Pedro Munari
UFSCar - Universidade Federal de São Carlos, Brazil
Production Engineering Department
Rodovia Washington Luís, Km 235
CEP: 13565-905, São Carlos – SP, Brazil
munari@dep.ufscar.br

Google MyCitations: http://scholar.google.com/citations?user=W88BOtMAAAAJ

ORCID: ORCID iD iconorcid.org/0000-0001-5929-593X

CV Lattes: http://lattes.cnpq.br/1328868140869976

FAPESP grants and scholarships: http://www.bv.fapesp.br/en/pesquisador/60439/pedro-augusto-munari-junior/

Thesis: Theoretical and computational issues for improving the performance of linear optimization methods
[View Manuscript] [View presentation] [Best PhD Dissertation Award 2014 - 1st place]

Finalist on the ROADEF/EURO Challenge 2016: Inventory Routing Problem
Finished on 4th place (Team S12)

Education

Mar/2009-Jan/2013

Ph.D. student at the University of São Paulo under the joint supervision of Prof. Marcos Arenales and Prof. Jacek Gondzio (University of Edinburgh, UK).
Thesis: Theoretical and computational issues for improving the performance of linear optimization methods.
Funded by: FAPESP/CAPES.
Submitted: 12 Dec 2012; Viva: 31 Jan 2013.

Jul/2012-Sep/2012

Visiting postgraduate student at the University of Edinburgh, UK, under the supervision of Prof. Jacek Gondzio.

Jan/2010-Dec/2010

Visiting postgraduate student at the University of Edinburgh, UK, under the supervision of Prof. Jacek Gondzio.

Mar/2007-Feb/2009

MSc at the University of São Paulo under the supervision of Prof. Marcos Arenales.
Dissertation: Computational aspects for an efficient and stable implementation of simplex-type methods. (in portuguese)
Funded by: FAPESP.

Mar/2002-Jan/2006

Bachelor in Computer Science from the University of State of São Paulo.


Awards

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Best PhD Dissertation in Applied and Computational Mathematics
Doctoral Prize "Odelar Leite Linhares"
Brazilian Society of Applied and Computational Mathematics (SBMAC)


Research interests


Theory and implementation of methods for linear, integer and combinatorial optimization:
- Simplex-type and interior point methods;
- Cutting plane/column generation procedures;
- Decomposition and relaxation techniques;
- Branch-and-price and branch-price-and-cut methods.

Vehicle routing problems:
- Practical variants: time windows, multiple deliverymen, pickup and delivery, maritime industry;
- Deterministic and stochastic models;
- Exact and hybrid methods.


Publications and working papers

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Furtado, M.G.S.; Munari, P.; Morabito, R. Pickup and delivery problem with time windows: a new compact two-index formulation. Operations Research Letters, v. 45 (4), p. 334-341, 2017.

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Álvarez, A.; Munari, P. An exact hybrid method for the vehicle routing problem with time windows and multiple deliverymen. Computers & Operations Research, v. 83, p. 1-12, 2017.

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Munari, P. Mathematical modeling in the airline industry: optimizing aircraft assignment for on-demand air transport. Proceeding Series of the Brazilian Society of Computational and Applied Mathematics, v. 5 (1), 2017.

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de la Vega, J.; Munari, P.; Morabito, R. Robust Optimization for the Vehicle Routing Problem with Multiple Deliverymen . Technical Report, Production Engineering Department, Federal University of São Carlos, Brazil. 2017. (Submitted)

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Álvarez, A.; Munari, P.; Morabito, R. Iterated local search and simulated annealing algorithms for the inventory routing problem. Technical Report, Production Engineering Department, Federal University of São Carlos, Brazil. 2017. (Submitted)

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Munari, P. A generalized formulation for vehicle routing problems. Working Paper, arXiv:1606.01935. June, 2016.

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Munari, P.; Morabito, R. A branch-price-and-cut for the vehicle routing problem with time windows and multiple deliverymen. Technical Report, Production Engineering Department, Federal University of São Carlos, Brazil. 2016. (Submitted)

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Álvarez, A. and Munari, P. Metaheuristic approaches for the vehicle routing problem with time windows and multiple deliverymen. Journal of Management & Production (Gestão & Produção), v. 23 (2), p. 279-293, 2016.

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Gondzio, J.; González-Brevis, P.; Munari, P. Large-Scale Optimization with the Primal-Dual Column Generation Method. Mathematical Programming Computation, v. 8 (1), p. 47-82, 2016.

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Munari, P.; Gondzio, J. Column generation and branch-and-price with interior point methods. Proceeding Series of the Brazilian Society of Computational and Applied Mathematics, v. 3 (1), 2015.

