Benchmarking in digital circuit design
MINO'08 Proceedings of the 7th WSEAS International Conference on Microelectronics, Nanoelectronics, Optoelectronics
Significance-Driven Graph Clustering
AAIM '07 Proceedings of the 3rd international conference on Algorithmic Aspects in Information and Management
Benchmarking in digital circuit design automation
WSEAS Transactions on Circuits and Systems
Finding non-dominated solutions in bi-objective integer network flow problems
Computers and Operations Research
Mixed models for the analysis of local search components
SLS'07 Proceedings of the 2007 international conference on Engineering stochastic local search algorithms: designing, implementing and analyzing effective heuristics
Algorithm engineering: bridging the gap between algorithm theory and practice
Algorithm engineering: bridging the gap between algorithm theory and practice
Multicriteria 0-1 knapsack problems with k-min objectives
Computers and Operations Research
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Statistical analysis is a powerful tool to apply when evaluating the performance of computer implementations of algorithms and heuristics. Yet many computational studies in the literature do not use this tool to maximum effectiveness. This paper examines the types of data that arise in computational comparisons and presents appropriate techniques for analyzing such data sets. Case studies of computational tests from the open literature are re-evaluated using the proposed methods in order to illustrate the value of statistical analysis for gaining insight into the behavior of the tested algorithms.