Speakers

PLENARY SPEAKERS

• Ralph E. Gomory - Forty Years of Corner Polyhedra [Abstract]
• Finn E. Kydland - Dynamic Programming and Economics [Abstract]
• Hans-Jürgen Zimmermann - 40 Years of EURO: History, Applications, Future Potentials [Abstract]


KEYNOTE & TUTORIAL SPEAKERS:



----------------------------------------------------------------------------------------------------------
Forty Years of Corner Polyhedra by Ralph E. Gomory

This talk will discuss the evolution of corner polyhedra from their beginnings in the study of Stock Cutting problems.  We will discuss both their practical and theoretical aspects. We will see that corner polyhedra are by themselves the simplest integer programs and therefore might be expected to be more amenable to analysis than the more complex I.P. s of which they are always a part. This expectation is fulfilled by some theoretical insights gained from corner polyhedra. The practical linkage stems from the fact that cutting planes for corner polyhedra are cutting planes for the complex practical problems of which they are a part.  No knowledge of corner polyhedra is assumed in this talk and historical and personal aspects will be included throughout.

----------------------------------------------------------------------------------------------------------
Dynamic Programming and Economics by Finn Kydland

All interesting phenomena in macroeconomics are dynamic in nature. An overstatement, perhaps, but only a slight one. As a consequence, over the past three or four decades, dynamic programming has been an essential tool, including in my own research. In quantitative aggregate economics, dynamic programming plays a key role from model formulation to model calibration to computation of model outcomes. In the process, for example, of calibrating a model economy, its steady-state relations are an essential part of what it takes to work backwards from empirical relations among variables to what the model parameters must be in order to be consistent with them. With advances in the development of theory and computers becoming much more powerful, the set of interesting questions that can be addressed with such models has expanded dramatically in the past decade or two. This is true especially for questions that dictate the inclusion of important heterogeneity across current generations and/or across individuals more generally.

In models with a role for the government, anticipated future policy affects economic behavior in earlier periods. For example, future tax policy affects investment behavior today. If we imagine policy to be selected so as to optimize an objective (welfare) function, the resulting policy, in the absence of a commitment mechanism, is generally time inconsistent. Aside from questions about its implementation, then, a consequence is that the formulation of the optimal-policy problem is not recursive. But one can generally convert such a model into a recursive structure by introducing an additional pseudo-state variable – a shadow price – which is subject to its own constraint implied by the model. Similar issues about recursivity, potentially resolved in an analogous manner, arise in many dynamic contracting environments.
----------------------------------------------------------------------------------------------------------
40 Years of EURO: History, Applications, Future Potentials  by H.-J.Zimmermann

40 years ago, i.e. in 1972, the world looked quite different from to-day: Logistics were slower and more complicated: The best way to travel from Europe to the USA was by ship,which took between 5 and 13 days. Alternatively one could take a “Super Constellation” and go via Island in 24 hours. There were no electronic booking systems, customs-and passport control at each European Border, but no security systems at airports, no terrorism and no hijacking of planes. Communication was as clumsy: No fax, no email, no courier services, a letter between Europe and oversees took two to three weeks, each single letter had to be typed ,and there were neither social nets nor a www. Professionally there existed three large OR - journals (and a number of small national ones), East and West was separated by the Iron Curtain. “Large” OR - Societies existed in the USA, Japan and Great Britain and in Europe there were a dozen of smaller national OR Societies. There was hardly any communication between these European societies and if one wanted to know what was going on in OR in another European country, the best way was, to ask a colleague in the USA. In the USA Ackoff had stated ( in 1979) “American Operations Research is dead though not yet buried”.

Under these circumstances the presidents of the European OR societies met at the IFORS conference 1972 in Dublin and came to the conclusion, that this situation of OR in Europe was sub-optimal and should be improved. They met again in 1973 and 1974 and decided to organize the first European OR conference at the end of January 1975 in Brussels. There were 500 participants and the representatives of 10 European  countries. In the framework of this conference EURO was founded, 7 European working groups were started, the EURO - bulletins was started and it was decided to prepare the publication of a European OR journal (EJOR).

