In this supplementary material we first provide the parameters we used in our discrete optical flow model. Next, we present histograms of the statistics of optical flow for MPI Sintel and KITTI which we use to select the upper bounds for the magnitude of flow vectors in our model. Finally, more detailed qualitative results on the processed datasets are shown, including comparisons to state-of-t...

This chapter is dedicated to Memetic Algorithms for Discrete Optimization. It begins with a general survey, and then explains in depth the key ingredients of a successful MA. A particular attention is given to the following issues: Design of semantic combination operators, development of dedicated local search procedures and management of population diversity. Several other important issues are...

Numerical simulation of structural response is a challenging issue in earthquake engineering and there has been remarkable progress in this area in the last decade. Endurance Time (ET) method is a new response history based analysis procedure for seismic assessment and structural design in which structures are subjected to a gradually intensifying dynamic excitation and their seismic performanc...

This chapter is dedicated to Memetic Algorithms for Discrete Optimization. It begins with a general survey, and then explains in depth the key ingredients of a successful MA. A particular attention is given to the following issues: Design of semantic combination operators, development of dedicated local search procedures and management of population diversity. Several other important issues are...

In the last decade our capability of solving integer programming problems has increased dramatically due to the effectiveness of cutting plane methods based on polyhedral investigations. Polyhedral cutting planes have become central features in optimization software packages for integer programming. Here we present some of the important polyhedral methods used in discrete optimization. We discu...

The bandwidth minimization problem is of significance in network communication and related areas. Let G be a graph of n vertices. The two-dimensional bandwidth B2(G) of G is the minimum value of the maximum distance between adjacent vertices when G is embedded into an n × n grid in the plane. As a discrete optimization problem, determining B2(G) is NP-hard in general. However, exact results for...

By leveraging semantic (label) information, supervised hashing has demonstrated better accuracy than unsupervised hashing in many real applications. Because the hashing-code learning problem is essentially a discrete optimization problem which is hard to solve, most existing supervised hashing methods try to solve a relaxed continuous optimization problem by dropping the discrete constraints. H...

—In order to solve discrete optimization problems, this paper proposed a discrete bacterial foraging algorithm (DBFA) based on the idea of bacterial foraging optimization (BFO). The proposed DBFA applies binary encoding, and thus has the advantages of solving both discrete and continuous optimization problems. Also, according to sharing experiences of bacterium, we use the rotation step to upd...