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GECCO
2006
Springer
148views Optimization» more  GECCO 2006»
15 years 1 months ago
A specification-based fitness function for evolutionary testing of object-oriented programs
Encapsulation of states in object-oriented programs hinders the search for test data using evolutionary testing. As client code is oblivious to the internal state of a server obje...
Yoonsik Cheon, Myoung Kim
GECCO
2006
Springer
218views Optimization» more  GECCO 2006»
15 years 1 months ago
Genetic programming with primitive recursion
When Genetic Programming is used to evolve arithmetic functions it often operates by composing them from a fixed collection of elementary operators and applying them to parameters...
Stefan Kahrs
GECCO
2006
Springer
130views Optimization» more  GECCO 2006»
15 years 1 months ago
An efficient multi-objective evolutionary algorithm with steady-state replacement model
The generic Multi-objective Evolutionary Algorithm (MOEA) aims to produce Pareto-front approximations with good convergence and diversity property. To achieve convergence, most mu...
Dipti Srinivasan, Lily Rachmawati
GECCO
2006
Springer
159views Optimization» more  GECCO 2006»
15 years 1 months ago
Genetic algorithms for positioning and utilizing sensors in synthetically generated landscapes
Positioning multiple sensors for acquisition of a a given environment is one of the fundamental research areas in various fields, such as military scouting, computer vision and ro...
Haluk Topcuoglu, Murat Ermis
GECCO
2006
Springer
163views Optimization» more  GECCO 2006»
15 years 1 months ago
The quadratic multiple knapsack problem and three heuristic approaches to it
The quadratic multiple knapsack problem extends the quadratic knapsack problem with K knapsacks, each with its own capacity Ck. A greedy heuristic fills the knapsacks one at a tim...
Amanda Hiley, Bryant A. Julstrom