نتایج جستجو برای: aco algorithm

تعداد نتایج: 755371  

2015
Hao Jia

Ant colony optimization (ACO) algorithm is a new heuristic algorithm which has been demonstrated a successful technology and applied to solving complex optimization problems. But the ACO exists the low solving precision and premature convergence problem, particle swarm optimization (PSO) algorithm is introduced to improve performance of the ACO algorithm. A novel hybrid optimization (HPSACO) al...

2007
Erik Dries Erik J. Dries

This research merges the hierarchical reinforcement learning (HRL) domain and the ant colony optimization (ACO) domain. The merger produces a HRL ACO algorithm capable of generating solutions for both domains. This research also provides two specific implementations of the new algorithm: the first a modification to Dietterich’s MAXQ-Q HRL algorithm, the second a hierarchical ACO algorithm. Thes...

Journal: :journal of industrial engineering and management studies 0
m. sayyah department of mathematics, parand branch, islamic azad university, parand, iran. h. larki department of mathematics, shahid chamran university of ahvaz, iran. m. yousefikhoshbakht young researchers & elite club, hamedan branch, islamic azad university, hamedan, iran.

one of the most important extensions of the capacitated vehicle routing problem (cvrp) is the vehicle routing problem with simultaneous pickup and delivery (vrpspd) where customers require simultaneous delivery and pick-up service. in this paper, we propose an effective ant colony optimization (eaco) which includes insert, swap and 2-opt moves for solving vrpspd that is different with common an...

2015
Yu Chen Yanmin Jia

In this paper, we prompt a new multi-dimensional algoithm to solve the traveling salesman problem based on the ant colony optimization algorithm and genetic algorithm. Ant Colony Optimization (ACO) is a heuristic algorithm which has been proven a successful technique and applied to a number of combinatorial optimization (CO) problems. The traveling salesman problem (TSP) is one of the most impo...

Journal: :Computers & OR 2009
T. C. Edwin Cheng Alexander A. Lazarev Evgeny R. Gafarov

We propose a hybrid algorithm based on the Ant Colony Optimization (ACO) meta-heuristic, in conjunction with four well-known elimination rules, to tackle the NP -hard single-machine scheduling problem to minimize the total job tardiness. The hybrid algorithm has the same running time as that of ACO. We conducted extensive computational experiments to test the performance of the hybrid algorithm...

The optimization of the utility consumption (steam and cooling water) is an important part for the optimization of process operating cost. To this end, the heat exchanger networks (HEN) are investigated in a process manner. Different approaches are presented for the synthesis of HEN where stochastic algorithms have received more attention recently. In this paper, a combination of Ant Colony Opt...

Feature selection is of great importance in Quantitative Structure-Activity Relationship (QSAR) analysis. This problem has been solved using some meta-heuristic algorithms such as: GA, PSO, ACO, SA and so on. In this work two novel hybrid meta-heuristic algorithms i.e. Sequential GA and LA (SGALA) and Mixed GA and LA (MGALA), which are based on Genetic algorithm and learning automata for QSAR f...

Journal: :IEEE Trans. Systems, Man, and Cybernetics, Part C 2010
Wei-neng Chen Jun Zhang Henry Shu-Hung Chung Rui-zhang Huang Ou Liu

The multimode resource-constrained projectscheduling problem with discounted cash flows (MRCPSPDCF) is important and challenging for project management. As the problem is strongly nondeterministic polynomial-time hard, only a few algorithms exist and the performance is still not satisfying. To design an effective algorithm for the MRCPSPDCF, this paper proposes an ant colony optimization (ACO) ...

2014
Ravichandran C. Gopalakrishnan Veerakumar Kuppusamy

Lung cancer is becoming a threat to mankind. Applying machine learning algorithms for detection and segmentation of irregular shaped lung nodules remains a remarkable milestone in CT scan image analysis research. In this paper, we apply ACO algorithm for lung nodule detection. We have compared the performance against three other algorithms, namely, Otsu algorithm, watershed algorithm, and globa...

2017
Niharika Sharma S. D. Chavan

Biological inspired routing or bio-inspired routing is a new heuristic routing algorithm in wireless sensor network, which is inspired from biological activities of insects. ACO is ants’ inspired routing algorithm ACO, which has the ability to find shortest path and re-establish the new route in the case of route failure. In order to improve the network performance i.e. increase network lifetim...

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