAD) software AutoCAD are first coded using the matrix-based methodology and the resulting FAS are assessed and the optimum assembly sequence is selected according to the assembly time optimisation criterion using DABC. The results of comparison of the performance of the proposed method with other methods proposed in the literature verify its superiority in finding the sequence with the lowest overall time. Further, examination of the results of application of APSD to assemblies consisting of parts in different numbers and shapes shows that it can select the optimum sequence from among hundreds of FAS.

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“…Li et al ( 2012 ) proposed a hybrid shuffled frog leaping algorithm (HSFLA) with a designed crossover operator for solving the multi-objective flexible job shop scheduling problem. Guo et al ( 2015 ) proposed an improved shuffled frog leaping algorithm (SFLA) for the combinatorial optimisation problem of an assembly sequence planning (ASP). Under a remote handling maintenance in radioactive environment the improved SFLA was compared with the SFLA, genetic algorithm, particle swarm optimisation, and adaptive mutation particle swarm optimisation in terms of efficiency and capability of locating the best global assembly sequence.…”

Section: Vertical Transportation Systemsmentioning

confidence: 99%

Vertical transportation systems embedded on shuffled frog leaping algorithm for manufacturing optimisation problems in industries

Aungkulanon

Luangpaiboon

2016

SpringerPlus

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Response surface methods via the first or second order models are important in manufacturing processes. This study, however, proposes different structured mechanisms of the vertical transportation systems or VTS embedded on a shuffled frog leaping-based approach. There are three VTS scenarios, a motion reaching a normal operating velocity, and both reaching and not reaching transitional motion. These variants were performed to simultaneously inspect multiple responses affected by machining parameters in multi-pass turning processes. The numerical results of two machining optimisation problems demonstrated the high performance measures of the proposed methods, when compared to other optimisation algorithms for an actual deep cut design.

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An Improved Shuffled Frog Leaping Algorithm for Assembly Sequence Planning of Remote Handling Maintenance in Radioactive Environment

Cited by 6 publications

References 53 publications

Assembly sequence planning using soft computing methods: A review

Assembly sequence planning using soft computing methods: A review

Optimum Assembly Sequence Planning System Using Discrete Artificial Bee Colony Algorithm

Vertical transportation systems embedded on shuffled frog leaping algorithm for manufacturing optimisation problems in industries

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