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CEC
2007
IEEE
14 years 3 months ago
Modified genetic algorithm for job-shop scheduling: A gap utilization technique
—The Job-Shop Scheduling Problem (JSSP) is one of the most critical combinatorial optimization problems. The objective of JSSP in this research is to minimize the makespan. In th...
S. M. Kamrul Hasan, Ruhul A. Sarker, David Cornfor...
GECCO
2008
Springer
179views Optimization» more  GECCO 2008»
13 years 10 months ago
ASAGA: an adaptive surrogate-assisted genetic algorithm
Genetic algorithms (GAs) used in complex optimization domains usually need to perform a large number of fitness function evaluations in order to get near-optimal solutions. In rea...
Liang Shi, Khaled Rasheed
GECCO
2006
Springer
169views Optimization» more  GECCO 2006»
14 years 14 days ago
An open-set speaker identification system using genetic learning classifier system
This paper presents the design and implementation of an adaptive open-set speaker identification system with genetic learning classifier systems. One of the challenging problems i...
WonKyung Park, Jae C. Oh, Misty K. Blowers, Matt B...
GECCO
2004
Springer
137views Optimization» more  GECCO 2004»
14 years 2 months ago
Modeling Coevolutionary Genetic Algorithms on Two-Bit Landscapes: Random Partnering
Abstract. A model of coevolutioinary genetic algorithms (COGA) consisting of two populations coevolving on two-bit landscapes is investigated in terms of the effects of random par...
Ming Chang, Kazuhiro Ohkura, Kanji Ueda, Masaharu ...
CORR
2006
Springer
130views Education» more  CORR 2006»
13 years 8 months ago
Genetic Programming for Kernel-based Learning with Co-evolving Subsets Selection
Abstract. Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on the fact that i) linear learning can be formalized as a well-posed opti...
Christian Gagné, Marc Schoenauer, Mich&egra...