In the meantime  EURO has 30 member countries, several professional journals, about 30 working groups, several very successful types of events, several prizes and awards, a very impressive web-page, and has had 25 successful  EURO conferences. Hence: EURO has turned out to be a very successful organization.

The success of OR can , however, not only be measured by the manifold growth of EURO ! As an applied discipline the situation of OR in Europe should also be considered from the point of view of  available OR - tools, from its public visibility, the areas of applications, the education in this area, and its relationship to other disciplines that have emerged in the meantime and are relevant for OR. In some of these dimensions OR can certainly also be considered to be very successful. In others there are still or again big challenges that have to be met, if OR is also to be successful in the future. In this presentation some of these challenges will be considered in more detail and some ways suggested, how they can possibly be met.
----------------------------------------------------------------------------------------------------------
On the role of randomness in exact tree search methods by Matteo Fischetti

----------------------------------------------------------------------------------------------------------
Providing a Scientific Basis for Managing Illegal Drugs & Markets by Jonathan Caulkins

What happens when formal training in operational analysis meets a classic “wicked problem” with multiple conflicting objectives, competing agency priorities, and abundant data that nevertheless do not answer the questions that really matter?  This talk gives one answer, drawing on 20+ years experience working on a particularly fascinating problem – policy regarding control of illegal markets, notably those for illegal drugs.

The tools of operations research, industrial organizations, and economics can be harnessed to provide an empirical, scientific basis for drug policy making.  The models discussed in this talk focus on drug initiation (product diffusion), price responsiveness (elasticity of demand), and operation of the illegal supply chain, both during normal times and when the distribution network is disrupted.  Corresponding data are drawn from epidemiological studies, forensic laboratory analysis, undercover buys, and extensive interviews with incarcerated drug smugglers and dealers in Australia, France, the UK, and the US.  These models provide the foundation for estimating the cost-effectiveness of different strategies for controlling drug use and associated social harms. 

However, I will not tell an entirely happy tale of Operations Research (OR) as panacea, limited only by the outside world’s ignorance of its power.  Rather, I will tell a story of a glass that is half full and yet also half empty. 

For example, these issues are truly “OR problems” in the sense that OR ideas and insights underpin key dynamics and in the sense that knowledge of OR empowers better understanding and solutions.  However, they are also problems of and for economics, sociology, political science, demography, psychology, medicine, and other disciplines.  OR can and should partner with other disciplines and perspectives when grappling with fundamental strategy choices related to drug policy. 

Likewise, the adversarial nature of the policy making process challenges an optimization-based way of looking at the world. 

The objective of this talk is to reflect on OR’s success and limitations in this and some allied domains to draw meta lessons for how experts can effectively use mathematical models and operational analysis to produce insights that inform decision makers in comparably messy domains.
----------------------------------------------------------------------------------------------------------
Optimization in Process Systems Enigineering by Igancio Grossmann

Enterprise-wide optimization (EWO) is a new emerging area that lies at the interface of chemical engineering and operations research, and has become a major goal in the process industries due to the increasing pressures for remaining competitive in the global marketplace. EWO involves optimizing the operations of supply, production and distribution activities of a company to reduce costs and inventories. A major focus in EWO is the optimization of manufacturing plants as part of the overall optimization of the supply chain. Major operational items include production planning, scheduling, and control. This talk provides an overview of major modeling and computational challenges in the development of deterministic and stochastic linear/nonlinear mixed-integer optimization models for planning and scheduling for the optimization of plants and entire supply chains that are involved in EWO problems. We illustrate the application of these ideas in four major problems:

a) integration of planning and scheduling in batch processes that lead to large-scale mixed-integer linear programs,
b) optimization of responsive process supply chains that lead to large-scale bicriterion mixed-integer optimization problems,
c) optimization of distribution-inventory planning of industrial gases that lead to integration of planning and vehicle-routing models,
d) optimization of oilfield infrastructures under uncertainty that lead to multistage stochastic programming problems with endogenous uncertain parameters.

