An immune algorithm for hybrid flow shop scheduling problem with time lags and sequence-dependent setup times

Javadian, Nikbakhsh; Farahmand-Mehr, Mohammad; Amiri-Aref, Mehdi; Kazemi, Mohammad Reza

doi:10.1007/s00170-012-3911-z

Cited by 17 publications

(7 citation statements)

References 13 publications

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“…Hybrid Flow Shop or as known as flexible flow shop is the generalization version of the flow shop and parallel machine environments, in which the same operations can be performed by the parallel machines. Briefly describing (Javadian, et al,. 2012), HFS is a group of jobs that has to be processed on a group of processing work centers.…”

Section: Ii2 Hybrid Flow Shopmentioning

confidence: 99%

“…The proposed job sequence is as follow, 1,7,13,5,6,12,4,10,11,3,9,15,2,8,14 The makespan of existing scheduling is 67.79 hours or more than 2 days and 19 hours to produce the 2400m length of each job. While on the selected proposed scheduling the makespan is 50.42 hours to produce the same length of products per job.…”

Section: VImentioning

confidence: 99%

“…As the character of hybrid flow shop scheduling, the machine's setup time in this textile industry is consequently produced time lags for the other machines. A time lag is described as the time between the end of the processing of one job at a certain machine inside one stage and the starting point in the next stage that the job is processed (Javadian, 2012). This impact obtains the waiting time for the work-inprocess material because of the setup time and the parallel machines.…”

Section: Introduction I1mentioning

confidence: 99%

“…In many industries, the beginning of an operation at a stage has the potency of delay because the preceding operation must need time to dry or cool down. (Javadian, 2012).…”

Section: Introduction I1mentioning

confidence: 99%

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Flowshop Scheduling With Sequence Dependent Set-Up Time Using Immune Algorithm to Reduce Makespan in Pt. Xyz Bandung as a Textile Industry

Nasution¹,

Damayanti²,

Juliani³

2019

IJIES

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In manufacturing operations, production system is certainly an important aspect. Thus, company should do the planning and production control well in order to have satisfactory system. One of the production planning process is scheduling. This process is one of the main process in production planning. The urge of doing the scheduling process is due to scheduling is the details of the planning process. The production scheduling in textile industry is considered as the industry with the hybrid flow shop scheduling type. Moreover, in this company there are several machine have the characteristic of sequence dependent setup time. Thus, in order to get the optimal solution this research used Immune Algorithm. This algorithm combines an efficient mutation to cooperate the pursuit for a near-optimal solution. Keywords—Hybrid flow shops, Sequence Dependent Setup Times, Makespan, Immune Algorithm

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Section: Ii2 Hybrid Flow Shopmentioning

confidence: 99%

Section: VImentioning

confidence: 99%

Section: Introduction I1mentioning

confidence: 99%

“…In many industries, the beginning of an operation at a stage has the potency of delay because the preceding operation must need time to dry or cool down. (Javadian, 2012).…”

Section: Introduction I1mentioning

confidence: 99%

See 2 more Smart Citations

Flowshop Scheduling With Sequence Dependent Set-Up Time Using Immune Algorithm to Reduce Makespan in Pt. Xyz Bandung as a Textile Industry

Nasution¹,

Damayanti²,

Juliani³

2019

IJIES

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“…Ruiz and Maroto [15] proposed a genetic algorithm for SDST hybrid flow shop with machine eligibility, where they conducted an extensive calibration of the different parameters and operators by means of experimental designs. Javadian et al [8] proposed a mathematical model and an immune algorithm for SDST hybrid flow shop with time lags. In their paper setup time was anticipatory and time lag and setup time occur simultaneously.…”

Section: Literature Reviewmentioning

confidence: 99%

An efficient genetic algorithm for a hybrid flow shop scheduling problem with time lags and sequence-dependent setup time

et al. 2014

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In this paper, a hybrid flow shop scheduling problem with a new approach considering time lags and sequence-dependent setup time in realistic situations is presented. Since few works have been implemented in this field, the necessity of finding better solutions is a motivation to extend heuristic or meta-heuristic algorithms. This type of production system is found in industries such as food processing, chemical, textile, metallurgical, printed circuit board, and automobile manufacturing. A mixed integer linear programming (MILP) model is proposed to minimize the makespan. Since this problem is known as NP-Hard class, a meta-heuristic algorithm, named Genetic Algorithm (GA), and three heuristic algorithms (Johnson, SPTCH and Palmer) are proposed. Numerical experiments of different sizes are implemented to evaluate the performance of presented mathematical programming model and the designed GA in compare to heuristic algorithms and a benchmark algorithm. Computational results indicate that the designed GA can produce near optimal solutions in a short computational time for different size problems.

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Metaheuristics for Solving a Hybrid Flexible Flowshop Problem with Sequence-Dependent Setup Times

Sioud

Gagné

Gravel

2014

Swarm Intelligence Based Optimization

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An immune algorithm for hybrid flow shop scheduling problem with time lags and sequence-dependent setup times

Cited by 17 publications

References 13 publications

Flowshop Scheduling With Sequence Dependent Set-Up Time Using Immune Algorithm to Reduce Makespan in Pt. Xyz Bandung as a Textile Industry

Flowshop Scheduling With Sequence Dependent Set-Up Time Using Immune Algorithm to Reduce Makespan in Pt. Xyz Bandung as a Textile Industry

An efficient genetic algorithm for a hybrid flow shop scheduling problem with time lags and sequence-dependent setup time

Metaheuristics for Solving a Hybrid Flexible Flowshop Problem with Sequence-Dependent Setup Times

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