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Sixth Joint Operations Research Days
Organizing committee:
We invite members of IBM research staff and Swiss OR researchers to submit abstracts about their recent research. We strongly encourage PhD students to present their results. There is no registration fee. Registration will be confirmed on a first come-first served basis. Keynotes speakers
Schedule
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| Thursday | ||||
| 10:00 | 10:30 | Coffee | ||
| Chairperson | Jon Lee | |||
| 10:30 | 11:15 | PACH | EPFL | Conflict-free coloring |
| 11:15 | 11:20 | Short break | ||
| Chairperson | Janos Pach | |||
| 11:20 | 11:40 | Trautmann | U Bern | Resource Allocation Capabilities of Commercial Software Packages for Project Management: An Experimental Performance Analysis |
| 11:40 | 12:00 | Mastrolilli | IDSIA | (Acyclic) Job Shops are Hard to Approximate |
| 12:00 | 12:20 | Stauffer | IBM | Decentralized decision making is close to optimal for one-warehouse multi-retailers systems |
| 12:20 | 14:20 | Lunch | ||
| Chairperson | Luca Gambardella | |||
| 14:20 | 14:40 | Faltings | EPFL | Distributed Algorithms for Constraint Optimization |
| 14:40 | 15:00 | Shankar | IBM | A Novel Algorithm for stochastic Linear Programs with a Conditional-Value-at-Risk Objective and Conditional-value-at-risk Constraints |
| 15:00 | 15:20 | Klatte | U Zürich | Generalized semi-infinite programs: reduction approach and a nonsmooth Newton method |
| 15:20 | 15:50 | Coffee break | ||
| Chairperson | Komei Fukuda | |||
| 15:50 | 16:35 | EISENBRAND | EPFL | Integer Programming and the Geometry of Numbers |
| 16:35 | 16:40 | Short break | ||
| Chairperson | Friedrich Eisenbrand | |||
| 16:40 | 17:00 | Foniok | ETHZ | Polynomial Pivoting for K-LCP: A Proof Using Unique-Sink Orientations |
| 17:00 | 17:20 | Sviridenko | IBM | Approximation Algorithms for the One-Warehouse Multi-Retailer problem |
| 17:20 | 17:40 | Shmonin | EPFL | Integer programming gaps |
| 19:30 | Dinner at Hotel Continental (click here for a map) | |||
| Friday | ||||
| Chairperson | Gerald Reiner | |||
| 09:00 | 9:20 | Horch | ABB | The Challenge of Increasing Complexity in Production Optimization |
| 9:20 | 9:40 | Montemanni | IDSIA | Heuristic construction of Constant GC-content DNA codes |
| 9:40 | 10:10 | Coffee break | ||
| Chairperson | Eleni Pratsini | |||
| 10:10 | 10:55 | SCHMEDDERS | U Zürich | Solving Dynamic Games |
| 10:55 | 11:00 | Short break | ||
| Chairperson | Karl Schmedders | |||
| 11:00 | 11:20 | Palvolgyi | EPFL | Decomposability of polygon coverings |
| 11:20 | 11:40 | Babonneau | Ordecsys | A partitioning algorithm for the network loading problem |
| 11:40 | 12:00 | Vacca | EPFL | Two-stage column generation: a novel framework |
| 12:00 | 14:00 | Lunch | ||
| Chairperson | Michel Bierlaire | |||
| 14:00 | 14:20 | Fulek | EPFL | Intersecting convex sets by rays |
| 14:20 | 14:40 | Tiemessen | IBM | Heuristics for Inventory Replenishment and Service Request Fulfillment in Spare Parts Networks |
| 14:40 | 14:50 | Short break | ||
| Chairperson | Norbert Trautmann | |||
| 14:50 | 15:10 | Rothvoss | EPFL | A PTAS for Static Priority Real-Time Scheduling with Resource Augmentation |
| 15:10 | 15:30 | Smorodinsky | EPFL | Conflict-Free coloring made stronger |

18 abstracts
Title: A partitioning algorithm for the network loading problem
Abstract: We present a partitioning algorithm for the network loading problem (NLP). The NLP consists of installing least cost integer capacities on the arcs that are sufficient to handle a network flow that meets the demands. Our solution method is a Benders partitioning scheme. The master program is a pure integer programming problem in the space of capacities. The subproblem is a continuous optimization problem ; it tests whether the integer capacities generated by the master program is sufficient to support flows that meet the demands. It also computes supporting hyperplanes to the set of feasible fractional capacities. The subproblem makes it possible to construct a polyhedral relaxation of the set of feasible capacities while the master program looks for interesting integer solutions within that polyhedral relaxation. Since the effort of computing integer solutions is entirely left to a pure integer programming solver (CPLEX in our case), the main advantage of our solution method is its simplicity. It also appear to be efficient on some problems.