We outline the solution methods that have been developed. Also, these problems have been addressed in collaboration with industry, and have led to substantial economic savings.
----------------------------------------------------------------------------------------------------------
Auctions: Why they proliferating and what you need to know to participate by Karla Hoffman

The advent of the Internet has led to the creation of global marketplaces in which sales of everything from low-cost used merchandise to billion dollar government procurements are conducted by auction. While some auction designs have been extremely successful, others have failed disastrously. This talk will describe a variety of alternative auction designs, and will explore why one design is likely to be more appropriate than another for a given application. We will begin with a brief history of auctions, provide reasons for eBay’s spectacular success, and highlight the Internet’s impact on auction theory and practice. We will then move on to a discussion of the strategies that are available to bidders in the most-utilized auction formats, thereby providing each of you with hints on how to be more successful when participating in auctions. Throughout the talk, we will highlight the role that operations research analysts can play in designing, running, and assisting participants in business-to-business and high-stakes government auctions.
----------------------------------------------------------------------------------------------------------

Computational Biology and Operations Research by Ceyda Oguz

Advancing the scientific understanding of organisms through computation has an ever-increasing importance that necessitates more research into fundamental problems of molecular biology. Research direction for these problems involves better analytical tools and more efficient algorithms due to massive volume of data. Hence computational biology can benefit from operations research area for developing mathematical models and devising efficient algorithms. In the literature, while integer programming and network models are usually employed at the modeling stage, dynamic programming, branch-and-bound algorithm, heuristics and metaheuristics are the prevalent computational methods employed for the problems. In this talk, I will give an overview of application of operations research methods to several computational problems that are faced in molecular biology. 

----------------------------------------------------------------------------------------------------------
Column Generation by Guy Desaulniers

Column generation is a well-known mathematical programming technique for solving large-scale optimization linear problems. In the mid-1980s, it was shown that it can be successfully embedded in a branch-and-bound framework (yielding a branch - and - price method) for solving integer programs. Since then, it has become the most popular exact methododology for solving several classes of vehicle routing problems. As a fertile testbed, the vehicle routing problem with time windows (VRPTW) played an important role in this success. It consists of finding a set of least-cost vehicle routes to deliver goods to a set of customers. Each customer must be visited exactly once within a given time window and each route must respect vehicle capacity. In this talk, we survey the evolution of the column generation methods developed for the VRPTW, starting from the seminal work of Desrochers, Desrosiers, and Solomon (1992). In particular, we present various path relaxations proposed to avoid solving the NP - hard elementary shortest path subproblem, labeling algorithms used to generate their corresponding columns, and valid inequalities tightening the lower bounds, including those that are directly defined on the master problem variables. We discuss certain acceleration strategies, report computational results, and highlight current and future challenges.
----------------------------------------------------------------------------------------------------------
Stochastic programming - a flexible tool for decision making under uncertainty by Jitka Dupacova

To apply stochastic programming (SP) means primarily to be familiar with the real-life problem in question, its purpose, constraints, and with the available level of information concerning the driving random factors. Even when implementation of complex SP models does frequently require simplifications and/or approximations, their outcome may point at new decision strategies.

We shall focus on the modeling issues. The interplay between the problem setting and the SP model building will be illustrated on selected examples related mainly to water resources management and planning.
----------------------------------------------------------------------------------------------------------
Lines, Timetables, Delays: Models and Trends in Optimization of Public Transport by Anita Schöbel

The talk consists of two parts: In the first part, a state-of-the-art survey about finding lines and timetables in the strategic planning of a public transportation system will be provided, and the problem of delay management, i.e. how to update the system in case of delays will be explored. The second part will discuss ongoing research questions, namely how the routing of the passengers can be included in the planning phases, how an integration of the planning phases can be obtained and tested, and how robustness issues can be integrated. Theoretical and experimental results on these topics will be shown.

Part 1 gives an overview on line planning, timetabling, and delay management. Given an existing public transportation network with its stops (or stations) and direct connections, the first step in the strategic planning of a transport system is to define lines and their frequencies. A line is a path in the public transportation network along which regular service is offered. We discuss various optimization models minimizing either the costs of the lines or maximizing the convenience for the passengers. If the lines have been found, the next step is to design a timetable. There are two different models: Periodic timetables which are repeated on e.g. an hourly basis and aperiodic timetables. The usual aim is to minimize the traveling time for the passengers. Integer programming formulations will be provided for both problem types and algorithmic approaches for finding timetables will be reviewed. Coming to the operational phase, the question of the delay management problem is how to react in case of delays such that the passengers' travel times do not increase too much. This concerns the decision if a punctual bus or train should wait for a delayed feeder bus or train or if it should better depart on time. In railway traffic also the limited capacity of the tracks has to be taken into account, i.e. priority decisions have to be made. Also here the state-of-the art of delay management will be presented.

