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The Combinatorial ANT System for Dynamic Combinatorial Optimization ProblemsThe Combinatorial ANT System for Dynamic Combinatorial Optimization Problems
(Universidad de Costa Rica, Centro de Investigación en Matemática Pura y Aplicada (CIMPA), 2005)
The Combinatorial ANT System for Dynamic Combinatorial Optimization ProblemsThe Combinatorial ANT System for Dynamic Combinatorial Optimization Problems
(2012-03-22)
In this paper is presented a distributed algorithm based on Ant System concepts,called Combinatorial Ant System, to solve dynamic combinatorial optimization problems. Our approach consists of mapping the solution space of ...
The Combinatorial ANT System for Dynamic Combinatorial Optimization ProblemsThe Combinatorial ANT System for Dynamic Combinatorial Optimization Problems
(2012-03-22)
In this paper is presented a distributed algorithm based on Ant System concepts,called Combinatorial Ant System, to solve dynamic combinatorial optimization problems. Our approach consists of mapping the solution space of ...
Neural approach for solving several types of optimization problems
(Springer, 2006-03-01)
Neural networks consist of highly interconnected and parallel nonlinear processing elements that are shown to be extremely effective in computation. This paper presents an architecture of recurrent neural net-works that ...
Neural approach for solving several types of optimization problems
(Springer, 2006-03-01)
Neural networks consist of highly interconnected and parallel nonlinear processing elements that are shown to be extremely effective in computation. This paper presents an architecture of recurrent neural net-works that ...
Neural approach for solving several types of optimization problems
(Springer/plenum PublishersNew YorkEUA, 2006)
Neural approach for solving several types of optimization problems
(Springer, 2014)
Learning in Combinatorial Optimization: What and How to Explore
(INFORMS, 2020)
We study dynamic decision making under uncertainty when, at each period, a decision maker implements a solution to a combinatorial optimization problem. The objective coefficient vectors of said problem, which are unobserved ...
Development of neurofuzzy architecture for solving the N-Queens problem
(Taylor & Francis Ltd, 2005-11-01)
Neural networks are dynamic systems consisting of highly interconnected and parallel nonlinear processing elements that are shown to be extremely effective in computation. This paper presents an architecture of recurrent ...