Title: Distributed Algorithms for Constraint Optimization
Abstract: We consider problems where multiple agents have to coordinate their decisions because of shared resources or other interdependencies, and this coordination problem can be formulated as a problem of constraint optimization. We survey distributed algorithms that allow such problems to be solved without a central authority.
Title: Polynomial Pivoting for K-LCP: A Proof Using Unique-Sink Orientations
Abstract: Joint work with K. Fukuda, B. Gärtner, H.-J. Lüthi. Unique-sink orientations of cubes provide a simple combinatorial description of simple principal pivoting methods for the linear complementarity problem (LCP). It had been known that there exists a pivot rule for the simple principal pivoting method that takes only a linear number of pivots to solve the K-matrix LCP. Using unique-sink orientations, we were able to show that this is actually true for any pivot rule.
Title: Intersecting convex sets by rays
Abstract: What is the smallest number t=t(n) such that for any collection of n pairwise disjoint convex sets in d-dimensional Euclidean space, there is a point such that any ray (half-line) emanating from it meets at most sets of the collection? This question of Urrutia is closely related to the notion of regression depth introduced by Rousseeuw and Hubert (1996). We show the following: Given any collection C of n pairwise disjoint compact convex sets in d-dimensional Euclidean space, there exists a point p such that any ray emanating from p meets at most (dn+1)/(d+1) members of C. There exist collections of n pairwise disjoint (i) equal length segments or (ii) disks in the Euclidean plane such that from any point there is a ray that meets at least 2n/3-2 of them. We also determine the asymptotic behavior of t(n) when the convex bodies are fat and of roughly equal size.
Title: The Challenge of Increasing Complexity in Production Optimization
Abstract: Today’s industries are more than ever enforced to lower their operational costs, largely due to a harder global competition. One related target is to ensure that the overall result of earlier isolated optimization tasks is “globally optimal”, i.e. the decisions done on different levels or in different process sections do not negate, or counteract, each other. This has created a trend and more importantly a need of increased information sharing between various decision-support systems. Inevitably, information sharing leads to more complex optimization systems as the models need to cover larger problem entities in order to merge previously separate optimization targets. Also, aspects earlier not considered may have to be included. Another complexity increase arises from the communication need between the tasks. The earlier isolated problems (e.g. machine-specific production planning) become networked, which means that not all goals can be derived from local facts alone, but at least some must be handled globally. Apart from the cultural change and integration challenges, it is very important to ensure that optimization methodologies can cope with the new demands. As no single strategy suffices to cover all industrial problem solutions – even within one plant – a system of optimization systems needs to be designed by combination of methods, partitioning of problems and modeling collaboration. Some strategies of combining solution methods will be shown, followed by project examples carried out at ABB Corporate Research. Finally, future challenges and opportunities are discussed.
Title: Generalized semi-infinite programs: reduction approach and a nonsmooth Newton method
Abstract: (in collaboration with Stephan Bütikofer IOR, UZH) We study nonlinear programs in finite dimensions with infinitely many inequality constraints, where the set of constraint indices depends on the state variables. Supposing strong regularity assumptions, the problem may be reduced to a standard nonlinear program with finitely many constraints, but now including some kind of nonsmoothness. We present this reduction procedure as well as convergence results and first numerical experiments for a nonsmooth Newton method for solving this type of models.
