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» Aggregation for the probabilistic traveling salesman problem
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EMO
2003
Springer
137views Optimization» more  EMO 2003»
13 years 10 months ago
A Two-Phase Local Search for the Biobjective Traveling Salesman Problem
This article proposes the Two-Phase Local Search for finding a good approximate set of non-dominated solutions. The two phases of this procedure are to (i) generate an initial sol...
Luis Paquete, Thomas Stützle
ANTSW
2004
Springer
13 years 10 months ago
S-ACO: An Ant-Based Approach to Combinatorial Optimization Under Uncertainty
A general-purpose, simulation-based algorithm S-ACO for solving stochastic combinatorial optimization problems by means of the ant colony optimization (ACO) paradigm is investigate...
Walter J. Gutjahr
ISCI
2008
83views more  ISCI 2008»
13 years 5 months ago
A diversity maintaining population-based incremental learning algorithm
In this paper we propose a new probability update rule and sampling procedure for population-based incremental learning. These proposed methods are based on the concept of opposit...
Mario Ventresca, Hamid R. Tizhoosh
GECCO
2007
Springer
437views Optimization» more  GECCO 2007»
13 years 11 months ago
A gestalt genetic algorithm: less details for better search
The basic idea to defend in this paper is that an adequate perception of the search space, sacrificing most of the precision, can paradoxically accelerate the discovery of the mo...
Christophe Philemotte, Hugues Bersini
CEC
2010
IEEE
13 years 6 months ago
Evolutionary multi-objective optimization algorithms with probabilistic representation based on pheromone trails
Abstract-- Recently, the research on quantum-inspired evolutionary algorithms (QEA) has attracted some attention in the area of evolutionary computation. QEA use a probabilistic re...
Hui Li, Dario Landa Silva, Xavier Gandibleux