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Improved Ant Colony-Genetic Algorithm for Information Transmission Path Optimization in Remanufacturing Service System 被引量:7
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作者 Lei Wang Xu-Hui Xia +2 位作者 Jian-Hua Cao Xiang Liu Jun-Wei Liu 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2018年第6期106-117,共12页
The information transmission path optimization(ITPO) can often a ect the e ciency and accuracy of remanufactur?ing service. However, there is a greater degree of uncertainty and complexity in information transmission ... The information transmission path optimization(ITPO) can often a ect the e ciency and accuracy of remanufactur?ing service. However, there is a greater degree of uncertainty and complexity in information transmission of remanu?facturing service system, which leads to a critical need for designing planning models to deal with this added uncer?tainty and complexity. In this paper, a three?dimensional(3D) model of remanufacturing service information network for information transmission is developed, which combines the physic coordinate and the transmitted properties of all the devices in the remanufacturing service system. In order to solve the basic ITPO in the 3D model, an improved 3D ant colony algorithm(Improved AC) was put forward. Moreover, to further improve the operation e ciency of the algorithm, an improved ant colony?genetic algorithm(AC?GA) that combines the improved AC and genetic algorithm was developed. In addition, by taking the transmission of remanufacturing service demand information of certain roller as example, the e ectiveness of AC?GA algorithm was analyzed and compared with that of improved AC, and the results demonstrated that AC?GA algorithm was superior to AC algorithm in aspects of information transmission delay, information transmission cost, and rate of information loss. 展开更多
关键词 Remanufacturing service Information transmission Path optimization ant colony algorithm Genetic algorithm
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MOALG: A Metaheuristic Hybrid of Multi-Objective Ant Lion Optimizer and Genetic Algorithm for Solving Design Problems
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作者 Rashmi Sharma Ashok Pal +4 位作者 Nitin Mittal Lalit Kumar Sreypov Van Yunyoung Nam Mohamed Abouhawwash 《Computers, Materials & Continua》 SCIE EI 2024年第3期3489-3510,共22页
This study proposes a hybridization of two efficient algorithm’s Multi-objective Ant Lion Optimizer Algorithm(MOALO)which is a multi-objective enhanced version of the Ant Lion Optimizer Algorithm(ALO)and the Genetic ... This study proposes a hybridization of two efficient algorithm’s Multi-objective Ant Lion Optimizer Algorithm(MOALO)which is a multi-objective enhanced version of the Ant Lion Optimizer Algorithm(ALO)and the Genetic Algorithm(GA).MOALO version has been employed to address those problems containing many objectives and an archive has been employed for retaining the non-dominated solutions.The uniqueness of the hybrid is that the operators like mutation and crossover of GA are employed in the archive to update the solutions and later those solutions go through the process of MOALO.A first-time hybrid of these algorithms is employed to solve multi-objective problems.The hybrid algorithm overcomes the limitation of ALO of getting caught in the local optimum and the requirement of more computational effort to converge GA.To evaluate the hybridized algorithm’s performance,a set of constrained,unconstrained test problems and engineering design problems were employed and compared with five well-known computational algorithms-MOALO,Multi-objective Crystal Structure Algorithm(MOCryStAl),Multi-objective Particle Swarm Optimization(MOPSO),Multi-objective Multiverse Optimization Algorithm(MOMVO),Multi-objective Salp Swarm Algorithm(MSSA).The outcomes of five performance metrics are statistically analyzed and the most efficient Pareto fronts comparison has been obtained.The proposed hybrid surpasses MOALO based on the results of hypervolume(HV),Spread,and Spacing.So primary objective of developing this hybrid approach has been achieved successfully.The proposed approach demonstrates superior performance on the test functions,showcasing robust convergence and comprehensive coverage that surpasses other existing algorithms. 展开更多
关键词 Multi-objective optimization genetic algorithm ant lion optimizer METAHEURISTIC
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Improved Ant Colony Algorithm for Vehicle Scheduling Problem in Airport Ground Service Support 被引量:3
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作者 Yaping Zhang Ye Chen +2 位作者 Yu Zhang Jian Mao Qian Luo 《Journal of Harbin Institute of Technology(New Series)》 CAS 2023年第1期1-12,共12页
Support vehicles are part of the main body of airport ground operations,and their scheduling efficiency directly impacts flight delays.A mathematical model is constructed and the responsiveness of support vehicles for... Support vehicles are part of the main body of airport ground operations,and their scheduling efficiency directly impacts flight delays.A mathematical model is constructed and the responsiveness of support vehicles for current operational demands is proposed to study optimization algorithms for vehicle scheduling.The model is based on the constraint relationship of the initial operation time,time window,and gate position distribution,which gives an improvement to the ant colony algorithm(ACO).The impacts of the improved ACO as used for support vehicle optimization are compared and analyzed.The results show that the scheduling scheme of refueling trucks based on the improved ACO can reduce flight delays caused by refueling operations by 56.87%,indicating the improved ACO can improve support vehicle scheduling.Besides,the improved ACO can jump out of local optima,which can balance the working time of refueling trucks.This research optimizes the scheduling scheme of support vehicles under the existing conditions of airports,which has practical significance to fully utilize ground service resources,improve the efficiency of airport ground operations,and effectively reduce flight delays caused by ground service support. 展开更多
