(DEP) of the Federal University of São Carlos (UFSCar), São Carlos / São
Paulo, Brazil
Topic: The Vehicle Allocation Problem with Uncertain Parameters: Robust
Optimization and Stochastic Programming Approaches
Supervisors: Prof. Reinaldo Morabito and Prof. Pedro Munari – DEP/UFSCar
The Operations Research Group at DEP/UFSCar is accepting applications for 1
postdoctoral position. The research project involves developing robust
optimization and stochastic programming models and methods for the vehicle
allocation problem.
The selection will be based on the candidates' curriculum vitae and their
potential contribution to this project, as well as to the associated FAPESP
Thematic Project: "Cutting, packing, lot-sizing, production scheduling,
routing, location problems, and their integration in industrial and
logistical contexts." Candidates must have completed a Ph.D. in areas
related to Operations Research. The full guidelines are available at
http://fapesp.br/bolsas/pd.
Interested applicants should submit a letter of recommendation, a letter of
interest, and a CV (for Brazilian applicants, the CV-Lattes). All
documentation must be sent by September 30, 2024, in a single PDF file to
both e-mail addresses: morabito@ufscar.br and munari@dep.ufscar.br.
The position is open to both Brazilian and foreign candidates. The selected
candidate will receive a FAPESP Postdoctoral Fellowship with a monthly
stipend of R$ 12,000.00, plus reimbursement for social security
contributions (INSS), a Technical Reserve (www.fapesp.br/rt), and the
possibility of a Research Internship Abroad Scholarship (
www.fapesp.br/bolsas/bepe).
If the postdoctoral fellow resides in a location different and distant from
São Carlos/Brazil, they may also receive support from FAPESP for relocation
to São Carlos.
Project Summary: The Vehicle Allocation Problem (VAP) involves allocating a
fleet of vehicles to meet the estimated cargo transport demand between
terminals over a finite time horizon with multiple periods. The objective
is to maximize the profit generated by services performed with the own
fleet, considering demand forecasts. In some cases, the goal is to minimize
the cost of meeting all demand, potentially requiring the hiring of
additional third-party vehicles. The real-world instances faced by cargo
carriers are considerably large, making it difficult to obtain optimal
solutions within acceptable computational times. Thus, the literature has
focused on developing heuristic methods that provide good solutions within
practical computational tolerances. In some cases, customized exact methods
have also been developed and applied to handle deterministic versions of
the problem within reasonable computational times. This postdoctoral
research project aims to extend exact and heuristic approaches to account
for uncertainties in the problem parameters, particularly in customer
demands, vehicle availability, and vehicle travel times. Models and
approaches using stochastic programming and robust optimization for the
problem will be developed and tested to generate solutions more immune to
parameter uncertainties.
-------------------------------------------------------
Prof. Dr. Pedro Munari
Associate Professor, Operations Research Group
Production Engineering Department, Federal University of São Carlos, Brazil
http://www.dep.ufscar.br/munari/
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