Algorithm engineering: bridging the gap between algorithm theory and practice
Algorithm engineering: bridging the gap between algorithm theory and practice
Analysis of evolutionary algorithms: from computational complexity analysis to algorithm engineering
Proceedings of the 11th workshop proceedings on Foundations of genetic algorithms
Shortest-path queries in static networks
ACM Computing Surveys (CSUR)
| Hi-index | 0.00 |
This paper defines algorithm engineering as a general methodology for algorithmic research. The main process in this methodology is a cycle consisting of algorithm design, analysis, implementation and experimental evaluation that resembles Popper's scientific method. Important additional issues are realistic models, algorithm libraries, benchmarks with real-world problem instances, and a strong coupling to applications. Algorithm theory with its process of subsequent modelling, design, and analysis is not a competing approach to algorithmics but an important ingredient of algorithm engineering.