GECCO
2009
Springer
13 years 9 months ago
2009
Springer
In this paper, we present a stigmergy-based algorithm for solving optimization problems with continuous variables, labeled Differential Ant-Stigmergy Algorithm (DASA). The perfor...
GECCO
2009
Springer
13 years 9 months ago
2009
Springer
High–dimensional optimization problems appear very often in demanding applications. Although evolutionary algorithms constitute a valuable tool for solving such problems, their ...
CEC
2009
IEEE
13 years 9 months ago
2009
IEEE
Abstract—A number of population based optimization algorithms have been proposed in recent years to solve unconstrained and constrained single and multi-objective optimization pr...
GECCO
2003
Springer
13 years 9 months ago
2003
Springer
This paper discusses a new model of parallel evolutionary algorithms (EAs) called the specialized island model (SIM) that can be used to generate a set of diverse non-dominated sol...
GECCO
2004
Springer
13 years 10 months ago
2004
Springer
The optimization of the epoxy polymerization process involves a number of conflicting objectives and more than twenty decision parameters. In this paper, the problem is treated tr...
ICTAC
2005
Springer
13 years 10 months ago
2005
Springer
We present a new derivation of efficient algorithms for a class of optimization problems called maximum marking problems. We extend the class of weight functions used in the speciï...
GECCO
2005
Springer
13 years 10 months ago
2005
Springer
Evolutionary Algorithms (EAs), popular search methods for solving search and optimization problems, are known for successful and fast location of single optimal solutions. However,...
EUROCAST
2005
Springer
13 years 10 months ago
2005
Springer
abstract NP-hard optimization problem, in a general sense. From the observation that, intuitively, there are many connections among categorical concepts and structural complexity n...
CP
2005
Springer
13 years 10 months ago
2005
Springer
Abstract. We present a parameterized approximation scheme for distributed combinatorial optimization problems based on dynamic programming. The algorithm is a utility propagation m...
APPROX
2005
Springer
13 years 10 months ago
2005
Springer
A large class of stochastic optimization problems can be modeled as minimizing an objective function f that depends on a choice of a vector x ∈ X, as well as on a random external...