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GECCO
2003
Springer
15 years 2 months ago
A Kernighan-Lin Local Improvement Heuristic That Solves Some Hard Problems in Genetic Algorithms
We present a Kernighan-Lin style local improvement heuristic for genetic algorithms. We analyze the run-time cost of the heuristic. We demonstrate through experiments that the heur...
William A. Greene
GECCO
2005
Springer
170views Optimization» more  GECCO 2005»
15 years 3 months ago
Multiobjective shape optimization with constraints based on estimation distribution algorithms and correlated information
A new approach based on Estimation Distribution Algorithms for constrained multiobjective shape optimization is proposed in this article. Pareto dominance and feasibility rules ar...
Sergio Ivvan Valdez Peña, Salvador Botello ...
84
Voted
ANOR
2005
120views more  ANOR 2005»
14 years 9 months ago
Solving the Vehicle Routing Problem with Stochastic Demands using the Cross-Entropy Method
An alternate formulation of the classical vehicle routing problem with stochastic demands (VRPSD) is considered. We propose a new heuristic method to solve the problem. The algori...
Krishna Chepuri, Tito Homem-de-Mello
KES
2010
Springer
14 years 8 months ago
Solving real-world vehicle routing problems with time windows using virus evolution strategy
This paper proposes a new solution to the vehicle routing problem with time windows using an evolution strategy adopting viral infection. The problem belongs to the NP-hard class a...
Hitoshi Kanoh, Souichi Tsukahara
75
Voted
GECCO
2008
Springer
238views Optimization» more  GECCO 2008»
14 years 10 months ago
Using multiple offspring sampling to guide genetic algorithms to solve permutation problems
The correct choice of an evolutionary algorithm, a genetic representation for the problem being solved (as well as their associated variation operators) and the appropriate values...
Antonio LaTorre, José Manuel Peña, V...