The three problems discussed in Part 1 can be solved more or less efficiently. However, the algorithms and approaches are still not suitable for solving real-world problems. In part 2 we will hence discuss features that are missing, identify the resulting research questions and show some first solution approaches aiming at making the algorithms work in practice.

A first problem concerns the decision of the passengers. In many papers on line planning, time tabling, and delay management it is assumed that it is already known how the passengers travel, i.e. a passenger's weight is assumed to be known for every edge or activity in the system. This is an unrealistic assumption since the route choice of the passengers depends on the lines, the timetable and on the delay management strategy. We will discuss how the passengers' decisions may be integrated into the optimization process.

Another issue is robustness. It is not helpful to have an exact optimal solution that might get totally meaningless if a small disturbance occurs. Hence, the aim should be to have a robust transportation system which performs well even if the scenario or the input data changes. We exemplary illustrate different concepts on how robustness can be integrated for the timetabling phase. Specialized algorithms for every single planning phase in public transportation are known. However, the best line plan is not helpful if it only allows bad timetables. Hence, some effort should be made to find integrated solutions.

Using our toolbox LinTim we illustrate how decisions made in earlier planning steps can
influence the subsequent planning phases. Among others we show how the quality of a timetable depends on decisions made in the line planning phase, how good the approximation of the passengers' weights fits to the real behavior of the passengers, and how the robustness of a public transport system may be simulated.
----------------------------------------------------------------------------------------------------------
Metaheuristics - the metaphor exposed by Kenneth Sörensen

In recent years, the field of combinatorial optimization has witnessed a true tsunami of "new" metaheuristic methods, most of them based on a metaphor of some natural process. The behavior of virtually any species of insects, the flow of water, musicians playing together, it seems that no ideas are too far-fetched to serve as inspiration to launch yet another metaheuristic. In this tutorial, we will critically investigate whether the resulting methods are truly original, or just a repackaging of old ideas. In general, the usefulness of metaphor-based methods will be put to the test.

On the other side of the spectrum, researchers in metaheuristics are picking up ideas traditionally found in exact methods only, such as an intelligent decomposition of the problem and the use of exact methods to solve subproblems. In some problem domains such as vehicle routing or scheduling, a consensus is starting to condense on which ideas and which methods work and which do not. This is the result of many years of development of ever more powerful metaheuristics, combined with a careful study of the combinatorial properties of the problem. Additionally, deconstructing of a method, combined with statistical testing of the components and parameters of a metaheuristic can reveal those components and parameter settings that truly contribute to the performance.

The main aim of this talk is to provide some guidelines on how to develop an efficient and effective metaheuristic. We will show that the way forward is through the rigorous use of scientific methods, rather than through the indiscriminate introduction of yet another metaphor.
----------------------------------------------------------------------------------------------------------
  The Role of Corner Polyhedra in Integer Programming by Ralph E. Gomory

This talk will discuss the evolution of corner polyhedra from their beginnings in the study of Stock Cutting problems.  We will discuss both their practical and theoretical aspects. We will see that corner polyhedra are by themselves the simplest integer programs and therefore might be expected to be more amenable to analysis than the more complex I.P. s of which they are always a part. This expectation is fulfilled by some theoretical insights gained from corner polyhedra. The practical linkage stems from the fact that cutting planes for corner polyhedra are cutting planes for the complex practical problems of which they are a part.  No knowledge of corner polyhedra is assumed in this talk.
----------------------------------------------------------------------------------------------------------
Dynamic Programming and Economics by Finn Kydland

All interesting phenomena in macroeconomics are dynamic in nature. An overstatement, perhaps, but only a slight one. As a consequence, over the past three or four decades, dynamic programming has been an essential tool, including in my own research. In quantitative aggregate economics, dynamic programming plays a key role from model formulation to model calibration to computation of model outcomes. In the process, for example, of calibrating a model economy, its steady-state relations are an essential part of what it takes to work backwards from empirical relations among variables to what the model parameters must be in order to be consistent with them. With advances in the development of theory and computers becoming much more powerful, the set of interesting questions that can be addressed with such models has expanded dramatically in the past decade or two. This is true especially for questions that dictate the inclusion of important heterogeneity across current generations and/or across individuals more generally.