Title: (Acyclic) Job Shops are Hard to Approximate
Abstract: Understanding the approximability of the job shop problem is considered one of the most prominent open problems in scheduling theory. Even though the best approximation algorithms have worse than logarithmic performance guarantee, the only known inapproximability result says that it is NP-hard to approximate acyclic job shops within a factor less than~$5/4$. For every $epsilon >0$, we show that the (acyclic) job shop problem cannot be approximated within ratio $O(log^{1-epsilon} lb)$, unless $NP$ has quasi-polynomial Las-Vegas algorithms, and where $lb$ denotes a trivial lower bound on the optimal value. This almost matches the best known results for acyclic job shops, since an $ {O}(log^{1+epsilon} lb)$-approximate solution can be obtained in polynomial time for every $epsilon>0$. Recently, a PTAS was given for the job shop problem, where the number of machines emph{and} the number of operations per job are assumed to be constant. Under $P ot = NP$, and when the number $mu$ of operations per job is a constant, we provide an inapproximability result whose value grows with $mu$ to infinity. Moreover, we show that the problem with two machines has no PTAS, unless $NP$ has quasi-polynomial algorithms. These results show that the restrictions on the number of machines and operations per job are necessary to obtain a PTAS. Finally, we solve (negatively) an open question raised by Bansal et al., by showing that even the preemptive variant with three machines has no PTAS.
Title: Heuristic construction of Constant GC-content DNA codes
Abstract: DNA codes are sets of words of fixed length n over the alphabet {A, C, G, T} which satisfy a number of combinatorial conditions. They have application in DNA computing, in DNA microarray technologies and as molecular bar codes. The combinatorial conditions considered are (i) minimum Hamming distance d, (ii) fixed GC content and, in some cases (iii) minimum distance d between any codeword and the reverse Watson-Crick complement of any codeword. The problem is to find DNA codes with the maximum number of codewords. The construction of DNA codes is studied from an algorithmic perspective. Four local search algorithms are developed and combined in a variable neighbourhood search framework. The algorithm has been run extensively. Over 254 problems considered, it was able to match or improve the best known lower bounds in 180 cases, with 52 new bests. (join work with D.H. Smith, University of Glamorgan, UK)
Title: Decomposability of polygon coverings
Abstract: A family of sets is a {em $k$-fold} covering of a point set if every point is contained in at least $k$ of the sets. A covering is {em decomposable} if the sets can be partitioned into two ($1$-fold) coverings. We say that a geometric set is {em cover-decomposable}, if there exists a $k$ such that every $k$-fold covering of {em any point set} in the plane by its translates is decomposable.\ We show which polygons are cover-decomposable. It turns out that every convex polygon is cover-decomposable and almost every concave polygon is not cover-decomposable.
Title: A PTAS for Static Priority Real-Time Scheduling with Resource Augmentation
Abstract: We present a polynomial time approximation scheme for the real-time scheduling problem with fixed priorities when resource augmentation is allowed. For a fixed epsilon > 0, our algorithm computes an assignment using at most (1+epsilon)*OPT +1 processors in polynomial time, which is feasible if the processors have speed 1+epsilon. This is joint work with Fritz Eisenbrand.
Title: Integer programming gaps
Abstract: We consider the problem of finding the maximum difference between the optimum value of ab integer program and its linear programming relaxation, as the right-hand side vector in the constraint matrix varies over a given polyhedron. It turns out that there is a polynomial algorithm for this problem if the number of variables is fixed.