关键词 airport surface traffic ground service support vehicle scheduling topology model improved ant colony algorithm response value
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A Drone-Based Blood Donation Approach Using an Ant Colony Optimization Algorithm
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作者 Sana Abbas Faraha Ashraf +2 位作者 Fahd Jarad Muhammad Shoaib Sardar Imran Siddique 《Computer Modeling in Engineering & Sciences》 SCIE EI 2023年第8期1917-1930,共14页
This article presents an optimized approach of mathematical techniques in themedical domain by manoeuvring the phenomenon of ant colony optimization algorithm(also known as ACO).A complete graph of blood banks and a p... This article presents an optimized approach of mathematical techniques in themedical domain by manoeuvring the phenomenon of ant colony optimization algorithm(also known as ACO).A complete graph of blood banks and a path that covers all the blood banks without repeating any link is required by applying the Travelling Salesman Problem(often TSP).The wide use promises to accelerate and offers the opportunity to cultivate health care,particularly in remote or unmerited environments by shrinking lab testing reversal times,empowering just-in-time lifesaving medical supply. 展开更多
关键词 NETWORK ant colony algorithm PATH complete graph blood banks DRONES travelling salesman problem
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Security Test Case Prioritization through Ant Colony Optimization Algorithm
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作者 Abdulaziz Attaallah Khalil al-Sulbi +5 位作者 Areej Alasiry Mehrez Marzougui Mohd Waris Khan Mohd Faizan Alka Agrawal Dhirendra Pandey 《Computer Systems Science & Engineering》 SCIE EI 2023年第12期3165-3195,共31页
Security testing is a critical concern for organizations worldwide due to the potential financial setbacks and damage to reputation caused by insecure software systems.One of the challenges in software security testin... Security testing is a critical concern for organizations worldwide due to the potential financial setbacks and damage to reputation caused by insecure software systems.One of the challenges in software security testing is test case prioritization,which aims to reduce redundancy in fault occurrences when executing test suites.By effectively applying test case prioritization,both the time and cost required for developing secure software can be reduced.This paper proposes a test case prioritization technique based on the Ant Colony Optimization(ACO)algorithm,a metaheuristic approach.The performance of the ACO-based technique is evaluated using the Average Percentage of Fault Detection(APFD)metric,comparing it with traditional techniques.It has been applied to a Mobile Payment Wallet application to validate the proposed approach.The results demonstrate that the proposed technique outperforms the traditional techniques in terms of the APFD metric.The ACO-based technique achieves an APFD of approximately 76%,two percent higher than the second-best optimal ordering technique.These findings suggest that metaheuristic-based prioritization techniques can effectively identify the best test cases,saving time and improving software security overall. 展开更多
关键词 CONFIDENTIALITY INTEGRITY AUTHENTICATION NON-REPUDIATION RESILIENCE AUTHORIZATION ant Colony Optimization algorithm
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New Hybrid Algorithm Based on BicriterionAnt for Solving Multiobjective Green Vehicle Routing Problem
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作者 Emile Nawej Kayij Joél Lema Makubikua Justin Dupar Kampempe Busili 《American Journal of Operations Research》 2023年第3期33-52,共20页
The main objective of this paper is to propose a new hybrid algorithm for solving the Bi objective green vehicle routing problem (BGVRP) from the BicriterionAnt metaheuristic. The methodology used is subdivided as fol... The main objective of this paper is to propose a new hybrid algorithm for solving the Bi objective green vehicle routing problem (BGVRP) from the BicriterionAnt metaheuristic. The methodology used is subdivided as follows: first, we introduce data from the GVRP or instances from the literature. Second, we use the first cluster route second technique using the k-means algorithm, then we apply the BicriterionAntAPE (BicriterionAnt Adjacent Pairwise Exchange) algorithm to each cluster obtained. And finally, we make a comparative analysis of the results obtained by the case study as well as instances from the literature with some existing metaheuristics NSGA, SPEA, BicriterionAnt in order to see the performance of the new hybrid algorithm. The results show that the routes which minimize the total distance traveled by the vehicles are different from those which minimize the CO<sub>2</sub> pollution, which can be understood by the fact that the objectives are conflicting. In this study, we also find that the optimal route reduces product CO<sub>2</sub> by almost 7.2% compared to the worst route. 展开更多