In models with a role for the government, anticipated future policy affects economic behavior in earlier periods. For example, future tax policy affects investment behavior today. If we imagine policy to be selected so as to optimize an objective (welfare) function, the resulting policy, in the absence of a commitment mechanism, is generally time inconsistent. Aside from questions about its implementation, then, a consequence is that the formulation of the optimal-policy problem is not recursive. But one can generally convert such a model into a recursive structure by introducing an additional pseudo-state variable – a shadow price – which is subject to its own constraint implied by the model. Similar issues about recursivity, potentially resolved in an analogous manner, arise in many dynamic contracting environments.
----------------------------------------------------------------------------------------------------------
40 Years of EURO: History, Applications, Future Potentials by H.-J.Zimmermann

40 years ago, i.e. in 1972, the world looked quite different from to-day: Logistics were slower and more complicated: The best way to travel from Europe to the USA was by ship,which took between 5 and 13 days. Alternatively one could take a “Super Constellation” and go via Island in 24 hours. There were no electronic booking systems, customs-and passport control at each European Border, but no security systems at airports, no terrorism and no hijacking of planes. Communication was as clumsy: No fax, no email, no courier services, a letter between Europe and oversees took two to three weeks, each single letter had to be typed ,and there were neither social nets nor a www. Professionally there existed three large OR - journals (and a number of small national ones), East and West was separated by the Iron Curtain. “Large” OR - Societies existed in the USA, Japan and Great Britain and in Europe there were a dozen of smaller national OR Societies. There was hardly any communication between these European societies and if one wanted to know what was going on in OR in another European country, the best way was, to ask a colleague in the USA. In the USA Ackoff had stated ( in 1979) “American Operations Research is dead though not yet buried”.

Under these circumstances the presidents of the European OR societies met at the IFORS conference 1972 in Dublin and came to the conclusion, that this situation of OR in Europe was sub-optimal and should be improved. They met again in 1973 and 1974 and decided to organize the first European OR conference at the end of January 1975 in Brussels. There were 500 participants and the representatives of 10 European  countries. In the framework of this conference EURO was founded, 7 European working groups were started, the EURO-bulletins was started and it was decided to prepare the publication of a European OR journal (EJOR).


----------------------------------------------------------------------------------------------------------
On the role of randomness in exact tree search methods by Matteo Fischetti

----------------------------------------------------------------------------------------------------------
Providing a Scientific Basis for Managing Illegal Drugs & Markets by Jonathan Caulkins

----------------------------------------------------------------------------------------------------------
Optimization in Process Systems Enigineering by Igancio Grossmann

Enterprise-wide optimization (EWO) is a new emerging area that lies at the interface of chemical engineering and operations research, and has become a major goal in the process industries due to the increasing pressures for remaining competitive in the global marketplace. EWO involves optimizing the operations of supply, production and distribution activities of a company to reduce costs and inventories. A major focus in EWO is the optimization of manufacturing plants as part of the overall optimization of the supply chain. Major operational items include production planning, scheduling, and control. This talk provides an overview of major modeling and computational challenges in the development of deterministic and stochastic linear/nonlinear mixed-integer optimization models for planning and scheduling for the optimization of plants and entire supply chains that are involved in EWO problems. We illustrate the application of these ideas in four major problems:

a) integration of planning and scheduling in batch processes that lead to large-scale mixed-integer linear programs,
b) optimization of responsive process supply chains that lead to large-scale bicriterion mixed-integer optimization problems,
c) optimization of distribution-inventory planning of industrial gases that lead to integration of planning and vehicle-routing models,
d) optimization of oilfield infrastructures under uncertainty that lead to multistage stochastic programming problems with endogenous uncertain parameters.

