"Combinatorial problems of production systems optimization under uncertainty"
Supervisors: Pr. André Rossi, Pr. Alexandre Dolgui and Dr. Evgeny Gurevsky
This postdoctoral fellowship is a part of the ADLACI project, funded
by the "RFI AtlanSTIC 2020" program of the french region "Pays de la
Loire", and dedicated to the optimal design of production systems
The design of production systems is an important industrial challenge
that includes several issues dealing with optimization aspects, named
in the literature as balancing problems. In general (see, for example,
the survey Scholl and Becker, 2006), they consist in a partition of
the set of all necessary production tasks among machines (or
workstations) with respect to a given production goal and subject to
some technological restrictions such as precedence, cycle time,
exclusion, inclusion or space constraints. One of the important goals
at the production systems design stage is the anticipation of the
task time variability in order to construct a robust system
configuration for a long term usage.
Since 2012 (see Gurevsky et al., 2012, 2013; Rossi et al. 2016), we
study and popularize an alternative robust approach for evaluating
production systems in such a situation. This approach is based on a
specific indicator, called as the stability radius. Given a feasible
production system configuration with already assigned tasks, it is
calculated as the maximal amplitude of the deviations of the uncertain
task times from their nominal values
for which the system admissibility remains respected. The most
practical advantage of using this indicator comparing with stochastic
and fuzzy approaches consists in the fact that there is no need to
possess reliable historical data on the variability of processing task
Design a production system configuration with the greatest stability
radius is a new difficult combinatorial optimization problem that has
been recently introduced and studied in our work Rossi et al. (2016)
for simple assembly lines and represents an important object of study
from both practical and algorithmic points of view. One of the goals
ADLACI project enrolls the perspectives of that paper and will be
dedicated to the optimal design of assembly lines with extra large
task time variations that can even be greater than the cycle time. In
response, the only technological solution, but still very expensive,
is the installation of parallel workstations with duplicated tasks
that conducts us to consider new complex industrial optimization
problems aiming to minimize the number of
parallel workstations and seeking the trade-off between the
corresponding stability radius to be maximized.
The object of this Post-Doc proposal is to develop efficient heuristic
and exact methods for the resolution of this new problem as well as to
study the computational complexity of some combinatorial optimization
sub-problems that can be appeared in. It will be achieved by studying
its particular structure in order to investigate, inter alia, good
quality upper/lower bounds on optima, efficient dominance properties
and appropriate branching techniques.
The successful candidate will be located in LERIA (Laboratory of
Computer Science) of the University of Angers (France) and is expected
to have good operational research and
multi-objective optimization skills as well as excellent programming
background in C/C++.
A previous experience with CPLEX or Gurobi, and knowledge of assembly
lines balancing or mono-dimensional bin-packing problems would be
appreciated as well.
Compensation: Between 1850 and 2100 euros net per month (depending on
the candidate experience).
Contract duration: 10 months from October 2016 to July 2017 (or from
November 2016 to August 2017).
Please send your CV, motivation letter and two references to
Gurevsky, E., Battaïa, O., Dolgui, A., 2012. Balancing of simple
assembly lines under variations of task processing times. Annals of
Operations Research 201 (1), 265-286.
Gurevsky, E., Battaïa, O., Dolgui, A., 2013. Stability measure for a
generalized assembly line balancing problem. Discrete Applied
Mathematics 161 (3), 377-394.
Rossi, A., Gurevsky, E., Battaïa, O., Dolgui, A., 2016. Maximizing the
robustness for simple assembly lines with fixed cycle time and limited
number of workstations. Discrete Applied Mathematics 208, 123-136.
Scholl, A., Becker, C., 2006. State-of-the-art exact and heuristic
solution procedures for simple assembly line balancing. European
Journal of Operational Research 168 (3), 666-693.
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