Batch Scheduling In A Two-Stage Flexible Flow Shop Problem

Gerstl, Enrique; Sarig, Assaf

doi:10.2478/fcds-2014-0001

Cited by 11 publications

(4 citation statements)

References 25 publications

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“…The processingflowisisolatedintonumerousstages,andtherearenumerousparallelmachinesto handleoccupationsineachstage.Duetothehugevolumeofthebusesandthelonggeneration cycle,asitwerebufferswithalimitednumberofspacescanbeconveyedwithinthegeneration line.Atthesametime,thetransportisn'tequippedwithachassisforbeginningthemotorwithin theinstallationworkshop,andtheycanasitwerebecarriedontheskids.Inthismanner,there's ordinarilyabufferbetweenthebodyshopandpaintshop,andthebufferisusuallyisolatedinto differentpathsfortheeaseofplanningandoperation (Ahmadetal.,2019).Eachpathhasan equalnumberofspacesforthetransportbodies.Thetransportentersthepathfromoneside andexitsthepathfromtheotherside.Theflexibleflow-shopschedulingproblem(FFSP)isa kindofclassicalNP-hardproblem (Khamseh,Jolai&Babaei,2015).Thelimitedbufferflexible flow shop scheduling problem (LBFFSP) is a kind of derivative problem of the FFSP and it has stimulated the focus of a huge number of researchers. Gerstl, Mosheiov & Sarig (2014) assumedthebufferbetweenthestagesisinfiniteintheclassicalFFSP.However,confinedby theequipment,spacecapacityofthebufferandotherfactors,themiddlebufferisusuallylimited andevendoesn'texistinlotsofactualproductionprocessesiniron,chemicalandpharmaceutical industries.Forthisreason,thestudyofLBFFSPhasimportanttheoreticalandpracticalvalue. Wardono&Fathi(2004)usedheuristicalgorithmtosolvetheFFSPofmulti-processparallel machineconstrainedbybuffer,butthissolutioncanonlybeusedtosolvetheproblemofsmaller scale.…”

Section: Introductionmentioning

confidence: 99%

Application Research of IICA Algorithm in a Limited-Buffer Scheduling Problem

Duan

Jiang

2022

International Journal of E-Collaboration

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An improved imperialist competition algorithm (IICA) was proposed to resolve the problem of flexible flow shop scheduling that with limited buffer (LBFFSP). The IICA algorithm adds the elite personal retention strategy, reform operation and the discrete processing on the basis of ICA algorithm. This paper uses an individual selection mechanism based on Hamming distance to improve the ability of initial solution. The prospect is to use the IICA to work out related problems in cloud computing environment. The scheduling problem in the cloud-computing environment needs to consider the optimization of the completion time and cost of using cloud resources. At last, simulation tests and example tests are used to check the usefulness of improved imperialist competition algorithm in solving LBFFSP problem. Compared with standard ICA, the improved ICA has improved in the algorithm evolution process. As such, scheme 4 has a better ability to evolve, and its evolution time is greater than that of scheme 3. Scheme 5 has the best algorithm optimization performance.

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Section: Introductionmentioning

confidence: 99%

Application Research of IICA Algorithm in a Limited-Buffer Scheduling Problem

Duan

Jiang

2022

International Journal of E-Collaboration

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“…The flexible flow-shop scheduling problem (FFSP) is an extension of the traditional flow shop scheduling problem, which has been proved to be an NP-hard problem [1][2][3][4], and LBFFSP has also received more and more attention in recent years. In the traditional FFSP, the buffer between each process is assumed to be infinite.…”

Section: Introductionmentioning

confidence: 99%

Research on the Improved Dragonfly Algorithm-Based Flexible Flow-Shop Scheduling

Han

Zhang

Shao

2019

Proceedings of the 11th International Conference on Modelling, Identification and Control (ICMIC2019)

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Compared with the classic flexible flow shop, limited buffer flexible flow shop may have a limited buffer production blockage, which will increase the complexity and uncertainty of the scheduling process. In order to solve the limited-buffer flexible flow-shop scheduling problem (LBFFSP), a mathematical programming model of limited buffer flexible flow shop is established and an Improved Dragonfly Algorithm (IDA) is proposed to solves this problem. Based on the standard Dragonfly Algorithm (DA), the idea of Simulated Anneal (SA) is combined to improve the ability of the algorithm to jump out local extremum and the algorithm combines the standard Dragonfly Algorithm (DA) with the Simulated Anneal (SA) idea to improve the ability to jump out local extremum and improve its persistence.

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“…With rapid development of information, advanced manufacturing, and artificial intelligence technology, Germany proposed "Industry 4.0" national strategy, which promotes progress in manufacturing industry and provides producing solution schemes for many complex industrial systems [1][2][3]. In the production of steel casting, assembly of heavy machinery, and other industries, a scheduling problem with non-deterministic polynomial hard (NP-hard) attributes [4][5][6][7][8], such as the flexible flow shop scheduling problem with the characteristics of customized production and parallel processing, was experienced [9,10]. During the actual production of the large equipment manufacturing workshop, only the buffer with limited capacity can be set in the workshop, owing to physical factors such as the workshop space and storage equipment capacity.…”

Section: Introductionmentioning

confidence: 99%

Flexible Flow Shop Scheduling Method with Public Buffer

Han

Shao

et al. 2019

Processes

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Actual manufacturing enterprises usually solve the production blockage problem by increasing the public buffer. However, the increase of the public buffer makes the flexible flow shop scheduling rather challenging. In order to solve the flexible flow shop scheduling problem with public buffer (FFSP–PB), this study proposes a novel method combining the simulated annealing algorithm-based Hopfield neural network algorithm (SAA–HNN) and local scheduling rules. The SAA–HNN algorithm is used as the global optimization method, and constructs the energy function of FFSP–PB to apply its asymptotically stable characteristic. Due to the limitations, such as small search range and high probability of falling into local extremum, this algorithm introduces the simulated annealing algorithm idea such that the algorithm is able to accept poor fitness solution and further expand its search scope during asymptotic convergence. In the process of local scheduling, considering the transferring time of workpieces moving into and out of public buffer and the manufacturing state of workpieces in the production process, this study designed serval local scheduling rules to control the moving process of the workpieces between the public buffer and the limited buffer between the stages. These local scheduling rules can also be used to reduce the production blockage and improve the efficiency of the workpiece transfer. Evaluated by the groups of simulation schemes with the actual production data of one bus manufacturing enterprise, the proposed method outperforms other methods in terms of searching efficiency and optimization target.

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Batch Scheduling In A Two-Stage Flexible Flow Shop Problem

Cited by 11 publications

References 25 publications

Application Research of IICA Algorithm in a Limited-Buffer Scheduling Problem

Application Research of IICA Algorithm in a Limited-Buffer Scheduling Problem

Research on the Improved Dragonfly Algorithm-Based Flexible Flow-Shop Scheduling

Flexible Flow Shop Scheduling Method with Public Buffer

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