A scheduling algorithm for the reentrant shop: an application in semiconductor manufacture

Kang, Y.M.; Kim, Sung-Shick; Shin, Hyun Joon

doi:10.1007/s00170-006-0736-7

Cited by 25 publications

(12 citation statements)

References 17 publications

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“…The sum of the total tardiness is minimized in many studies such as by Kang et al [13] where a reentrant flow shop problem is solved with a three phases algorithm. The same is found in the work of Mönch et al [22] where a genetic algorithm is applied to subproblems of the initial parallel reentrant problem with setup and batch production.…”

Section: Contextmentioning

confidence: 99%

New multi-objective method to solve reentrant hybrid flow shop scheduling problem

Dugardin

Yalaoui

Amodeo

2010

European Journal of Operational Research

134

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Section: Contextmentioning

confidence: 99%

New multi-objective method to solve reentrant hybrid flow shop scheduling problem

Dugardin

Yalaoui

Amodeo

2010

European Journal of Operational Research

134

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“…Park, Kim, and Jun (2000) estimated the average performance which comprised the cycle time and the throughput of the RFS with single-job machines and batch machines by developing an approximate method based on the mean value analysis. Kang, Kim, and Shin (2007) proposed a heuristic algorithm that minimises total weighted tardiness for RFS problems with sequence dependent set-up time. Abe and Ida (2008) studied minimising turnaround time of a RFS scheduling problem by genetic local search methods that are more valid than other methods such as swap, move, and swap-2 neighbourhood.…”

Section: Literature Reviewmentioning

confidence: 99%

Re-entrant flow shop scheduling problem with time windows using hybrid genetic algorithm based on auto-tuning strategy

Chamnanlor

Sethanan

Chien

et al. 2013

International Journal of Production Research

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The re-entrant flow shop scheduling problem considering time windows constraint is one of the most important problems in hard-disc drive (HDD) manufacturing systems. In order to maximise the system throughput, the problem of minimising the makespan with zero loss is considered. In this paper, evolutionary techniques are proposed to solve the complex re-entrant scheduling problem with time windows constraint in manufacturing HDD devices with lot size. This problem can be formulated as a deterministic Fm | fmls, rcrc, temp | C max problem. A hybrid genetic algorithm was used for constructing chromosomes by checking and repairing time window constraints, and improving chromosomes by a left-shift heuristic as a local search algorithm. An adaptive hybrid genetic algorithm was eventually developed to solve this problem by using fuzzy logic control in order to enhance the search ability of the genetic algorithm. Finally, numerical experiments were carried out to demonstrate the efficiency of the developed approaches.

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“…For re-entrant lines, the earliness/tardiness scheduling problem has also attracted much attention. For example, Kang et al (2007) addressed a heuristic policy that minimises total weighted tardiness for a re-entrant shop, which consists of three phases: the prior plan phase, the initial solution generation phase and the solution improvement phase. This policy gives very efficient schedules in terms of total weighted tardiness.…”

Section: Literature Reviewmentioning

confidence: 99%

A two-layer dynamic scheduling method for minimising the earliness and tardiness of a re-entrant production line

Yan

Wang

2012

International Journal of Production Research

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This study focuses on the dynamic scheduling problem of a re-entrant production line, in which all of the parts are assumed to have the same processing routes and be processed on every machine. A two-layer dynamic scheduling method is proposed for the dynamic scheduling of the re-entrant line with the objective of minimising total earliness and tardiness. This method consists of two layers. The top layer is to select the appropriate scheduling policy, and the bottom layer is to generate the scheduling by using the policy selected in the top layer. In the top layer, three different rules are constructed for selecting scheduling policies, namely the lateness comparison rule, the lateness variation comparison rule, and the equal interval switching rule. In the bottom layer, three different scheduling policies are proposed to generate the real-time scheduling for manufacturing, namely the FCFS (first come first service) scheduling policy, the PI (proportional-integral) scheduling policy, and the fuzzy PI scheduling policy. Considering that the real-time status of manufacturing changes constantly, it is necessary to switch among different scheduling policies to adapt to this change. Numerical experiments are performed in the situations with and without urgent jobs. The results show that the proposed two-layer dynamic scheduling method outperforms any single scheduling policy (e.g., the FCFS policy, the PI policy and the fuzzy PI policy) for the dynamic scheduling of a re-entrant production line.

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A scheduling algorithm for the reentrant shop: an application in semiconductor manufacture

Cited by 25 publications

References 17 publications

New multi-objective method to solve reentrant hybrid flow shop scheduling problem

New multi-objective method to solve reentrant hybrid flow shop scheduling problem

Re-entrant flow shop scheduling problem with time windows using hybrid genetic algorithm based on auto-tuning strategy

A two-layer dynamic scheduling method for minimising the earliness and tardiness of a re-entrant production line

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