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GECCO
2008
Springer
131views Optimization» more  GECCO 2008»
13 years 11 months ago
The study for transportation planning considered the inventory using hybrid genetic algorithm
The transportation planning (TP) is well-known basic network problem. However, for some real-world applications, it is often that the TP model is extended to satisfy other additio...
Shinichiro Ataka, Mitsuo Gen
GECCO
2008
Springer
155views Optimization» more  GECCO 2008»
13 years 11 months ago
Towards memoryless model building
Probabilistic model building methods can render difficult problems feasible by identifying and exploiting dependencies. They build a probabilistic model from the statistical prope...
David Iclanzan, Dumitru Dumitrescu
GECCO
2008
Springer
172views Optimization» more  GECCO 2008»
13 years 11 months ago
Empirical analysis of a genetic algorithm-based stress test technique
Evolutionary testing denotes the use of evolutionary algorithms, e.g., Genetic Algorithms (GAs), to support various test automation tasks. Since evolutionary algorithms are heuris...
Vahid Garousi
GECCO
2008
Springer
143views Optimization» more  GECCO 2008»
13 years 11 months ago
A parallel evolutionary algorithm for unconstrained binary quadratic problems
In this paper an island model is described for the unconstrained Binary Quadratic Problem (BQP), which can be used with up to 2500 binary variables. Our island model uses a master...
István Borgulya
GECCO
2008
Springer
155views Optimization» more  GECCO 2008»
13 years 11 months ago
Integrating user preferences with particle swarms for multi-objective optimization
This paper proposes a method to use reference points as preferences to guide a particle swarm algorithm to search towards preferred regions of the Pareto front. A decision maker c...
Upali K. Wickramasinghe, Xiaodong Li