Simulation modeling and analysis of due-date assignment methods and scheduling decision rules in a dynamic job shop production system

Vinod, V.V.; Sridharan, R.

doi:10.1016/j.ijpe.2010.08.017

Cited by 124 publications

(54 citation statements)

References 47 publications

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“…They considered the problem of determining optimum due dates and processing sequence concurrently to minimize costs of earliness, due date assignment and weighted number of tardy jobs. (Vinod & Sridharan, 2011) studied due date assignment rules and scheduling methods in a dynamic job shop environment. As a due date assignment method they used PWW, TWK, DTWK (Dynamic Total Work Content), RWK (Random Work Content) and as a scheduling rules they used seven different types of rules.…”

Section: Background and Related Researchesmentioning

confidence: 99%

Process Planning and Scheduling With PPW Due-Date Assignment Using Hybrid Search

Demir

Çakar

İpek

et al. 2017

Mijst

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Section: Background and Related Researchesmentioning

confidence: 99%

Process Planning and Scheduling With PPW Due-Date Assignment Using Hybrid Search

Demir

Çakar

İpek

et al. 2017

Mijst

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“…Its major advantage is that it does not consume material, energy and resources, it only requires data. Thus, different variants of production are tested in advance as we search for an optimal solution [10,11].  Tabu-search (TS), which is one of the most commonly used metaheuristics in combinatorial optimization problems.…”

Section:  Departure Of the Ordersmentioning

confidence: 99%

Hybrid Algorithm Based on Priority Rules for Simulation of Workshop Production

Zupan¹,

Herakovič²,

Starbek³

2016

Int. j. simul. model.

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The proposed hybrid algorithm is a combination of heuristic algorithm extended with priority rules, discrete event simulation and genetics algorithm. It takes into account 11 different priority rules and scenarios, is based on the assumption that for a realistic workshop scheduling of orders, it is necessary to consider real throughput times of the operations, otherwise the obtained scheduling of orders is not suitable for the industrial environment. The simulation result for the proposed model is the optimal sequence of selected orders for the selected time interval while taking into account three criteria: the minimum flow time of all orders, the maximum average utilization of workplaces, and the minimum waiting time of the orders. Because the mentioned criteria are usually mutually exclusive the advantage of the proposed model is that we can find the optimum with respect to all three criteria. In the paper, an example of the application of the proposed model is shown.

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“…Moreover, the calculation of due dates in ETO environments is relatively mistreated. Most studies focus on static problem instances where jobs do not arrive continuously in the system [46], or require significant modelling efforts [53] and simulation experiments [54], which are rarely feasible in actual daily practice for due-date calculation.…”

Section: Order Due-date Assignmentmentioning

confidence: 99%

A mobile application for knowledge-enriched short-term scheduling of complex products

2016

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The ever-increasing product complexity, especially for the case of engineer-to-order products, highly affects the performance of manufacturing systems. Therefore, a high degree of flexibility is needed during daily decision-making activities, such as production scheduling. For addressing this challenge, this research work proposes a knowledge-enriched short-term job-shop scheduling mechanism, which is implemented into a mobile application. More precisely, it focuses on the short-term scheduling of the resources of the machine shop, through an intelligent algorithm that generates and evaluates alternative assignments of resources to tasks. Based on the requirements of a new order, a similarity mechanism retrieves successfully executed past orders together with a dataset that includes the processing times, the job and task sequence, and the suitable resources. In addition to that, the similarity mechanism is used to calculate the due-date assignments of the orders based on the knowledge stored in past cases. Afterwards, it adapts these parameters to the requirements of the new order so as to evaluate the alternative schedules and identify a good alternative in a timely manner. The deriving schedule can be presented on mobile devices, and it can be manipulated by the planner on-thefly respecting tasks precedence constraints and machine availability. A case study from the mould-making industry is used for validating the proposed method and application.

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Simulation modeling and analysis of due-date assignment methods and scheduling decision rules in a dynamic job shop production system

Cited by 124 publications

References 47 publications

Process Planning and Scheduling With PPW Due-Date Assignment Using Hybrid Search

Process Planning and Scheduling With PPW Due-Date Assignment Using Hybrid Search

Hybrid Algorithm Based on Priority Rules for Simulation of Workshop Production

A mobile application for knowledge-enriched short-term scheduling of complex products

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