We outline the solution methods that have been developed. Also, these problems have been addressed in collaboration with industry, and have led to substantial economic savings.
----------------------------------------------------------------------------------------------------------
Auctions: Why they proliferating and what you need to know to participate by Karla Hoffman

The advent of the Internet has led to the creation of global marketplaces in which sales of everything from low-cost used merchandise to billion dollar government procurements are conducted by auction. While some auction designs have been extremely successful, others have failed disastrously. This talk will describe a variety of alternative auction designs, and will explore why one design is likely to be more appropriate than another for a given application. We will begin with a brief history of auctions, provide reasons for eBay’s spectacular success, and highlight the Internet’s impact on auction theory and practice. We will then move on to a discussion of the strategies that are available to bidders in the most-utilized auction formats, thereby providing each of you with hints on how to be more successful when participating in auctions. Throughout the talk, we will highlight the role that operations research analysts can play in designing, running, and assisting participants in business-to-business and high-stakes government auctions.
----------------------------------------------------------------------------------------------------------
Column Generation by Guy Desaulniers

Column generation is a well-known mathematical programming technique for solving large-scale optimization linear problems. In the mid-1980s, it was shown that it can be successfully embedded in a branch-and-bound framework (yielding a branch-and-price method) for solving integer programs. Since then, it has become the most popular exact methododology for solving several classes of vehicle routing problems. As a fertile testbed, the vehicle routing problem with time windows (VRPTW) played an important role in this success. It consists of finding a set of least-cost vehicle routes to deliver goods to a set of customers. Each customer must be visited exactly once within a given time window and each route must respect vehicle capacity. In this talk, we survey the evolution of the column generation methods developed for the VRPTW, starting from the seminal work of Desrochers, Desrosiers, and Solomon (1992). In particular, we present various path relaxations proposed to avoid solving the NP-hard elementary shortest path subproblem, labeling algorithms used to generate their corresponding columns, and valid inequalities tightening the lower bounds, including those that are directly defined on the master problem variables. We discuss certain acceleration strategies, report computational results, and highlight current and future challenges.
----------------------------------------------------------------------------------------------------------
Stochastic programming - a flexible tool for decision making under uncertainty by Jitka Dupacova

To apply stochastic programming (SP) means primarily to be familiar with the real-life problem in question, its purpose, constraints, and with the available level of information concerning the driving random factors. Even when implementation of complex SP models does frequently require simplifications and/or approximations, their outcome may point at new decision strategies.

We shall focus on the modeling issues. The interplay between the problem setting and the SP model building will be illustrated on selected examples related mainly to water resources management and planning.
----------------------------------------------------------------------------------------------------------
Lines, Timetables, Delays: Models and Trends in Optimization of Public Transport by Anita Schöbel

The talk consists of two parts: In the first part, a state-of-the-art survey about finding lines and timetables in the strategic planning of a public transportation system will be provided, and the problem of delay management, i.e. how to update the system in case of delays will be explored. The second part will discuss ongoing research questions, namely how the routing of the passengers can be included in the planning phases, how an integration of the planning phases can be obtained and tested, and how robustness issues can be integrated. Theoretical and experimental results on these topics will be shown.

Part 1 gives an overview on line planning, timetabling, and delay management. Given an existing public transportation network with its stops (or stations) and direct connections, the first step in the strategic planning of a transport system is to define lines and their frequencies. A line is a path in the public transportation network along which regular service is offered. We discuss various optimization models minimizing either the costs of the lines or maximizing the convenience for the passengers. If the lines have been found, the next step is to design a timetable. There are two different models: Periodic timetables which are repeated on e.g. an hourly basis and aperiodic timetables. The usual aim is to minimize the traveling time for the passengers. Integer programming formulations will be provided for both problem types and algorithmic approaches for finding timetables will be reviewed. Coming to the operational phase, the question of the delay management problem is how to react in case of delays such that the passengers' travel times do not increase too much. This concerns the decision if a punctual bus or train should wait for a delayed feeder bus or train or if it should better depart on time. In railway traffic also the limited capacity of the tracks has to be taken into account, i.e. priority decisions have to be made. Also here the state-of-the art of delay management will be presented.

The three problems discussed in Part 1 can be solved more or less efficiently. However, the algorithms and approaches are still not suitable for solving real-world problems. In part 2 we will hence discuss features that are missing, identify the resulting research questions and show some first solution approaches aiming at making the algorithms work in practice.

