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检索条件"主题词=Ant Colony Optimization algorithm"

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A Secure QoS Routing algorithm Based on ACO for Wireless Sensor Network

A Secure QoS Routing Algorithm Based on ACO for Wireless Sen...

引用

15th IEEE International Conference on High Performance Computing and Communications (HPCC) /11th IEEE/IFIP International Conference on Embedded and Ubiquitous Computing (EUC)

作者： Shi, Qinghua Li, Zhong Shandong Univ Coll Comp Sci & Technol Jinan 250100 Peoples R China

ISBN: (纸本)9780769550886

Secure routing issues, as a crucial research direction of security is emergent and significant in WSN The existing QoS routing protocol ignores the security design. A secure QoS routing algorithm based on ACO is designed in this paper. This algorithm combines ant colony optimization algorithm with credit evaluation mechanism effectively. In order to achieve good security performance, the creditworthiness of nodes is introduced as the control factor in ant colony algorithm. Firstly the algorithm will kick off the nodes which are not meet QoS needs. The set of candidate nodes will be optimized. Then an optimal route will be got by the improved ACO algorithm. The algorithm prefers the node with high creditworthiness as the next hop, thus this algorithm can avoid some attack and the optimal route has higher reliability. Finally, the security of the algorithm is analyzed from a variety of network attack.

关键词： ant colony optimization algorithm QoS secure routing

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RATE: A RSU-Aided Scheme for Data-Centric Trust Establishment in VANETs

RATE: A RSU-Aided Scheme for Data-Centric Trust Establishmen...

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7th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM)

作者： Wu, Aifeng Ma, Jianqing Zhang, Shiyong Fudan Univ Sch Comp Sci Shanghai 200433 Peoples R China

ISBN: (纸本)9781424462520

In the research area of vehicular ad-hoc networks (VANETs), a novel notion named data-centric trust establishment is introduced recently, which means the trustworthiness of data is evaluated according to the data's intrinsic properties instead of the reputation of providing entities. In this paper, we propose a Roadside-unit Aided Trust Establishment scheme (RATE) that aims to execute data-centric trust establishment in VANET efficiently(1). Compared to existing trust establishment approaches, RATE is completely data-centric, making RATE appropriate for rapidly changing environment. In addition, through the employment of ant colony optimization algorithm, RATE has ability to integrate direct observed data with feedback information when evaluating the trustworthiness of data, eventually improves the accuracy of evaluation result. Lastly, RATE decouples data-consuming and data-providing entities, thus enables vehicles to mitigate the attacks launched by malicious nodes through directly-linked communications. Simulation shows that RATE can effectively analyze data provided in VANET and correctly establish trust on data.

关键词： Aging Computational fluid dynamics Delay Educational institutions RSU-aided scheme Resilience Roads VANET Vehicles ant colony optimization algorithm data-centric trust establishment directly-linked communications malicious nodes optimisation roadside-unit aided trust establishment scheme vehicular ad hoc networks vehicular ad-hoc networks

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The Container Truck Route optimization Problem by the Hybrid PSO-ACO algorithm 13th

The Container Truck Route Optimization Problem by the Hybrid...

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13th International Conference on Intelligent Computing (ICIC)

作者： Liu, Yi Feng, Mao Shahbazzade, Sabina Hangzhou Dianzi Univ Hangzhou 310018 Zhejiang Peoples R China Univ Calif Berkeley Berkeley CA 94720 USA

ISBN: (纸本)9783319633091;9783319633084

This paper mainly research on the container tuck route optimization problem with the integrated loading and unloading operation. Considered the disperse-stacking of containers in yards and the loading/unloading operations of each berth, the objective function of scheduling problem is the optimal rout of the container truck. In order to solve this problem, the hybrid swarm intelligence algorithm (PSO-ACO) is proposed, which combined the particle swarm optimization algorithm with the ant colony optimization algorithm. The hybrid swarm intelligence algorithm takes advantage of strong local search ability of ant colony optimization algorithm and the ACO's pheromone taxis, which can avoid the particle swarm optimization algorithm fall in the local optimum during the convergence. The results show that the mathematical model and hybrid algorithm have effective, reliability and stability in solving the container truck scheduling problem.

关键词： Container truck route Scheduling Particle swarm optimization algorithm ant colony optimization algorithm

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Fast Collision Detection algorithm based on parallel ant

Fast Collision Detection Algorithm based on parallel ant

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International Conference on Virtual Reality and Visualization (ICVRV)

作者： Qu Huiyan Zhao Wei Jilin Agr Univ JLAU Sch Informat Technol Changchun Peoples R China

ISBN: (纸本)9780769551500

In order to improve the real-time, precision and interactivity of collision detection, based on detailed study of intelligent optimization algorithm technology, we propose a parallel ant colony optimization algorithm, which is introduced into improved random collision detection algorithm, in preliminary testing phase we use balancing bounding box tree first to rule out disjoint objects quickly, use parallel thought[1] to accelerate the speed of collision detection, regard the basic unit and leaves of object as "ants", and then traverse the search. Compare to traditional serial and parallel collision detection algorithm and partial parallel collision detection algorithm, especially for large-scale optimization problems, in the premise does not affect the accuracy and interactivity, the algorithm accelerate the collision detection efficiency further and reduce the time complexity.

关键词： Collision detection ant colony optimization algorithm parallel balanced bounding box tree

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A Bio-Inspired Method for Personalized Learning Path Recommendation Problem 31

A Bio-Inspired Method for Personalized Learning Path Recomme...