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Santos, L.M.R.; Munari, P.; Costa, A.M.; Santos, R.H.S. A branch-and-price method for the vegetable crop rotation scheduling problem with minimal plot sizes. European Journal of Operational Research, v. 245 (2), p. 581–590, 2015.

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Aerts, N. ; Broeders, E. ; Bruin, E. ; Kang, R. J. ; Munari, P. Power line route optimisation in a finite spatial grid. Proceedings of the 106th European Study Group Mathematics with Industry. Universiteit Utrecht, The Netherlands, Studiegroep Wiskunde met de Industrie, p. 55-84, 2015.

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Munari, P.; Gondzio, J. Using the primal-dual interior point algorithm within the branch-price-and-cut method. Computers & Operations Research, v. 40 (8), p. 2026-2036, 2013.

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Gondzio, J.; González-Brevis, P.; Munari, P. New developments in the primal-dual column generation technique. European Journal of Operational Research, v. 224 (1), p. 41-51, 2013.

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Munari, P.; González-Brevis, P.; Gondzio, J. A note on the primal-dual column generation technique. Electronic Notes in Discrete Mathematics, v. 37, p. 309-314, 2011.

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Alem, D.J.; Munari, P.; Arenales, M.N.; Ferreira, P.A.V. On the cutting stock problem under stochastic demand. Annals of Operations Research, v. 179, p. 169-186, 2010.


Softwares

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PDCGM v.2.0: Implementation of the Primal-Dual Column Generation Method.


Conferences Comitee

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2nd Brazilian Workshop on Interior Point Methods (Organizer)
17-18/May, 2016 - Campinas, Brazil.

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1st Brazilian Workshop on Interior Point Methods (Organizer)
27-28/April, 2015 - Campinas, Brazil.

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XVI Oficina Nacional de Problemas de Corte, Empacotamento, Dimensionamento de Lotes e Programação da Produção. (Organizer)
27-28/March, 2014 - São Carlos, Brazil.


Conferences and workshops attended

Feb/2017

Combinatorial Optimization and Applications 2017.
Edinburgh, Scotland, UK.

July/2016

28th European Conference on Operational Research.
Poznan, Poland.

July/2016

14th EUROPT Workshop on Advances in Continuous Optimization.
Warsaw, Poland.

May/2016

Column Generation 2016.
Buzios-RJ, Brazil.

May/2016

2nd Brazilian Workshop on Interior Point Methods (BWIPM 2016).
Campinas, Brazil.

Sep/2015

AIRO 2015 - 45th Annual Conference of the Italian Operations Research Society.
Pisa, Italy.

Sep/2015

OR 2015 - International Conference on Operations Research.
Austria, Vienna.

Apr/2015

1st Brazilian Workshop on Interior Point Methods (BWIPM 2015).
Campinas, Brazil.

Jan/2015

106th European Study Group in Mathematics with Industry (SWI 2015).
Utrecht, Netherlands.

Sep/2014

XXXV Congresso Nacional de Matemática Aplicada e Computacional (CNMAC 2014).
Natal, Brazil.

Jul/2014

20th Confer. of the International Federation of Operational Research Societies (IFORS).
Barcelona, Spain.

Mar/2014

X Brazilian Workshop on Continuous Optimization.
Florianópolis, Brazil.

Mar/2014

3rd International Symposium on Combinatorial Optimization (ISCO 2014).
Lisbon, Portugal.

Aug/2012

21st International Symposium on Mathematical Programming (ISMP 2012).
Berlin, Germany.

Jul/2012

25th European Conference on Operational Research (EURO).
Vilnius, Lithuania.

May/2011

SIAM Conferece on Optimization (OP11).
Darmstadt, Germany.

Mar/2011

VI Latin-American Algorithms, Graphs and Optimization Symposium (LAGOS'11).
Bariloche, Argentina.

Sep/2010

2nd IMA Conference on Numerical Linear Algebra and Optimisation.
University of Birmingham, UK.

Aug/2010

Summer school on column generation 2010.
Darmstadt University of Technology, Germany.

Apr/2010

2nd Student Conference on Operational Research (SCOR 2010).
University of Nottingham, UK.

Jan-Dec/2010

Seminars of the Edinburgh Research Group in Optimization (ERGO).
University of Edinburgh, UK.


