Setup-oriented dispatching rules – a survey

Pickardt, Christoph W.; Branke, Jürgen

doi:10.1080/00207543.2011.629634

Cited by 34 publications

(27 citation statements)

References 41 publications

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“…For example, SPTNS has been reported in Jacobs and Bragg (1988) to outperform the SPT rule in respect to minimization of flow time, a result which contradicts those of Vinod and Sridharan (2008) and Wemmerlov (1992). Finally, note that two rules which are included in this study (SPSU & CRNS) have been shortlisted in a comprehensive survey of setup-oriented priority rules (Pickardt & Branke, 2012) as more promising candidates among other alternatives.…”

Section: Related Workmentioning

confidence: 89%

Efficient priority rules for dynamic sequencing with sequence-dependent setups

Xanthopoulos¹,

Koulouriotis²,

Γαστεράτος³

et al. 2016

10.5267/j.ijiec

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This article addresses the problem of dynamic sequencing on n identical parallel machines with stochastic arrivals, processing times, due dates and sequence-dependent setups. The system operates under a completely reactive scheduling policy and the sequence of jobs is determined with the use of dispatching rules. Seventeen existing dispatching rules are considered including standard and setup-oriented rules. The performance of the system is evaluated by four metrics. An experimental study of the system is conducted where the effect of categorical and continuous system parameters on the objective functions is examined. In light of the results from the simulation experiments, a parameterized priority rule is introduced and tested. The simulation output is analyzed using rigorous statistical methods and the proposed rule is found to produce significantly better results regarding the metrics of mean cycle time and mean tardiness in single machine cases. In respect to three machine cases, the proposed rule matches the performance of the best rule from the set of existing rules which were studied in this research for three metrics.

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Section: Related Workmentioning

confidence: 89%

Efficient priority rules for dynamic sequencing with sequence-dependent setups

Xanthopoulos¹,

Koulouriotis²,

Γαστεράτος³

et al. 2016

10.5267/j.ijiec

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show abstract

“…A recent overview is given by Pickardt and Branke (2011). Their findings show that the ATCS rule (Lee, Bhaskaran and Pinedo, 1997) performs well, especially if the objective function is tardiness related.…”

Section: Scheduling With Setup-oriented Dispatching Rulesmentioning

confidence: 99%

“…As an alternative to switching rules, we can use composite rules that have an integrated term for setup avoidance. These are usually based on common dispatching rules that have proven to be effective on flow time-or tardiness-related performance criteria (Pickardt and Branke, 2011). The ATCS rule is one of the most effective rules with respect to mean tardiness and considers the slack (time until due date minus remaining processing time of the job) and the setup avoidance separately.…”

Section: Dispatching Rulesmentioning

confidence: 99%

“…In this paper, we present a simulation study of a flow-shop scenario with sequence-dependent setup times. We have selected the ATCS (Apparent Tardiness Cost with Setups) (Lee, Bhaskaran and Pinedo, 1997) rule since it performs well in scenarios with sequence-dependent setup times (Pickardt and Branke, 2011). ATCS is a combination of three different basic rules: WSPT (weighted shortest processing time), a minimum slack rule as well as the minimum setup time rule.…”

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confidence: 99%

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Dynamic adjustment of dispatching rule parameters in flow shops with sequence-dependent set-up times

Heger

Branke

Hildebrandt

et al. 2016

International Journal of Production Research

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Decentralized scheduling with dispatching rules is applied in many fields of production and logistics, especially in highly complex manufacturing systems. Since dispatching rules are restricted to their local information horizon, there is no rule that outperforms other rules across various objectives, scenarios and system conditions. In this paper, we present an approach to dynamically adjust the parameters of a dispatching rule depending on the current system conditions. The influence of different parameter settings of the chosen rule on system performance is estimated by a machine learning method, whose learning data is generated by preliminary simulation runs. Using a dynamic flow shop scenario with sequence dependent setup times, we demonstrate that our approach is capable of significantly reducing the mean tardiness of jobs.

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“…In past years, family-based dispatching heuristics received significant attention in literature (Pickardt and Branke 2012). However, most studies consider the development of myopic heuristics that restrict decision scope to a single manufacturing stage, and rely on local information for underpinning dispatching decisions.…”

Section: Introductionmentioning

confidence: 99%

Coordinating batching decisions in manufacturing networks

Zee

2017

International Journal of Production Research

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Family-based dispatching heuristics aim for improving job flow times by reducing time spent on set-ups. They realise set-up efficiencies by batching similar types of jobs. By their intuitiveness and the simplicity of their decision logic, they may contribute to an easy to implement and viable strategy in many practical settings. Similar to common dispatching rules most existing family-based dispatching heuristics are myopic, i.e. their decision scope is restricted to a single manufacturing stage. Hence, they neglect opportunities for improving shop performance by coordinating batching decisions with other manufacturing stages. Case examples from industry underpin the need for exploring these opportunities. We do so by studying a simple two-stage flow shop, entailing a serial and a batch stage. To facilitate shop coordination we propose extensions to existing family-based dispatching heuristics. Extended heuristics seek to further increase set-up efficiencies by allowing for upstream job re-sequencing, and pro-active set-ups, i.e. set-ups that may be initiated prior to the arrival of a job. Outcomes of an extensive simulation study indicate significant performance gains for extended heuristics vs. existing heuristics. Performance gains are largest for moderate and high set-up to run-time ratios.

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Setup-oriented dispatching rules – a survey

Cited by 34 publications

References 41 publications

Efficient priority rules for dynamic sequencing with sequence-dependent setups

Efficient priority rules for dynamic sequencing with sequence-dependent setups

Dynamic adjustment of dispatching rule parameters in flow shops with sequence-dependent set-up times

Coordinating batching decisions in manufacturing networks

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