Title: Conflict-Free coloring made stronger
Abstract: In FOCS 2002, Even et al. showed that any set of $n$ discs in the plane can be Conflict-Free colored with a total of at most $O(\log n)$ colors. Namely, it can be colored with $O(\log n)$ colors such that for any (covered) point $p$ there is some disc whose color is distinct from all other colors of discs containing $p$. They also showed that this bound is asymptotically tight. We prove the following stronger result: Any set of $n$ discs in the plane can be colored with a total of at most $O(k \log n)$ colors such that for any point $p$ that is covered by at least $k$ discs, there are at least $k$ distinct discs each of which is colored by a color distinct from all other discs containing $p$ and for any point $p$ covered by at most $k$ discs, all discs covering $p$ are colored distinctively. We call such a coloring a {\em $k$-Strong Conflict-Free} coloring. We extend this result to pseudo-discs and arbitrary regions with linear union-complexity. Joint work with Elad Horev and Roi Krakovski
Title: Decentralized decision making is close to optimal for one-warehouse multi-retailers systems
Abstract: Roundy developped in 1985 a centralized algorithm to manage efficiently (within 2% of optimality) the inventory of a simple distribution system consisting of one warehouse and many retailers, where the retailers are facing continuous demands with constant rates. In order to ensure near optimality of the global system, the retailers usually have to increase their own optimal inventory costs. In practice tough, for ease of implementation or for accounting purpose, decisions are often taken in a decentralized way and all the retailers and the central warehouse try to minimize their own inventory costs independently of the others. In this talk we show that in the continuous rate setting, this practical approach is ususally good (within 6% of optimal in average) and is provably close to optimal (within 1.2748 of optimal in the worst case).
Title: A Novel Algorithm for stochastic Linear Programs with a Conditional-Value-at-Risk Objective and Conditional-value-at-risk Constraints
Abstract: Conditional-Value-at-Risk (CVaR), as a mathematical programming-friendly risk measure, was first introduced by Uryasev & Rockafellar (2000). Using a discrete sample-approximation of the underlying stochastic coefficients, they provided a linear reformulation for stochastic linear programs with CVaR objective/constraints, which can then be solved using general-purpose linear programming solvers. An important point to note in this reformulation is that the resulting number of additional decision variables & the number of additional constraints, scale linearly with the size of samples. More recently, Kunzi-Bay and Mayer (2006) presented a two-stage, stochastic programming interpretation of the above linear reformulation for the specific case of a CVaR Objective, and developed a computationally efficient algorithm, CVarMin, to address linear CVaR optimization in the objective function, observing an order of magnitude speed-up. We present a novel, computationally efficient algorithm for stochastic linear programs with both Conditional-Value-at-Risk (CVaR) Objective and Conditional-value-at-risk Constraints, retaining the above discrete sample-approximation of the stochastic coefficients. We start with a reformulation that is different from the above references, and iteratively construct and solve a sequence of compact-sized linear optimization problems. We also show that the resulting sequence converges to the true optimal solution of the sample-predicated linear program. The problem size in each iteration of the sequence is unaffected by the size of random samples, which makes it very efficient for large-scale problems. A comparison with the general-purpose linear reformulation of Uryasev & Rockafellar suggests at least an order of magnitude speed-up of computational time, and more improvement with increasing number of CVaR constraints and size of samples. Applications include practical problems, such as, portfolio optimization.
Title: Approximation Algorithms for the One-Warehouse Multi-Retailer problem
Abstract: Deterministic inventory theory provides streamlined optimization models that attempt to capture tradeoffs in managing the flow of goods through a supply chain. We will consider two well-studied deterministic inventory models, called the {em one-warehouse multi-retailer problem} (OWMR) and its special case the {em joint replenishment problem} (JRP), and give approximation algorithms with improved performance guarantees; more specifically, we give a 1.8-approximation algorithm for both problems. Our results are based on an LP-rounding approach and improve previous results of Levi, Roundy and Shmoys. Our results also show strong integrality gaps for the corresponding linear programs.
Title: Heuristics for Inventory Replenishment and Service Request Fulfillment in Spare Parts Networks
Abstract: Motivated by IBMs spare parts logistics, we present a distributed inventory network for spare parts where service requests can usually be solved from multiple local warehouses. We consider a single-item, multi-location, single-echelon model with service level constraints and centralized control. We discuss an inventory controller that consists of a decision rule for selecting the local warehouse that sends out a part to a waiting customer, and a heuristic for calculating replenishment orders. Replenishment orders are calculated by solving a simple but state-dependent LP model at carefully selected moments in time. What differentiates the proposed solution from many existing solutions is that we use stock level information from the entire network to jointly optimize replenishment decisions at all local warehouses. We have carried out simulation experiments to evaluate the proposed solution at different scenarios. We present and discuss the results and draw conclusions.
