Invited Speakers:

  Francesco Archetti (University of Milan, Italy ) 

        "Operations Systems and Life Sciences: Integration Perspectives"

  Francisco Barahona (IBM Watson Center, USA ) - ORMA Invited Speaker

         "Separation of partition inequalities and their role in network design"(abstract)

  Oleg Burdakov (Linköping University,Sweeden ) 

         "Isotonic Regression: Algorithms and Applications" (abstract)

  Laureano Escudero (Universidad Miguel Hernández,Spain ) 

         "On Solving  Mixed 0-1 Stochastic Programs" (abstract)

  Gilbert Laporte (Canada Research Chair in Distribution Management,Canada ) 

         "Metaheuristics for the Vehicle Routing Problem:  Fifteen Years of Research" (abstract)

  Martin Savelsbergh (Georgia Institute of Technology,USA ) 

         "Logistics Challenges and Optimization Opportunities" (abstract)

 

 

Keynote Speakers:
 
  Stream:"Stochastic Simulation and Optimization"

      Pierre L'Ecuyer ( Université de Montréal, Canada )

            "Uniform Random Number Generation: Overview and Recent Developments"  (abstract)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Francisco Barahona (IBM Watson Center, USA ) - ORMA Invited Speaker

"Separation of partition inequalities and their role in network design"


Partition inequalities are used in network design problems to impose different types of connectivity constraints. We describe several classes of these inequalities, we give separation algorithms and discuss their applications to different Network Design problems.

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Oleg Burdakov (Linköping University,Sweeden ) 

"Isotonic regression: algorithms and applications"

The isotonic regression problem (IR) has important applications in statistics, operations research and image processing. It can be formulated as a quadratic programming problem of finding the n-dimensional vector x that minimizes the Euclidean distance from a given vector to a cone. The cone is defined by linear constraints which

establishes relations between some pairs of components of x in the form "component number i is less-or-equal to component number j". The relation between the components can be presented by an acyclic directed graph. The applied IR problems are often characterized by a very large value of n. Therefore, the complexity of IR algorithms is required to rise with n not too rapidly. The IR problem is known to be of polynomial complexity.

In our presentation, we discuss applications of the IR problems and give an overview of optimization algorithms developed for solving these problems.

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Laureano Escudero

Universidad Miguel Hernández:

 "On Solving  Mixed 0--1 Stochastic Programs"

Abstract. We present a framework for solving mixed 0-1 multi-stage problems under uncertainty in the objective function coefficients and the right-hand-side. A scenario analysis scheme with full recourse is used. The constraints are modelled by a splitting variable representation via scenarios. So, a mixed 0-1 model for each scenario is considered plus the non-anticipativity constraints that equate the so-called common continuous and 0-1 variables from the same group of scenarios in each stage. A Branch-and-Fix Coordination approach is presented for coordinating the selection of the branching Twin Node Families (TNF) and the branching common variables in the scenario subproblems to be jointly optimized. We consider Lagrangean Substitution and Decomposition schemes for bounding purposes at the so-called candidate and integer TNFs. Some computational experience is reported for different types of problems.

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Gilbert Laporte

Canada Research Chair in Distribution Management:

 "Metaheuristics for the Vehicle Routing Problem: Fifteen Years of Research"

Over the past fifteen years several powerful metaheuristics have been developed for the Vehicle Roputing Problem (VRP). The best methods are based on tabu search, variable neighbourhood search, genetic search, and ant algorithms. Much progress has been accomplished since the publication of the first tabu search heuristic for the VRP in 1989. Several methods have been proposed, but not all have been equally successful. In this talk I will provide an overview of some of the best algorithmic ideas proposed over the past fifteen years, and I will also mention some ideas that did not work so well.

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Martin Savelsbergh

Georgia Institute of Technology:

 "Logistics Challenges and Optimization Opportunities"

Abstract. Traditionally companies have focused on improving their own internal business processes when faced with pressures to operate more efficiently and more cost effectively. However, a system-wide focus, e.g., a collaborative focus, opens up cost saving opportunities that are impossible to achieve with an internal company focus.  With the possibility of sharing and analyzing data through the connectivity provided by the internet, there has recently been a shift of attention towards controlling and reducing system wide costs and sharing these cost savings to increase profitability for all parties involved.

 With the availability of timely and accurate information, new collaborative opportunities which create mutual benefit by taking advantage of operational synergies between buyers, sellers, or buyers and sellers are now arising.  Collaborative logistics is viewed by many logistics professionals as the most promising opportunity for reducing logistics costs and therefore increasing profitability and economic prosperity.

 Probably one of the most successful applications of collaboration in logistics to date is vendor managed inventory (although it is not typically presented as an example of logistics collaboration). In environments where vendor managed inventory partnerships are in effect, the vendor is allowed to choose the timing and size of deliveries.  In exchange for this freedom, the vendor agrees to ensure that its customers do not run out of product.  In a more traditional relationship, where customers call in their orders, large inefficiencies can occur due to the timing of customers' orders, i.e., high inventory and high distribution costs.  By initiating vendor managed inventory partnerships demand variability is decreased, reducing inventory holding and
distribution costs.

 Another, more recent, successful application of collaboration in logistics is found in the trucking industry.  To execute shipments from different shippers a carrier often has to reposition its assets, i.e., trucks.  Shippers have no insight in how the interaction between their various shipments affects a carrier's asset repositioning costs.  However, shippers are implicitly charged for these repositioning costs.  No single participant in the logistics system controls asset repositioning costs, so only through collaborative logistics initiatives can these costs be controlled and reduced.  Asset repositioning is expensive.  A recent report estimates that 18% of all trucks movements every day are empty. In a $921 billion U.S. logistics market, the collective loss is staggering: more than $165 billion.

 In this presentation, we introduce a variety of challenging optimization problems that arise as a result of these collaborative logistics initiatives and discuss the potential solution approaches.

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Pierre L'Ecuyer

Université de Montréal, Canada

 "Uniform Random Number Generation: Overview and Recent Developments"

In this talk, we first outline a set of design principles for uniform random number generators (RNGs) used for stochastic simulation. We recall the main requirements for a good generator (good multidimensional uniformity, high speed, etc.) and theoretical figures of merit for certain classes of linear-type generators. We also discuss theoretical versus statistical testing of RNGs.

Bad RNGs are still well alive. As an illustration, we briefly examine those in Excel, Visual Basic, and the Java standard library, and exhibit two very simple simulation models for which these RNGs give totally wrong results.

We then summarize some recent ideas for constructing fast and reliable generators. They include: (a) combined multiple recursive generators with coe_cients that are a sum or a diffrence of a few powers of 2; (b) combined generators whose components are based on linear recurrences modulo 2 (such as Tausworthe, twisted GFSR, etc.); (c) polynomial linear congruential generators with tempering; (d) mixted linear/nonlinear combined generators. Practical random number packages with multiple streams and substreams are presented at the end of the talk.

Several papers on uniform RNGs are available on this speakers’s web page.

 

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