A first problem concerns the decision of the passengers. In many papers on line planning, time tabling, and delay management it is assumed that it is already known how the passengers travel, i.e. a passenger's weight is assumed to be known for every edge or activity in the system. This is an unrealistic assumption since the route choice of the passengers depends on the lines, the timetable and on the delay management strategy. We will discuss how the passengers' decisions may be integrated into the optimization process.

Another issue is robustness. It is not helpful to have an exact optimal solution that might get totally meaningless if a small disturbance occurs. Hence, the aim should be to have a robust transportation system which performs well even if the scenario or the input data changes. We exemplary illustrate different concepts on how robustness can be integrated for the timetabling phase. Specialized algorithms for every single planning phase in public transportation are known. However, the best line plan is not helpful if it only allows bad timetables. Hence, some effort should be made to find integrated solutions.

Using our toolbox LinTim we illustrate how decisions made in earlier planning steps can
influence the subsequent planning phases. Among others we show how the quality of a timetable depends on decisions made in the line planning phase, how good the approximation of the passengers' weights fits to the real behavior of the passengers, and how the robustness of a public transport system may be simulated.
----------------------------------------------------------------------------------------------------------
Metaheuristics - the metaphor exposed by Kenneth Sörensen

In recent years, the field of combinatorial optimization has witnessed a true tsunami of "new" metaheuristic methods, most of them based on a metaphor of some natural process. The behavior of virtually any species of insects, the flow of water, musicians playing together, it seems that no ideas are too far-fetched to serve as inspiration to launch yet another metaheuristic. In this tutorial, we will critically investigate whether the resulting methods are truly original, or just a repackaging of old ideas. In general, the usefulness of metaphor-based methods will be put to the test.

On the other side of the spectrum, researchers in metaheuristics are picking up ideas traditionally found in exact methods only, such as an intelligent decomposition of the problem and the use of exact methods to solve subproblems. In some problem domains such as vehicle routing or scheduling, a consensus is starting to condense on which ideas and which methods work and which do not. This is the result of many years of development of ever more powerful metaheuristics, combined with a careful study of the combinatorial properties of the problem. Additionally, deconstructing of a method, combined with statistical testing of the components and parameters of a metaheuristic can reveal those components and parameter settings that truly contribute to the performance.

The main aim of this talk is to provide some guidelines on how to develop an efficient and effective metaheuristic. We will show that the way forward is through the rigorous use of scientific methods, rather than through the indiscriminate introduction of yet another metaphor.
-------------------------------------------------------------------------------------------------------

 How to Make OR the Most Liked Course in the Curriculum? by Erhan Erkut

As teachers of OR, many of us would like to think that OR is one of the most valuable topics in university education. However, past experience shows that some of the students in our classrooms may not agree with this. How do we close this perception gap, and attract the best students to OR? This is just another problem, and if we think we are the best-trained problem solvers in the world, we should be able to overcome it easily. Unfortunately, while we may have exceptional training in analytical thinking and quantitative analysis, many of us lack the tools necessary for strategic planning, brand creation, and reputation management. Furthermore, most of us lack formal training in teaching, which makes matters worse.  

My colleagues at the University of Alberta and I have experimented with various methods and tools over two decades, and we established that an OR curriculum can be very successful even in a business school - a considerably more challenging environment than an engineering school. The winning recipe includes ingredients such as spreadsheets, real-time modeling (“slow learning”), course management system, web tools, on-line communication, large classes, labs, student assistants, videos, guest speakers, on-line exams, and group projects; all delivered with a heavy emphasis on applications, and with a student-centered pedagogical approach. The results have been very positive; the reputation of the introductory course became “most useful”, many of the best students took our electives, all members of our team won teaching awards, and through our collaboration with the industry we established a know-how transfer unit called Centre for Excellence in Operations.

In this tutorial, I will describe the problem we faced, and our attempts to solve it with examples of what worked and what did not, with an emphasis on what audience members could transfer to their institutions. The focus is not only on making one course popular, but on managing the entire student supply chain, complete with a student club, competitions, conferences, internships, and graduate programs. If you are interested in improving the perception and image of OR in your institution through teaching (and strategic planning), you are welcome to attend this session. 

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