Search
Now showing items 1-10 of 176
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 ...
Minmax regret combinatorial optimization problems: an Algorithmic Perspective
(CAMBRIDGE UNIV PRESS, 2012)
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 ...
Optimal capacitor placement in radial distribution networks
(Institute of Electrical and Electronics Engineers (IEEE), 2001-11-01)
The capacitor placement (replacement) problem for radial distribution networks determines capacitor types, sizes, locations and control schemes. Optimal capacitor placement is a hard combinatorial problem that can be ...
An application of a multi-objective tabu search algorithm to a bicriteria flowshop problem
(Kluwer Academic PublDordrechtHolanda, 2004)
Tabu search algorithm for network synthesis
(Institute of Electrical and Electronics Engineers (IEEE), 2000-05-01)
Large scale combinatorial problems such as the network expansion problem present an amazingly high number of alternative configurations with practically the same investment, but with substantially different structures ...
Optimal capacitor placement in radial distribution networks
(Ieee-inst Electrical Electronics Engineers IncNew YorkEUA, 2001)
Neural approach for solving several types of optimization problems
(Springer/plenum PublishersNew YorkEUA, 2006)
Genetic local search for multi-objective flowshop scheduling problems
(Elsevier Science BvAmsterdamHolanda, 2005)
Comparative studies on non-convex optimization methods for transmission network expansion planning
(Institute of Electrical and Electronics Engineers (IEEE), 1998-08-01)
We have investigated and extensively tested three families of non-convex optimization approaches for solving the transmission network expansion planning problem: simulated annealing (SA), genetic algorithms (GA), and tabu ...