Talks and presentations

Feb/2017

Solving challenging vehicle routing problems: you better follow the central path
Combinatorial Optimization and Applications 2017
Plenary speaker
[View slides]

May/2016

p-step formulations for vehicle routing problems: a generalized class of models based on column generation
Column Generation 2016
[View slides]
Abstract: Different types of formulations are proposed in the literature to model vehicle routing problems. Currently, the most used ones can be fitted into two classes, namely vehicle flow formulations and set partitioning formulations. These types of formulations differ from each other not only due to their variables and constraints but also due to their main features. Vehicle flow formulations have the advantage of being compact models, so general-purpose optimization packages can be used to straightforwardly solve them. However, they typically show weak linear relaxations and have a large number of constraints. Branch-and-cut methods based on specialized valid inequalities can also be devised to solve these formulations, but they have not shown to be effective for large-scale instances. On the other hand, set partitioning formulations have stronger linear relaxations, but requires the implementation of sophisticate techniques such as column generation and specialized branch-and-price methods. Due to all these reasons, so far it is has been recognized in the vehicle routing community that these two types of formulations are rather different. In this talk, we show that they are actually strongly related as they correspond to special cases of a generalized formulation of vehicle routing problems.

Apr/2015

The advantages of interior point methods for decomposition techniques
1st Brazilian Workshop on Interior Point Methods (BWIPM 2015)
[View slides]
Abstract: Decomposition techniques are essential tools for solving challenging large-scale optimization problems. There is a number of problems in the field of integer programming and nonlinear optimization that can only be effectively solved after applying a technique such as Dantzig-Wolfe or Benders decomposition. Most implementations are based on the simplex method to obtain optimal solutions of linear relaxations. However, as it has been shown by a few researchers, interior point methods (IPM) can offer several advantages to improve the performance of decomposition algorithms. The central solutions provided by IPM can be useful to stabilize the behavior of decomposition algorithms and speed up the running time of the implementations. In this talk, we review the main strategies proposed for combining IPM and decomposition techniques and summarize their results. In addition, we present new results that indicate the positive impact of such combinations for solving vehicle routing problems.

Sep/2014

Theoretical and computational issues for improving the performance of linear optimization methods
XXXV Congresso Nacional de Matemática Aplicada e Computacional (CNMAC 2014)
Plenary talk for the Best PhD Dissertation Award - Prêmio Odelar Leite Linhares
[View slides]

Jul/2014

Solving convex optimization problems with column generation and interior point methods
20th Confer. of the International Federation of Operational Research Societies (IFORS)
Abstract: The column generation technique and the primal-dual interior point algorithm can be suitably combined for solving challenging optimization problems. Interior point methods provide stability to column generation, typically reducing the number of iterations and improving running times. In this talk, we describe the theoretical and computational issues regarding such combination. In addition, we present the results of using this strategy to solve convex optimization problems which arise in important real-life situations, such as data analysis, decision-making under uncertainty and networks.

Mar/2014

Interior point method and column generation for solving large-scale optimization problems
X Brazilian Workshop on Continuous Optimization
Abstract: The column generation technique has proven to be an important tool when solving continuous optimization problems. In practice, the performance of this technique is strongly dependent on the type of the dual solutions used to generate columns. Optimal dual solutions which are extreme points of the feasible set typically oscillate too much between consecutive iterations, which leads to a slow convergence of the column generation technique. To overcome this behavior, non-optimal dual solutions may be used instead. In this talk, we show that the interior point method is more than an alternative to the simplex method in this context. Indeed, it offers advantageous features which can be used to stabilize the dual solutions in the column generation technique. We present the results of computational experiments with classes of problems that arise in important real-life contexts such as vehicle routing, data analysis, decision-making under uncertainty and telecommunication and transportation networks. The results provide evidence of the benefits of appropriately combining the interior point algorithm with column generation, specially for solving large-scale problems. The experiments were run using the PDCGM library, an implementation of the primal-dual column generation method which is publicly available on the Internet.

Mar/2014

Using an interior point branch-price-and-cut method for solving variants of the vehicle routing problem
3rd International Symposium on Combinatorial Optimization (ISCO 2014)
Abstract: Branch-price-and-cut methods have been successfully used to solve many combinatorial optimization problems. As recently present in the literature, the performance of these methods can be improved by combining them with the primal-dual interior point algorithm. The resulting interior point branch-price-and-cut method typically shows more stability in the column generation, smaller number of valid inequalities and less nodes in the search tree. As a result, the total CPU time may be significantly reduced. These improvements are mainly due to the centrality of primal and dual solutions provided by the interior point algorithm, even when these solutions are non-optimal. In this talk, we describe the challenges of implementing an interior point branch-price-and-cut for solving a practical variant of the vehicle routing problem with time windows. This variant involves deciding how many deliverymen to assign to each vehicle, in addition to the usual routing and scheduling decisions. Such situation is faced by many companies in practice, especially those which must perform a large number of deliveries in very busy urban areas, such as dairy, beverage and tobacco industries. We present the results of computational experiments which indicate the advantages of using an interior point branch-price-and-cut method in this context.

