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FUZZIEEE
2007
IEEE
15 years 10 months ago
Learning Fuzzy Linguistic Models from Low Quality Data by Genetic Algorithms
— Incremental rule base learning techniques can be used to learn models and classifiers from interval or fuzzyvalued data. These algorithms are efficient when the observation e...
Luciano Sánchez, José Otero
GECCO
2000
Springer
138views Optimization» more  GECCO 2000»
15 years 7 months ago
Domain Knowledge and Representation in Genetic Algorithms for Real World Scheduling Problems
This paper discusses the issues that arise in the design and implementation of an industrialstrength evolutionary-based system for the optimization of the monthly work schedules f...
Ioannis T. Christou, Armand Zakarian
GECCO
2006
Springer
184views Optimization» more  GECCO 2006»
15 years 7 months ago
Genetic algorithms and mixed integer linear programs for optimal strategies in a student's "sports" activity
This paper uses an entertaining student "sports" game to illustrate that GAs can be adapted to problems with uncertain properties and complexity. These problems can be s...
Thomas Butter, Franz Rothlauf, Jörn Grahl, To...
GECCO
2005
Springer
384views Optimization» more  GECCO 2005»
15 years 9 months ago
A case study of process facility optimization using discrete event simulation and genetic algorithm
Optimization problems such as resource allocation, job-shop scheduling, equipment utilization and process scheduling occur in a broad range of processing industries. This paper pr...
Keshav P. Dahal, Stuart Galloway, Graeme M. Burt, ...
EPS
1997
Springer
15 years 8 months ago
Investigating Parallel Genetic Algorithms on Job Shop Scheduling Problems
This paper describes a GA for job shop scheduling problems. Using the Giffler and Thompson algorithm, we created two new operators, THX crossover and mutation, which better trans...
Shyh-Chang Lin, Erik D. Goodman, William F. Punch ...