2. The Algorithm ...59 3. Convergence Analysis ..., ...60 4. Complexity Analysis ...63 5. Conclusions ...67 References ...67 A Simple Proof for a Result of Ollerenshaw on Steiner Trees ...68 Xiufeng Du, Ding-Zhu Du, Biao Gao, and Lixue Qii 1. Introduction ...68 2. In the Euclidean Plane ...69 3. In the Rectilinear Plane ...70 4. Discussion ...-...71 References ...71 Optimization Algorithms for the Satisfiability (SAT) Problem ...72 Jun Gu 1. Introduction ...72 2. A Classification of SAT Algorithms ...7:3 3. Preliminaries ...IV 4. Complete Algorithms and Incomplete Algorithms ...81 5. Optimization: An Iterative Refinement Process ...86 6. Local Search Algorithms for SAT ...89 7. Global Optimization Algorithms for SAT Problem ...106 8. Applications ...137 9. Future Work ...140 10. Conclusions ...141 References ...143 Ergodic Convergence in Proximal Point Algorithms with Bregman Functions ...155 Osman Guier 1. Introduction ...: ...155 2. Convergence for Function Minimization ...158 3. Convergence for Arbitrary Maximal Monotone Operators ...161 References ...163 Adding and Deleting Constraints in the Logarithmic Barrier Method for LP ...166 D. den Hertog, C. Roos, and T. Terlaky 1. Introduction ...16(5 2. The Logarithmic Darrier Method ...lG8 CONTENTS IX 3. The Effects of Shifting, Adding and Deleting Constraints ...171 4. The Build-Up and Down Algorithm ...177 ...5. Complexity Analysis ...180 References ...184 A Projection Method for Solving Infinite Systems of Linear Inequalities ...186 Hui Hu 1. Introduction ...186 2. The Projection Method ...186 3. Convergence Rate ...189 4. Infinite Systems of Convex Inequalities ...191 5. Application ...193 References ...

2. The Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 3. Convergence Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ., . . . . 60 4. Complexity Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 5. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 A Simple Proof for a Result of Ollerenshaw on Steiner Trees . . . . . . . . . . 68 Xiufeng Du, Ding-Zhu Du, Biao Gao, and Lixue Qii 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 2. In the Euclidean Plane . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 3. In the Rectilinear Plane . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70 4. Discussion . . . . . . . . . . . . -. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 Optimization Algorithms for the Satisfiability (SAT) Problem . . . . . . . . . 72 Jun Gu 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 2. A Classification of SAT Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7:3 3. Preliminaries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IV 4. Complete Algorithms and Incomplete Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . 81 5. Optimization: An Iterative Refinement Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86 6. Local Search Algorithms for SAT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 7. Global Optimization Algorithms for SAT Problem . . . . . . . . . . . . . . . . . . . . . . . . 106 8. Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137 9. Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140 10. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143 Ergodic Convergence in Proximal Point Algorithms with Bregman Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155 Osman Guier 1. Introduction . . .: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155 2. Convergence for Function Minimization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158 3. Convergence for Arbitrary Maximal Monotone Operators . . . . . . . . . . . .

Humanitarian logistics is a complex science because actors are compelled to work with outmost speed in interrupted environments with unknown players. Even more complex are civil-military relations because as studies reveal, the differences between these two actors run deep. This work examines civil-military relations in the preparedness and response phase of humanitarian crises by developing a frame of reference, setting forth operational and theoretical definitions, examining overlapping supply chains, civil-military cooperation framework and proposing a working model. Data collection is based on two NGOs and a military task force, and this data analyzed vis-a-vis the frame of reference. From the analysis, some conclusions were drawn. First, a number of strategies are employed during the preparedness and response phase. Also, overlapping roles generate both positive and negative impact. Meanwhile, different organizational structures and funding outlay mean differences in how activities are coordinated and information shared. Lastly, cooperation, trust, information sharing and coordination are closely linked when finding a strategic fit among actors.

As current silicon-based microelectronic devices and circuits are approaching their fundamental limits, the research field of nanoelectronics is emerging worldwide. Materials other than silicon and device principles other than complementary metal-oxide-semiconductor (CMOS) are being investigated. With this background, the present book focuses on nanoelectronic devices in InGaAs/InP based on ballistic and quantum effects. The main material studied was a modulation doped InGaAs/InP two-dimensional electron gas. The book covers mainly three types of devices and their twofold integration: in-plane gate transistors, three-terminal ballistic junctions and quantum dots. Novel device properties were studied in detail. The author hopes the results presented in this book to be a valuable contribution to the nanoelectronic research on InP-based semiconductors. The book should be interesting to semiconductor material scientists, device physicists and electronic engineers.