Title: Resource Allocation Capabilities of Commercial Software Packages for Project Management: An Experimental Performance Analysis
Abstract: We report on the results of an experimental analysis where we have compared the resource allocation capabilities of recent versions of 5 commercial project management software packages against state-of-the-art solution methods from the literature. For our analysis, we have used 1560 RCPSP instances from the standard test set PSPLIB. The results indicate that using the automatic resource allocating feature of those packages may result in project durations that are considerably longer than necessary, in particular when the resource scarcity is high or when the number of activities is large.
Title: Two-stage column generation: a novel framework
Abstract: Column generation has been intensively used in the last decades to compute good quality lower bounds for combinatorial problems reformulated through Dantzig-Wolfe decomposition. In this work we propose a novel framework to cope with problems in which the structure of the original formulation, namely the presence of a combinatorial number of decision variables, does not allow for straightforward reformulation. The basic idea is to start from a meaningful subset of original variables, apply the DW reformulation to the subset, solve the reformulation with column generation and perform the explicit pricing on original variables retracing back the reformulation and using complementary-slackness conditions. The Discrete Split Delivery Vehicle Routing Problem with Time Windows (DSDVRPTW) is used as an illustration for the method, which provides a new exact approach to the problem. Preliminary computational experiments are reported. This is joint work with Matteo Salani.

All participants, including speakers, must register using the following registration forms.
Registration deadline: August 25, 2008.
Today is March 24, 2010.
Sorry, the deadline is over.
Click here to submit an abstract.
Current number of registered participants: 47
| Alipour | Masoud | EPFL |
| Antonini | Gianluca | IBM ZRL |
| Babonneau | Frédéric | Ordecsys |
| Bielser | Mike | IOR, University of Zurich |
| Bierlaire | Michel | TRANSP-OR, EPFL |
| Boedi | Richard | IBM Research |
| Cope | Eric | IBM Zurich Research Lab |
| Eisenbrand | Friedrich | DISOPT, EPFL |
| Flötteröd | Gunnar | Berlin Institute of Technology |
| Foniok | Jan | ETH Zurich |
| Fukuda | Komei | ETH Zurich |
| Fulek | Radoslav | EPFL |
| Gambardella | Luca Maria | IDSIA |
| Horch | Alexander | ABB Corporate Research, Ladenburg, Germany |
| Klatte | Diethard | IOR, UZH |
| Labbi | Abdel | IBM Research - Zurich |
| Laumanns | Marco | IFOR, ETH Zurich |
| Lee | Jon | IBM TJ Watson Research Center |
| Liebling | Thomas | EPFL |
| Mastrolilli | Monaldo | IDSIA |
| Mayer | Janos | Institute for Operations Research, University of Zurich |
| Montemanni | Roberto | IDSIA |
| Nesterov | Yurii | CORE- UCL Belgium |
| Pach | Janos | DCG, EPFL |
| Palvolgyi | Domotor | EPFL |
| Pratsini | Eleni | IBM Zurich Research Lab |
| Prodon | Alain | EPFL - ROSO |
| Ray | Bonnie | IBM Watson Research Center |
| Reiner | Gerald | Université de Neuchâtel |
| Robin | Thomas | TRANSP-OR, EPFL |
| Rosta | Vera | Renyi Institute Budapest |
| Rothvoss | Thomas | DISOPT, EPFL |
| sallam | karam | department assistant in faculty of computer and informatics-operation research dept |
| Schmedders | Karl | University of Zurich |
| Shmonin | Gennady | DISOPT, EPFL |
| Smorodinsky | Shakhar | Ben Gurion University |
| Stauffer | Gautier | IBM Zurich Research Lab |
| Subramanian | Dharmashankar | IBM Research |
| Sviridenko | Maxim | IBM TJ Watson Research Center |
| Tiemessen | Harold | IBM Research |
| Trautmann | Norbert | BWL, University of Bern |
| Uldry | Marc | Université de Fribourg - DIUF |
| Vacca | Ilaria | TRANSP-OR, EPFL |
| Vial | Jean-Philippe | ORDECSYS |
| von Bergen | Silvia | IOR, University of Zurich |
| Widmer | Marino | Université de Fribourg - DIUF |
| Zenklusen | Rico | ETH Zurich |
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