Mines de Saint-Etienne, France, invites applications for a position of PhD
Student
Research area: discrete optimization of stochastic systems.
Supervisors: Prof. Alexandre Dolgui, Dolgui@emse.fr, et Dr. Helene Marian,
marian@emse.fr (Assistant Professor)
Project description:
The Material Requirement Planning (MRP) approach is widely used in industry
for production planning and supply management. In MRP for a deterministic
environment without constraints and under a lot for lot policy, the items
are delivered just-in time (JIT). Nevertheless, under actual operating
conditions, there are always random factors, and thus, stockouts are
possible. Therefore, it is necessary to find the methods to adapt the MRP
techniques to these real world situations. Fortunately, MRP has several
parameters to configure it. An adequate choice of these parameters can fine
tune MRP to deal with a more realistic work setting. Thus, one of crucial
issues of MRP is its parameterization for real life enterprises and situations.
We have already begun to explore this problem. For Lot for Lot policy, in
(Dolgui and Louly, 2002), a Markov model was suggested. A special case of
this problem was considered in (Louly and Dolgui, 2002), when all
components have identical properties, i.e. the same lead time probability
distribution and same unit holding cost. In (Louly et al, 2008), the same
problem was considered, but for minimizing holding cost only, while
backlogging cost is replaced with a service level constraint. The formulas
obtained in (Louly and Dolgui, 2002) and (Louly et al, 2008) for optimal
planned lead times represent new generalizations of the Discrete Newsboy
model.
In this new PhD thesis we plan extends our previous results by considering
diverse lot-sizing policies and without the restrictive assumptions on the
holding costs and probability distributions. From a practical point of
view, this provides more general and comprehensive model and cost
evaluation than in the earlier work.
References
- Dolgui A., Ould Louly M.-A. (2002). A Model for Supply Planning
under Lead Time Uncertainty. International Journal of Production Economics,
78, 145-152
- Ould Louly M.-A., Dolgui A. (2002). Newsboy model for supply
planning of assembly systems. International Journal of Production Research,
40(17), 4401-4414.
- Ould Louly M.-A., A. Dolgui, and F. Hnaien, (2008). Supply planning
for single-level assembly system with stochastic component delivery times
and service level constraint, International Journal of Production
Economics, 115(1), 236-247.
Responsibilities:
The PhD position is available immediately for a duration of three years and
includes research and teaching (40 hours year). The employment is full-time
and comes with a competitive salary of 1800 euros/month. You will be given
the opportunity to present your research results at international conferences.
Qualifications:
The position requires a Master's degree (or equivalent) in Industrial
Engineering and Operations Research, or related areas. Proficiency in
English, strong team spirit, social skills, independence and a high level
of motivation for demanding research work further core qualifications.
Applications:
Inquiries and applications including a detailed CV, transcripts, a record
of attended courses (with grades), and a copy of the Master's thesis should
be addressed to: dolgui@emse.fr and marian@emse.fr or by mail to:
Prof. Dr. Alexandre Dolgui
Ecole des Mines de Saint-Etienne
158, cours Fauriel
42023 Saint-Etienne, France
URL: www.emse.fr/~dolgui
____________________________________________________________________
Alexandre Dolgui, Dr.Hab., Ph.D.
Professor
Director of the Centre for Industrial Engineering and Computer Science
Ecole des Mines de Saint-Etienne
/National Institute of Science and Technology@Saint-Etienne/
158, Cours Fauriel, 42023 Saint-Etienne cedex 2, France
Fax: +33 (0)4.77.42.66.66
E-mail: dolgui@emse.fr
URL: www.emse.fr/~dolgui
New book:
Supply Chain Engineering: Useful Methods and Techniques, Springer
http://www.springer.com/engineering/production+eng/book/978-1-84996-016-8
_____________________________________________________________________
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