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Solving and optimizing a no-wait flow-shop scheduling problem at certain execution times

Petridis Prodromos

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URI: http://purl.tuc.gr/dl/dias/3636195C-ADE3-40E8-AA8F-E53DE3DF7150
Year 2021
Type of Item Diploma Work
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Bibliographic Citation Prodromos Petridis, "Solving and optimizing a no-wait flow-shop scheduling problem at certain execution times", Diploma Work, Σχολή Μηχανικών Παραγωγής και Διοίκησης, Πολυτεχνείο Κρήτης, Chania, Greece, 2021 https://doi.org/10.26233/heallink.tuc.90395
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Summary

Within a production system, planning the production line inluences directly the flow of financial inputs. The successful implementation of scheduling is an important element to increase financial results. On the contrary, waiting for so long in a production system are a burrier to economic results. Practically, the objectives of operations scheduling are the following: the efficient utilization of machines and staff, the productive means of the production process, and the minimization of the total completion time of the order, significantly reducing the expectation of customers to satisfaction the required demand. Scheduling production in a workflow without waiting is a special case of a flowshop system, because problems are not only difficult to search but also to find the best solution for them. Thus, research applications/techniques make the appearance in the field of management planning with the widespread use of linear and nonlinear programming models. More specifically, the key factors in the problem of production scheduling are the restriction and rules that system, which is about to the capacity of the available production equipment, the requirements of production resources, human resources and inventories, the fulfillment of the requirements set by the technology concerned and the production plan data for the overall level of production. In the context of the present diplomatic work, is being actualized a specialized solution and optimization of a problem in scheduling work flow is carried out with certain lead times without waiting, through constraints relating to task precedence and minimum production rates per job. Last but not least, using the optimum number of people, they was placed based on the optimum solution in specific locations within the specified time period, which was set for the completion of the order, while offering the maximum possible performance of its use.

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