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Anticipatory Optimization for Dynamic Decision Making (Operations Research/Computer Science Interfaces Series)

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Anticipatory optimization for dynamic decision making relies on a number of different scientific disciplines. On a general level, the foundations of the field may be localized at the intersection of operations research, computer science and decision theory. Closer inspection reveals the important role of branches such as simulation, metaheuristics, Markov decision processes, dynamic programming and data mining. Moreover, realization of an advanced approach to anticipatory optimization is hardly possible without supporting database technology and without profound knowledge about the problem domain under consideration.

However, bringing together all these elements is not an end in itself. Rather the integral nature of anticipatory optimization reflects the complexity of dynamic decision problems as they increasingly occur within various operational contexts. Ultimately, the need for anticipatory optimization results from the fact that today many companys’ operations are carried out under strongly dynamic and uncertain conditions.

Starting from a discussion of origins and impacts of these conditions, the following chapters elaborate on anticipatory optimization for dynamic decision making. The presentation has three major facets. First of all, it focuses on consistent integration of the methodological building blocks required for making an anticipatory decision. Moreover, the presentation distinguishes between different degrees of anticipation that may be realized by such a decision. Last but not least, an exemplary class of dynamic decision problems from the field of vehicle routing is considered for detailed investigation.

Going all the way from understanding the nature of dynamic decision making to realization of anticipatory optimization at its best involves certain challenges. Facing these challenges has been my everyday experience throughout the past years of research. I am grateful for this experience as it comprises numerous fascinating insights into the subject of dynamic decision making and beyond.

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