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CLOUDCOM
2010
Springer
13 years 6 months ago
Scaling Populations of a Genetic Algorithm for Job Shop Scheduling Problems Using MapReduce
Inspired by Darwinian evolution, a genetic algorithm (GA) approach is one of the popular heuristic methods for solving hard problems, such as the Job Shop Scheduling Problem (JSSP...
Di-Wei Huang, Jimmy Lin
GECCO
2006
Springer
188views Optimization» more  GECCO 2006»
14 years 7 days ago
Dominance learning in diploid genetic algorithms for dynamic optimization problems
This paper proposes an adaptive dominance mechanism for diploidy genetic algorithms in dynamic environments. In this scheme, the genotype to phenotype mapping in each gene locus i...
Shengxiang Yang
ITICSE
1997
ACM
14 years 23 days ago
A genetic algorithms tutorial tool for numerical function optimisation
The field of Genetic Algorithms has grown into a huge area over the last few years. Genetic Algorithms are adaptive methods, which can be used to solve search and optimisation pro...
Edmund K. Burke, D. B. Varley
GECCO
2000
Springer
145views Optimization» more  GECCO 2000»
14 years 5 days ago
A New Genetic Algorithm for Minimum Span Frequency Assignment using Permutation and Clique
We propose a new Genetic Algorithm (GA) for solving the minimum span frequency assignment problem (MSFAP). The MSFAP is minimizing the range of the frequencies assigned to each tr...
Shouichi Matsui, Ken-ichi Tokoro
EMO
2003
Springer
81views Optimization» more  EMO 2003»
14 years 1 months ago
Solving Hierarchical Optimization Problems Using MOEAs
Abstract. In this paper, we propose an approach for solving hierarchical multi-objective optimization problems (MOPs). In realistic MOPs, two main challenges have to be considered:...
Christian Haubelt, Sanaz Mostaghim, Jürgen Te...