Topic
Extremal optimization
About: Extremal optimization is a research topic. Over the lifetime, 1168 publications have been published within this topic receiving 104943 citations.
Papers published on a yearly basis
Papers
More filters
28 citations
25 Sep 2005
TL;DR: An algorithm based on ant colony system for solving traveling salesman problem is proposed, which introduces an inner loop aiming to update the pheromone trails and generates improved tours.
Abstract: An algorithm based on ant colony system for solving traveling salesman problem is proposed. The new algorithm, introduces in ant colony system an inner loop aiming to update the pheromone trails. The update increases the pheromone in the trail followed by the ants and therefore generates improved tours.
28 citations
TL;DR: Results show that the proposed ACOFRS is an alternative method for performing global optimization in phase equilibrium calculations of multicomponent systems and it outperformed other stochastic optimization methods such as Particle Swarm Optimization, Differential Evolution and Genetic Algorithms.
28 citations
TL;DR: An index, namely convergence factor (CF), is introduced that can show the performance of meta-heuristic optimization algorithms and examples show these algorithms have some similarities in common that should be taken into account in solving optimization problems.
28 citations
08 Sep 2010
TL;DR: This paper investigates ACO algorithms with respect to their runtime behavior for the traveling salesperson (TSP) problem, and presents a new construction graph that has a stronger local property than the given input graph which is often used for constructing solutions.
Abstract: Ant colony optimization (ACO) has been widely used for different combinatorial optimization problems. In this paper, we investigate ACO algorithms with respect to their runtime behavior for the traveling salesperson (TSP) problem. We present a new construction graph and show that it has a stronger local property than the given input graph which is often used for constructing solutions. Later on, we investigate ACO algorithms for both construction graphs on random instances and show that they achieve a good approximation in expected polynomial time.
27 citations