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31st International Conference on Computers in Education (ICCE)

作者： Zheng, Yaqian Wang, Deliang Xu, Yaping Mao, Ziqi Zhao, Yaqi Li, Yanyan Beijing Normal Univ Sch Educ Technol Beijing Peoples R China Beijing Normal Univ Res Ctr Knowledge Engn Beijing Peoples R China Univ Hong Kong Fac Educ Hong Kong Peoples R China

ISBN: (纸本)9786269689019

The recommendation of personalized learning paths is recognized as one of the most challenging aspects in the field of e-learning. In the existing literature, numerous approaches have been proposed to identify appropriate learning paths for e-learners, taking into consideration multiple perspectives. However, the current state of research lacks a unified framework that effectively integrates the most vital parameters associated with the learner, learning object (LO), and domain knowledge to generate optimal learning paths. To address this challenge, a novel bio-inspired approach is proposed for solving the personalized learning path problem. In this method, we initially incorporate the learner, LO and domain knowledge models into a unified mathematical model. Then an enhanced ant colony optimization algorithm is utilized to determine the optimal personalized learning paths for learners. To investigate the effectiveness of the proposed method, we performed several computational experiments based on six simulation datasets. The results indicate that the proposed method surpasses other competing methods in terms of performance and robustness, showcasing its superior effectiveness.

关键词： E-learning learning path recommendation unified model ant colony optimization algorithm

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Layout Planning Study for Off-road Park Facilities Based on Complex System Theory

Layout Planning Study for Off-road Park Facilities Based on ...

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2nd International Conference on Information Management, Innovation Management and Industrial Engineering

作者： Zhang, Xizhou Wen, Ying Liu, Jun Wan, Dan Huazhong Univ Sci & Technol Dept Traff Planning & Management Wuhan 430074 Peoples R China

ISBN: (纸本)9780769538761

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 simplified model of multi-objective optimization of the parking facilities site considering the highest social benefit of their layout. The Intelligent ant colony optimization algorithm is introduced to solve the model.

关键词： ant colony optimization algorithm Complex System Theory layout planning parking facilities self-organization

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ACO-based Parallel Machine Scheduling Considering Both Setup Time and Run-based Preventive Maintenance with Reliability Constraints

ACO-based Parallel Machine Scheduling Considering Both Setup...

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IEEE International Conference on Industrial Engineering and Engineering Management (IEEE IEEM)

作者： Chen, Siqi Wang, Liya Shanghai Jiao Tong Univ Sch Mech Engn Shanghai Peoples R China

ISBN: (纸本)9781538667866

This paper studied the problem of parallel processing machine scheduling, taking both set up time and run-based preventive maintenance with reliability constraints into consideration. The objective is to minimize makespan. For this NP-hard problem, an ant colony optimization (ACO) algorithm is proposed. The node selecting probability equation is set based on characteristics of this problem. The objective value obtained by the proposed algorithm is compared to that of the classical LPT rule through numerical experiments. The experiment results imply that the proposed ACO algorithm has better performance than the LPT rule.

关键词： Parallel machine scheduling ant colony optimization algorithm preventive maintenance setup time

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An improved ant colony algorithm to solve knapsack problem

An improved ant colony algorithm to solve knapsack problem

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14th International Conference on Geoinformatics

作者： Li Shuang Wang Shuliang Zhang Qiuming China Univ Geosci Sch Comp Wuhan 430074 Peoples R China Wuhan Univ State Key Lab Informat Engn Surveying Mapping & R Wuhan 430072 Peoples R China Wuhan Univ Int Sch Software Wuhan 430072 Peoples R China

ISBN: (纸本)9780819465283

ant colony optimization algorithm is a novel simulated evolutionary algorithm, which provides a new method for complicated combinatorial optimization problems. In this paper the algorithm is used for solving the knapsack problem. It is improved in selection strategy and information modification, so that it can not easily run into the local optimum and can converge at the global optimum. The experiments show the robustness and the potential power of this kind of meta heuristic algorithm.

关键词： ant colony optimization algorithm Knapsack Problem evolutionary computing

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An adaptive weighted ant colony algorithm 29

An adaptive weighted ant colony algorithm

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第29届中国控制与决策会议

作者： Shi-wei Gao Ya-jie Li Department of Electric & Engineering Lanzhou Petrochemical College of Vocational Technology College of Electrical and Information Engineering Lanzhou University of Technology

ISBN: (纸本)9781509046584

The ant colony algorithm is a metaheuristic algorithm,it provides a new approach for solving discrete optimization problems-the traveling salesman problem,for instance,is usually tested as the *** the ant colony algorithm was introduced,many refinements have been developed to improve the performance by refining the pheromone updating strategies,which have achieved great success on the traveling salesman *** introduce a new ant colony algorithm based on Adaptive Weighted Updating *** demonstrate the effectiveness and flexibility of the new algorithm in this paper.

关键词： ant colony optimization algorithm ant colony System Adaptive Weighted

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Adjustment Mechanism Of Node Transmission Power

Adjustment Mechanism Of Node Transmission Power

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International Conference on Mechatronics and Computational Mechanics (ICMCM 2012)

作者： Li Hongsheng He Ninghui Wuhan Univ Technol Dept Automat Coll Wuhan 430070 Peoples R China Wuhan Univ Technol Dept Mech & Elect Engn Coll Wuhan 430070 Peoples R China

ISBN: (纸本)9783037856598

As to the power control protocol, in the CPC protocol each node uses the maximum transmit power choosed by all network nodes;the communication consumption of IPC protocol is smaller, but each node is using its own definition of transmission power, two-way link between nodes in the network can not be guaranteed. The sent power control based on data transmission can resolve the defaults of CPC and IPC.

关键词： ant colony optimization algorithm Transmit power Power control

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