Many recent caching systems aim to improve hit ratios, but there is no good sense among practitioners of how much further hit ratios can be improved. In other words, should the systems community continue working on this problem? Currently, there is no principled answer to this question. Most prior work assumes that objects have the same size, but in practice object sizes often vary by several o...

This paper presents a faster algorithm for the M-convex submodular flow problem, which is a generalization of the minimum-cost flow problem with an M-convex cost function for the flow-boundary, where an M-convex function is a nonlinear nonseparable discrete convex function on integer points. The algorithm extends the capacity scaling approach for the submodular flow problem by Fleischer, Iwata ...

In theory, combinatorial auctions can provide significant benefits in many real-world applications, such as truckload procurement. In practice, however, the use of such auctions has been greatly limited by the need for bidders to bid on an exponential number of bundles and for the auctioneer to solve an exponentially large winner-determination problem. We address these challenges for VCG combin...

Image-based localization is an important problem in robotics and an integral part of visual mapping and navigation systems. An approach to robustly match images to previously recorded ones must be able to cope with seasonal changes especially when it is supposed to work reliably over long periods of time. In this paper, we present a novel approach to visual localization of mobile robots in outd...

This paper deals with the assignment of a type of task to each member of a multi-function staff (each worker is able to perform a given subset of types of tasks, possibly with a priority index associated to each element of the subset). The resulting number of workers for each type of task must be not less than a given lower bound and as close as possible to another given value. The objectives a...

Economies of scale often appear as decreasing marginal costs, but may also occur as a constraint that at least a minimum quantity should be produced or nothing at all. Taking the latter into account can support decisions about keeping a production site, setting up a new one, establishing new routes in logistics network, and many more. In our work, we define the corresponding problem Minimum Cos...

In this paper, we study inverse optimization problems defined as follows: Let S denote the set of feasible solutions of an optimization problem P, let c be a specified cost vector, and x0 be a given feasible solution. The solution x0 may or may not be an optimal solution of P with respect to the cost vector c. The inverse optimization problem is to perturb the cost vector c to d so that x0 is a...

In this paper, we consider the inverse spanning tree problem. Given an undirected graph Go = (Ni, AO) with n nodes, mn arcs, an arc cost vector c, and a spanning tree T, the inverse spanning tree problem is to perturb the arc cost vector c to a vector d so that T is a minimum spanning tree with respect to the cost vector d and the cost of perturbation given by Id c = L(l j) Aldij ciil is minimu...

In this paper we discuss the parallel asynchronous implementation of the classical primaldual method for solving the linear minimum cost network flow problem. Multiple augmentations and price rises are simultaneously attempted starting from several nodes with possibly outdated price and flow information. The results are then merged asynchronously subject to rather weak compatibility conditions....

This paper addresses a large-scale power plant maintenance scheduling and production planning problem, which has been proposed by the ROADEF/EURO Challenge 2010. We develop two lower bounds for the problem: a greedy heuristic and a flow network for which a minimum cost flow problem has to be solved. Furthermore, we present a solution approach that combines a constraint programming formulation o...