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Bi-objective optimisation approaches to Job-shop problem with power requirements

Autor: Damien Lamy, Matthieu Gondran, Nikolay Tchernev, S. Kemmoe

Publikováno v: Expert Systems with Applications
Expert Systems with Applications, Elsevier, 2020, 162, pp.113753. ⟨10.1016/j.eswa.2020.113753⟩
Expert Systems with Applications, 2020, 162, pp.113753. ⟨10.1016/j.eswa.2020.113753⟩

International audience; Nowadays, a large focus is given to mass personalisation, and multiple path shop floors are suited to such production environments. Hence, this paper deals with the Job-shop scheduling problem that is used for modelling a manu

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d1613711970b963459602ba88fc94b91
https://hal.archives-ouvertes.fr/hal-03003304

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A GRASP embedding a bi-level ELS for solving Flexible Job-shop Problems

Autor: Damien Lamy, S. Kemmoe, Nikolay Tchernev

Publikováno v: IFAC-PapersOnLine. 49:1749-1754

In this paper, an evolution of the GRASPxELS for the Flexible Job-shop problem is proposed, resulting in a GRASP with a bi-level ELS paradigm. As ELS is based on neighborhood search, a random neighborhood is developed, including two different neighbo

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::4ffff6a3fb387e77cc791ee3b8132ccc
https://doi.org/10.1016/j.ifacol.2016.07.835

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A Job-shop with an Energy Threshold Issue Considering Operations with Consumption Peaks

Autor: Damien Lamy, S. Kemmoe, Nikolay Tchernev

Publikováno v: IFAC-PapersOnLine. 48:788-793

In this paper the Job-shop problem is addressed as a support for a manufacturing system scheduling considering an energy consumption threshold that must not be exceeded. It is considered that an operation may consume a lot of energy at the beginning

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::8162fd48bb9258314e3ea9133b5f450c
https://doi.org/10.1016/j.ifacol.2015.06.179

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Job-shop like manufacturing system with variable power threshold and operations with power requirements

Autor: Nikolay Tchernev, Damien Lamy, S. Kemmoe

Publikováno v: International Journal of Production Research
International Journal of Production Research, Taylor & Francis, 2017, 55 (20), pp.6011-6032. ⟨10.1080/00207543.2017.1321801⟩
International Journal of Production Research, 2017, 55 (20), pp.6011-6032. ⟨10.1080/00207543.2017.1321801⟩

This paper addresses an important issue in manufacturing by considering the scheduling of a Job-shop like manufacturing system involving a power threshold that must not be exceeded over time. A power profile is attached to operations that must be sch

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c92527546fa763ba253109e967d0f0c5
https://hal.archives-ouvertes.fr/hal-03003290

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Model for flexibility evaluation in manufacturing network strategic planning

Autor: Pierre-Alban Pernot, Nikolay Tchernev, S. Kemmoe

Publikováno v: International Journal of Production Research. 52:4396-4411

In response to market pressures, manufacturers have adopted different approaches to provide flexibility regarding several aspects. In this paper, we suggest a model for the evaluation of the flexibility of the manufacturing supply chain, based on gra

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::48d2649d4212c410a87a8c0452cf2d7c
https://doi.org/10.1080/00207543.2013.845703

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A GRASP for supply chain optimization with financial constraints per production unit

Autor: Alain Quilliot, S. Kemmoe, Nikolay Tchernev, Philippe Lacomme

Publikováno v: MIC 2011
MIC 2011, 2011, Udine, Italy
Operations Research/Computer Science Interfaces Series ISBN: 9781461463214
HAL

This paper deals with supply chain optimization using the job-shop model where extra flow constraints are included modelizing cash flow exchanges between different supply chain partners including suppliers, retailers and manufacturers. The problem un

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4f6dc419c09ce4abc69774ccdec473eb
https://hal.science/hal-02081964

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