نتایج جستجو برای: aco beamsearch

تعداد نتایج: 3072  

2012
Liangjun Ke

Combining ant colony optimization (ACO) and multiobjective evolutionary algorithm based on decomposition (MOEA/D), this paper proposes a multiobjective evolutionary algorithm, MOEA/D-ACO. Following other MOEA/D-like algorithms, MOEA/D-ACO decomposes a multiobjective optimization problem into a number of single objective optimization problems. Each ant (i.e. agent) is responsible for solving one...

2008
Madjid Khichane Patrick Albert Christine Solnon

We introduce two reactive frameworks for dynamic adapating some parameters of an Ant Colony Optimization (ACO) algorithm. Both reactive frameworks use ACO to adapt parameters: pheromone trails are associated with parameter values; these pheromone trails represent the learnt desirability of using parameter values and are used to dynamically set parameters in a probabilistic way. The two framewor...

2009
Madjid Khichane Patrick Albert Christine Solnon

We introduce two reactive frameworks for dynamically adapting some parameters of an Ant Colony Optimization (ACO) algorithm. Both reactive frameworks use ACO to adapt parameters : pheromone trails are associated with parameter values ; these pheromone trails represent the learnt desirability of using parameter values and are used to dynamically set parameters in a probabilistic way. The two fra...

2014
Marco Baioletti Andrea Chiancone Valentina Poggioni Valentino Santucci

In this paper a new generation ACO-Based Planner, called ACOPlan 2013, is described. This planner is an enhanced version of ACOPlan, a previous ACO-Based Planner (Baioletti et al. 2011), which differs from the former in the search algorithm and in the implementation, now done on top of Downwards. The experimental results, even if are not impressive, are encouraging and confirm that ACO is a sui...

Journal: :JORS 2004
J. Levine Frederick Ducatelle

The Bin Packing Problem and the Cutting Stock Problem are two related classes of NP-hard combinatorial optimization problems. Exact solution methods can only be used for very small instances, so for real-world problems, we have to rely on heuristic methods. In recent years, researchers have started to apply evolutionary approaches to these problems, including Genetic Algorithms and Evolutionary...

2010
Michalis Mavrovouniotis Shengxiang Yang

In recent years, there has been a growing interest in addressing dynamic optimization problems (DOPs) using evolutionary algorithms (EAs). Several approaches have been developed for EAs to increase the diversity of the population and enhance the performance of the algorithm for DOPs. Among these approaches, immigrants schemes have been found beneficial for EAs for DOPs. In this paper, random, e...

2017
Neeta Agarwal

Feature Selection is the process of selecting a subset of features available, allowing a certain objective function to be optimized, from the data containing noisy,irrelevant and redundant features. This paper presents a novel feature selection method that is based on hybridization of ACO with a binary PSO to obtain excellent properties of two algorithms by synthesizing them and aims at achievi...

2010
Lucio Mauro Duarte Luciana Foss Flávio Rech Wagner Tales Heimfarth

We present a model for the travelling salesman problem (TSP) solved using the ant colony optimisation (ACO), a bio-inspired mechanism that helps speed up the search for a solution and that can be applied to many other problems. The natural complexity of the TSP combined with the selforganisation and emergent behaviours that result from the application of the ACO make model-checking this system ...

Journal: :IJCNS 2009
Zhaoquan Cai Han Huang Yong Qin Xianheng Ma

Ant colony optimization (ACO) has been proved to be one of the best performing algorithms for NP-hard problems as TSP. The volatility rate of pheromone trail is one of the main parameters in ACO algorithms. It is usually set experimentally in the literatures for the application of ACO. The present paper first proposes an adaptive strategy for the volatility rate of pheromone trail according to ...

2002
John Levine Frederick Ducatelle

The Bin Packing Problem and the Cutting Stock Problem are two related classes of NP-hard combinatorial optimisation problems. Exact solution methods can only be used for very small instances, so for real-world problems we have to rely on heuristic methods. In recent years, researchers have started to apply evolutionary approaches to these problems, including Genetic Algorithms and Evolutionary ...

نمودار تعداد نتایج جستجو در هر سال

با کلیک روی نمودار نتایج را به سال انتشار فیلتر کنید