Reverse search for enumeration
Discrete Applied Mathematics - Special volume: first international colloquium on graphs and optimization (GOI), 1992
Enumerating the k best plane spanning trees
Computational Geometry: Theory and Applications
How to Employ Reverse Search in Distributed Single Source Shortest Paths
SOFSEM '01 Proceedings of the 28th Conference on Current Trends in Theory and Practice of Informatics Piestany: Theory and Practice of Informatics
Smart Enumeration: A Systematic Approach to Exhaustive Search
Integrated Circuit and System Design. Power and Timing Modeling, Optimization and Simulation
Expert Systems with Applications: An International Journal
Online parameter tuning for object tracking algorithms
Image and Vision Computing
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For half a century since computers came into existence, the goal of finding elegant and efficient algorithms to solve "simple" (well-defined and well-structured) problems has dominated algorithm design. Over the same time period, both processing and storage capacity of computers have increased by roughly a factor of a million. The next few decades may well give us a similar rate of growth in raw computing power, due to various factors such as continuing miniaturization, parallel and distributed computing. If a quantitative change of orders of magnitude leads to qualitative advances, where will the latter take place? Only empirical research can answer this question. Asymptotic complexity theory has emerged as a surprisingly effective tool for predicting run times of polynomial-time algorithms. For NP-hard problems, on the other hand, it yields overly pessimistic bounds. It asserts the non-existence of algorithms that are efficient across an entire problem class, but ignores the fact that many instances, perhaps including those of interest, can be solved efficiently. For such cases we need a complexity measure that applies to problem instances, rather than to over-sized problem classes. Combinatorial optimization and enumeration problems are modeled by state spaces that usually lack any regular structure. Exhaustive search is often the only way to handle such "combinatorial chaos". Several general purpose search algorithms are used under different circumstances. We describe reverse search and illustrate this technique on a case study of enumerative optimization: enumeratingt he k shortest Euclidean spanning trees.