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» Solving iterated functions using genetic programming
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129
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GECCO
2008
Springer
132views Optimization» more  GECCO 2008»
15 years 4 months ago
Hybridizing an evolutionary algorithm with mathematical programming techniques for multi-objective optimization
In recent years, the development of multi-objective evolutionary algorithms (MOEAs) hybridized with mathematical programming techniques has significantly increased. However, most...
Saúl Zapotecas Martínez, Carlos A. C...
122
Voted
ICSM
2002
IEEE
15 years 8 months ago
A Case Study of Unanticipated Incremental Change
Incremental changes add new functionality and properties to software. They are the core of software evolution, maintenance, iterative development, agile development, and similar s...
Václav Rajlich, Prashant Gosavi
154
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BMCBI
2006
139views more  BMCBI 2006»
15 years 3 months ago
Improvement in accuracy of multiple sequence alignment using novel group-to-group sequence alignment algorithm with piecewise li
Background: Multiple sequence alignment (MSA) is a useful tool in bioinformatics. Although many MSA algorithms have been developed, there is still room for improvement in accuracy...
Shinsuke Yamada, Osamu Gotoh, Hayato Yamana
DAC
2009
ACM
16 years 4 months ago
Provably good and practically efficient algorithms for CMP dummy fill
Abstract--To reduce chip-scale topography variation in Chemical Mechanical Polishing (CMP) process, dummy fill is widely used to improve the layout density uniformity. Previous res...
Chunyang Feng, Hai Zhou, Changhao Yan, Jun Tao, Xu...
110
Voted
CORR
2002
Springer
111views Education» more  CORR 2002»
15 years 3 months ago
The Fastest and Shortest Algorithm for All Well-Defined Problems
An algorithm M is described that solves any well-defined problem p as quickly as the fastest algorithm computing a solution to p, save for a factor of 5 and loworder additive term...
Marcus Hutter