During the last decade, many novel approaches have been considered for dealing with computationally difficult discrete optimization problems. Such approaches include interior point methods, semidefinite programming techniques, and global optimization. More efficient computational algorithms have been developed and larger problem instances of hard discrete problems have been solved. This progress is due in part to these novel approaches, but also to new computing facilities and massive parallelism. This volume contains the papers presented at the workshop on 'Novel Approaches to Hard Discrete Optimization'. The articles cover a spectrum of issues regarding computationally hard discrete problems.
On the distribution of values in the quadratic assignment problem by A. Barvinok and T. Stephen Modeling and optimization in massive graphs by V. Boginski, S. Butenko, and P. M. Pardalos A tale on guillotine cut by M. Cardei, X. Cheng, X. Cheng, and D.-Z. Du Wavelength assignment algorithms in multifiber networks by M. X. Cheng, Z. Gong, X. Huang, H. Zhao, X. Jia, and D. Li Indivisibility and divisbility polytopes by D. Coppersmith and J. Lee The dual active set algorithm and the iterative solution of linear programs by W. W. Hager Positive eigenvalues of generalized words in two Hermitian positive definite matrices by C. J. Hillar and C. R. Johnson Semi-infinite linear programming approaches to semidefinite programming problems by K. Krishnan and J. E. Mitchell SDP versus LP relaxations for polynomial programming by J. B. Lasserre An approximation scheme for the rectilinear Steiner minimum tree in presence of obstructions by M. Min, S. C.-H. Huang, J. Liu, E. Shragowitz, W. Wu, Y. Zhao, and Y. Zhao A convex feasibility problem defined by a nonlinear separation oracle by F. S. Mokhtarian Efficient algorithms for the smallest enclosing ball problem in high dimensional space by G. Zhou, J. Sun, and K.-C. Toh.