A memetic algorithm for solving flexible Job-Shop Scheduling Problems

Ma, Wenping; Zuo, Yi; Zeng, Jiulin; Liang, Shuang; Jiao, Licheng

doi:10.1109/cec.2014.6900332

Cited by 9 publications

(3 citation statements)

References 19 publications

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“…The results show that the results obtained by MA are better (Yuan, & Xu, 2015). The MA algorithm proposed by Ma et al introduces two efficient local searchers on the basis of GA to increase the local search ability (Ma, Zuo, Zeng, Liang, & Jiao, 2014).…”

Section: An Improved Memetic Algorithmmentioning

confidence: 95%

Consensus aware manufacturing service collaboration optimization under blockchain based Industrial Internet platform

Zhang

Tao

et al. 2019

Computers & Industrial Engineering

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To realize collaboration among distributed enterprises, manufacturing service collaboration on Industrial Internet platform is an efficient method. However, the low degree of participation resulted by the sense of distrust, dissatisfaction, and insecurity hinders the widely application of Industrial Internet platform. Therefore, a secure, trustworthy, and multi-user satisfied manufacturing service collaboration method is in urgent need. A blockchain based platform could be utilized to support collaboration among distributed participants to complete trustworthy transactions. In addition, in order to satisfy multiple users, there should be a suitable collaboration mechanism that allows interest-independent participants to fulfil their short/long-term expectations and guide them to a consensus. Based on the establishment of the underlying data and network layer of the blockchain, the collaboration optimization of manufacturing services based on consensus is proposed. By utilizing Memetic algorithm, both the long-term utility of providers and the short-term utility of consumers are combined to choose the optimal providers for the tasks. The providers are selected with higher satisfaction degree of consumers.

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Section: An Improved Memetic Algorithmmentioning

confidence: 95%

Consensus aware manufacturing service collaboration optimization under blockchain based Industrial Internet platform

Zhang

Tao

et al. 2019

Computers & Industrial Engineering

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“…In their proposed algorithm, some simple local search methods are used to balance exploration and exploitation. Ma et al [83] proposed a memetic algorithm (MA) to solve the FJSP. The MA is a hybrid GA combined with two efficient local searches to exploit information in the search region.…”

Section: Population-based Meta-heuristicsmentioning

confidence: 99%

Review on flexible job shop scheduling

Xie

Gao

Peng

et al. 2019

IET Collaborative Intelligent Manufacturing

144

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Flexible job shop scheduling problem (FJSP) is an NP‐hard combinatorial optimisation problem, which has significant applications in the real world. Due to its complexity and significance, lots of attentions have been paid to tackle this problem. In this study, the existing solution methods for the FJSP in recent literature are classified into exact algorithms, heuristics and meta‐heuristics, which are reviewed comprehensively. Moreover, the real‐world applications of the FJSP are also introduced. Finally, the development trends of the manufacturing industry are analysed, and the future research opportunities of the FJSP are summarised in detail.

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“…Traditional approaches for resolution of the FJSSP are as varied as the different formulations of the problem. They include fast, simple heuristics, taboo search (Liouane et al., ), evolutionary approaches (Gu et al., ; Zhang et al., ; Ma et al., a; Ma et al., b; Yuan and Xu, ; Zheng et al., ), Monte‐Carlo Tree Search (Wu et al., ), simulated annealing (SA) (Shivasankaran et al., ), and modern hybrid metaheuristics that consolidate the advantages of different approaches (Zhou et al., ). The FJSSP is an extension of classic JSSP, and incorporates all the difficulties and complexities of this problem (Mastrolilli and Gambardella, ; Kacem et al., , ; Ho and Tay, ; Chen and Chen, ; Amiri et al., ; Mati et al., ; Knopp et al., ).…”

Section: Introductionmentioning

confidence: 99%

Accelerated simulated annealing algorithm applied to the flexible job shop scheduling problem

Cruz-Chávez

Martínez-Rangel

Cruz-Rosales

2015

Int Trans Operational Res

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This paper presents a simulated annealing algorithm accelerated by a partial scheduling mechanism and a cooling schedule mechanism that is a function of the standard deviation. This facilitates a rapid approach to good solutions in the flexible job shop scheduling problem (FJSSP). The results demonstrate that for benchmark instances of several sizes, simulated annealing that implements the proposed mechanism converges more quickly to good solutions than simulated annealing that does not implement the proposed mechanism.

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A memetic algorithm for solving flexible Job-Shop Scheduling Problems

Cited by 9 publications

References 19 publications

Consensus aware manufacturing service collaboration optimization under blockchain based Industrial Internet platform

Consensus aware manufacturing service collaboration optimization under blockchain based Industrial Internet platform

Review on flexible job shop scheduling

Accelerated simulated annealing algorithm applied to the flexible job shop scheduling problem

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