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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
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
AAAI
1998
13 years 6 months ago
Fast Probabilistic Modeling for Combinatorial Optimization
Probabilistic models have recently been utilized for the optimization of large combinatorial search problems. However, complex probabilistic models that attempt to capture interpa...
Shumeet Baluja, Scott Davies
STOC
2002
ACM
121views Algorithms» more  STOC 2002»
14 years 5 months ago
Average case analysis for batched disk scheduling and increasing subsequences
We consider the problem of estimating the tour length and finding approximation algorithms for the asymmetric traveling salesman problem arising from the disk scheduling problem. ...
Eitan Bachmat