This book discusses large-scale optimization problems involving systems made up of interconnected subsystems. The main viewpoint is to break down the overall optimization problem into smaller, easier-to-solve subproblems, each involving one subsystem (decomposition), without sacrificing the objective of achieving the global optimum, which requires an iterative process (coordination). This topic emerged in the 70's in the context of deterministic optimization. The present book describes the main principles and methods of decomposition-coordination using typical situations, then proposes a general framework that makes it possible to construct well-behaved algorithms and to study their convergence. This theory is presented in the context of deterministic as well as stochastic optimization, and has been taught by the authors in graduate courses and implemented in numerous industrial applications. The book also provides exercises and problems with answers to illustrate the potential of this approach.
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