http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
Online Optimization of Large Scale Systems
Whether costs are to be reduced, profits to be maximized, or scarce resources to be used wisely, optimization methods are available to guide decision making. In online optimization the main issue is: incomplete data; and the scientific challenge: How well can an online algorithm perform? Can one guarantee solution quality, even without knowing all data in advance? In real-time optimization there is an additional requirement, decisions have to be computed very fast, fast in relation to the time frame of the instance we consider. Online and real-time optimization problems occur in all branches of optimization: linear, nonlinear, integer, stochastic. These areas have developed their own techniques but they are addressing the same issues: quality, stability, and robustness of the solutions. To fertilize this emerging topic of optimization theory and to foster cooperation between the different branches of optimization, the Deutsche Forschungsgemeinschaft (DFG) has supported a Priority Programme "Online Optimization of Large Systems". This volume contains "background articles" and "research articles". Background articles are intended to give an overview over the basic theory in the respective area and are accessible to graduate math students. Research articles summarize the progress in a project achieved in the Priority Programme.
I. Optimal Control for Ordinary Differential Equations -- II. Optimal Control for Partial Differential Equations -- III. Moving Horizon Methods in Chemical Engineering -- IV. Delay Differential Equations in Medical Decision Support Systems -- V. Stochastic Optimization in Chemical Engineering -- VI. Stochastic Trajectory Planning in Robot Control -- VII. Integer Stochastic Programming -- VIII. Combinatorial Online Planning in Transportation -- IX. Real-Time Annealing in Image Segmentation.
edited by Martin Grötschel, Sven O. Krumke, Jörg Rambau.