Aug/2012

Using interior point methods in branch-price-and-cut framework
21st International Symposium on Mathematical Programming (ISMP 2012)
Abstract: Branch-price-and-cut framework has proven to be a very powerful method for solving integer programming problems. It combines decomposition techniques with the generation of both columns and valid inequalities and relies on strong bounds to guide the search in the branch-and-bound tree. In this talk, we present how the performance of branch-price-and-cut framework can be improved by using the primal-dual interior point method. We discuss in detail how the challenges involved in combining the primal dual interior point method with the integer programming techniques are addressed. The effort to overcome these challenges pays off in a number of advantageous features offered by the new approach. We present the computational results of solving the well-known instances of the Vehicle Routing Problem with Time Windows, a challenging integer programming problem. The results confirm that the proposed approach delivers the best overall performance when compared with other branch-price-and-cut frameworks available in the literature.

Jul/2012

Solving the vehicle routing problem with time windows by an interior point branch-price-and-cut framework
25th European Conference on Operational Research (EURO)
Abstract: In this talk, we present a branch-price-and-cut framework for the vehicle routing problem with time windows which is based on a primal-dual interior point method for efficiently solving the linear relaxations at each branch node. The interior point method is used to obtain well-centred, non-optimal solutions that are used to improve the generation of columns and valid inequalities. Computational results using the Solomon's instances show that the proposed approach has a better overall performance than the best branch-price-and-cut framework available in the literature.

May/2011

Solving combinatorial optimization problems with interior point methods
SIAM Conferece on Optimization (OP11)
Abstract: A wealth of solution methods is available for solving combinatorial optimization problems. Focusing on general-purpose exact methods based on integer programming models, the standard approaches rely on solving a sequence of closely related linear programming problems. In this talk, we address the challenging issues of using a primal-dual interior point method within a branch-and-price-and-cut strategy, and present preliminary computational results for classical combinatorial optimization problems from the literature.

Mar/2011

A note on the primal-dual column generation method for combinatorial optimization
VI Latin-American Algorithms, Graphs and Optimization Symposium (LAGOS'11)
Abstract: In this talk, we address the primal-dual column generation technique, which relies on well-centred suboptimal solutions of the restricted master problems. Although very efficient on solving a particular class of problems, this technique has never been tested in the context of combinatorial optimization. Here, we summarize new theoretical developments and present computational results for two classical combinatorial optimization problems. The results show that the primal-dual technique usually leads to substantial reductions in the number of iterations when compared to the classical and also analytic centre approaches.

Oct/2010

Further developments in the primal-dual column generation
Seminars of the Edinburgh Research Group in Optimization (ERGO).

Sep/2010

Warmstarting primal-dual interior point methods for integer programming
2nd IMA Conference on Numerical Linear Algebra and Optimisation.

Apr/2010

On solving large-scale integer programming problems
2nd Student Conference on Operational Research (SCOR 2010).


Teaching

2016

First semester:
- Continuous and Discrete Linear Optimization [WEBPAGE]
Production Engineering (post-graduate), UFSCar, Brazil

2015

Second semester:
- Operations Research for Production Engineering I
Production Engineering (undergraduate), UFSCar, Brazil

First semester:
- Continuous and Discrete Linear Optimization
Production Engineering (post-graduate), UFSCar, Brazil

2014

Second semester:
- Operations Research for Production Engineering I
- Probabilistic models applied to Production Engineering

Production Engineering (undergraduate), UFSCar, Brazil

First semester:
- Operations Research for Production Engineering II
Production Engineering (undergraduate), UFSCar, Brazil

2013

Second semester:
- Operations Research for Production Engineering I
- Introduction to Operations Research

Production Engineering (undergraduate) and Statistics (undergraduate), UFSCar, Brazil

First semester:
- Operations Research for Production Engineering II
Production Engineering (undergraduate), UFSCar, Brazil

2010

Second semester:
Tutoring the MSc courses Mathematical Programming and Dynamic and Integer Programming.
Operational Research MSc Programme, University of Edinburgh, UK


Referee of the following journals and conferences

European Journal of Operational Research (EJOR)
Mathematical Programming Computation (MPC)
Computational Optimization and Applications (COAP)
Revista Produção
Pesquisa operacional para o desenvolvimento (PODES)
Simpósio Brasileiro de Pesquisa Operacional (SBPO)