COR
2006
13 years 5 months ago
2006
A problem of assigning cooperating uninhabited aerial vehicles to perform multiple tasks on multiple targets is posed as a new combinatorial optimization problem. A genetic algori...
EOR
2008
13 years 5 months ago
2008
In this paper we present an extension of ant colony optimization (ACO) to continuous domains. We show how ACO, which was initially developed to be a metaheuristic for combinatoria...
ANOR
2010
13 years 5 months ago
2010
The design of effective neighborhood structures is fundamentally important for creating better local search and metaheuristic algorithms for combinatorial optimization. Significant...
GECCO
2008
Springer
13 years 6 months ago
2008
Springer
The landscape formalism unites a finite candidate solution set to a neighborhood topology and an objective function. This construct can be used to model the behavior of local sea...
AAAI
2007
13 years 7 months ago
2007
Russian Doll Search (RDS) is a well-known algorithm for combinatorial optimization. In this paper we extend it from mono-objective to multi-objective optimization. We demonstrate ...
GECCO
2006
Springer
13 years 8 months ago
2006
Springer
Genetic algorithms (GAs) have recently become very popular by solving combinatorial optimization problems. In this paper, we propose an extension of the hybrid genetic algorithm f...
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I am a member of Mathematics department at Sabzevar Tarbiat Moallem University from 1999 until now. My main research interests lie in the areas of Super-Resolution, Computer Vision...
ICCAD
1993
IEEE
13 years 9 months ago
1993
IEEE
In this paper, we present an integrated approach to synthesis and mapping to go beyond the combinatorial limit set up by the depth-optimal FlowMap algorithm. The new algorithm, na...
CCO
2001
Springer
13 years 9 months ago
2001
Springer
Lagrangian relaxation is commonly used in combinatorial optimization to generate lower bounds for a minimization problem. We propose a modified Lagrangian relaxation which used i...
WEA
2004
Springer
13 years 10 months ago
2004
Springer
We introduce a metaheuristic framework for combinatorial optimization. Our framework is similar to others (e.g. [1]) in that it is modular enough that important components can be i...