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To reduce accidents and increasing safety, thereby saving lives are one of the context of driver assistance system, among the complex and challenging tasks of future road vehicle is road lane detection. Lane detection is difficult problem because of varying road condition that one can encounter during driving. In this paper a hybrid approach on captured images using ant colony optimization (ACO) on...
Firstly, the model of resource-constrained multi-project scheduling is established. Secondly, a new project priority indicator named project risk ratio synthesizing project throughput and lose per unit of constrained resource is presented. Thirdly, the ant colony optimization (ACO) algorithm is introduced to solve the multi-project scheduling model. Furthermore, in order to accelerate the convergence...
Ant Colony Optimization (ACO) has proven to be a very powerful optimization heuristic for combinatorial optimization problems. This paper introduces a new type of ACO algorithm that will be used for routing along multiple routes in a network as opposed to optimizing a single route. Contrary to traditional routing algorithms, the Ant Dispersion Routing (ADR) algorithm has the objective of determining...
Evacuation routing problem with mixed traffic flow is complex due to the interaction among different types of evacuees. The positive feedback mechanism of single ant colony system may lead to congestion on some optimum routes. Like different ant colony systems in nature, different components of traffic flow compete and interact with each other during evacuation process. In this paper, an approach...
A new text classification algorithm which is based on Ant Colony Algorithm is proposed in this paper. It makes use of the advantage in solving discrete problems by ACO and discreteness of text documents' features. Texts are classified by crawling of class population ants which have class information with them to find an optimal path matching it during iteration in the algorithm. It can get a satisfactory...
Ant colony optimization (ACO) is a cooperative, population-based technique for optimization. Ant algorithms were designed on the base of the behavior of real ant colonies. Real ants can always find the shortest way between the nest and food source, using the environment as the communication tool, named stigmergy. In this paper we focus precisely on the process of finding an optimal path by ant colony...
The natural disaster of heavy snow and server rime in winter affect people's life order by disturbing traffic. A two-stage emergency resource scheduling model was constructed to optimize the emergent resource dispatching plan, so that the limited supplies, which may ensure health and safety of the blocked staff, could reach all parts of the highway net as soon as possible. An ant colony optimization...
Urban off-road park facilities layout planning is an important component of the parking system planning and an integrated system engineering issue with multi-index and multi-constraint. This paper includes the study of the organizational mechanisms of parking facilities layout form and analysis of all factors that impact the public parking facilities layout. In this paper, the author established the...
With the popularity of urban private car, urban road resources become limited. How to enhance the efficiency of road transportation with the existing road resources is one of today's academic research hot spots. To solve this problem, this paper proposes a new algorithm for dynamic route guidance, in order to provide 'the best path' for drivers The algorithm is based on ant colony optimization, using...
An optimal task assignment method for a two robots cooperation system which consists of a serial robot Puma and a parallel robot Stewart is described in this paper. Both robots are with initially identical functionalities. A hierarchical control architecture is established for the system whose assigned task here is NP-hard. In the higher hierarchy, ant colony optimization (ACO) algorithm inspired...
This paper addressed a robot path planning algorithm based on improved ant colony optimization. The ant colony algorithm is used for a global path planning in robot rescue. A target attracting function is introduced to guide the searching process which can improve the search quality of ant colony algorithm in the complex and dynamic environment. The affectivity of proposed algorithm is verified in...
Our paper deals with the detection and automatic extraction of a hierarchical network of urban streets from maps containing only building footprint data. We develop a new approach for extracting, locating and labelling plausible street networks in a given city, based on geometrical an functional considerations. Using some basic tools from the "Mathematical Morphology" field, we propose simple,...
Modeling intersection with agent-oriented technology, this paper gives detail description of intersection agent structure and control strategy. It applies fuzzy theory and ant colony optimization (ACO) in intersection signal control and put forward an intersection fuzzy control model with self-learning mechanism. ACO is used to optimize fuzzy control rules, so the intersection agent has self-learning...
The ant colony optimization is a new meta-heuristic, it is a population based algorithm and is a good method for combination optimizations. Due to the random probabilistic search strategy, the slow convergence is the main problem of the ACO. In order to improve the convergence of the algorithm, the premium-penalty ant colony optimization (PPACO) is proposed. In this new algorithm, the good solutions...
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