关键词 Metaheuristics Green Vehicle Routing Problem ant Colony algorithm Genetic algorithms Green Logistics
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Path Planning for AUVs Based on Improved APF-AC Algorithm
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作者 Guojun Chen Danguo Cheng +2 位作者 Wei Chen Xue Yang Tiezheng Guo 《Computers, Materials & Continua》 SCIE EI 2024年第3期3721-3741,共21页
With the increase in ocean exploration activities and underwater development,the autonomous underwater vehicle(AUV)has been widely used as a type of underwater automation equipment in the detection of underwater envir... With the increase in ocean exploration activities and underwater development,the autonomous underwater vehicle(AUV)has been widely used as a type of underwater automation equipment in the detection of underwater environments.However,nowadays AUVs generally have drawbacks such as weak endurance,low intelligence,and poor detection ability.The research and implementation of path-planning methods are the premise of AUVs to achieve actual tasks.To improve the underwater operation ability of the AUV,this paper studies the typical problems of path-planning for the ant colony algorithm and the artificial potential field algorithm.In response to the limitations of a single algorithm,an optimization scheme is proposed to improve the artificial potential field ant colony(APF-AC)algorithm.Compared with traditional ant colony and comparative algorithms,the APF-AC reduced the path length by 1.57%and 0.63%(in the simple environment),8.92%and 3.46%(in the complex environment).The iteration time has been reduced by approximately 28.48%and 18.05%(in the simple environment),18.53%and 9.24%(in the complex environment).Finally,the improved APF-AC algorithm has been validated on the AUV platform,and the experiment is consistent with the simulation.Improved APF-AC algorithm can effectively reduce the underwater operation time and overall power consumption of the AUV,and shows a higher safety. 展开更多
关键词 PATH-PLANNING autonomous underwater vehicle ant colony algorithm artificial potential field bio-inspired neural network
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Research on Grid Planning of Dual Power Distribution Network Based on Parallel Ant Colony Optimization Algorithm
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作者 Shuaixiang Wang 《Journal of Electronic Research and Application》 2023年第1期32-41,共10页
A distribution network plays an extremely important role in the safe and efficient operation of a power grid.As the core part of a power grid’s operation,a distribution network will have a significant impact on the s... A distribution network plays an extremely important role in the safe and efficient operation of a power grid.As the core part of a power grid’s operation,a distribution network will have a significant impact on the safety and reliability of residential electricity consumption.it is necessary to actively plan and modify the distribution network’s structure in the power grid,improve the quality of the distribution network,and optimize the planning of the distribution network,so that the network can be fully utilized to meet the needs of electricity consumption.In this paper,a distribution network grid planning algorithm based on the reliability of electricity consumption was completed using ant colony algorithm.For the distribution network structure planning of dual power sources,the parallel ant colony algorithm was used to prove that the premise of parallelism is the interactive process of ant colonies,and the dual power distribution network structure model is established based on the principle of the lowest cost.The artificial ants in the algorithm were compared with real ants in nature,and the basic steps and working principle of the ant colony optimization algorithm was studied with the help of the travelling salesman problem(TSP).Then,the limitations of the ant colony algorithm were analyzed,and an improvement strategy was proposed by using python for digital simulation.The results demonstrated the reliability of model-building and algorithm improvement. 展开更多
关键词 Parallel ant colony optimization algorithm Dual power sources Distribution network Grid planning
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Improved ant colony optimization algorithm for the traveling salesman problems 被引量:22
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作者 Rongwei Gan Qingshun Guo +1 位作者 Huiyou Chang Yang Yi 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2010年第2期329-333,共5页
Ant colony optimization (ACO) is a new heuristic algo- rithm which has been proven a successful technique and applied to a number of combinatorial optimization problems. The traveling salesman problem (TSP) is amo... Ant colony optimization (ACO) is a new heuristic algo- rithm which has been proven a successful technique and applied to a number of combinatorial optimization problems. The traveling salesman problem (TSP) is among the most important combinato- rial problems. An ACO algorithm based on scout characteristic is proposed for solving the stagnation behavior and premature con- vergence problem of the basic ACO algorithm on TSP. The main idea is to partition artificial ants into two groups: scout ants and common ants. The common ants work according to the search manner of basic ant colony algorithm, but scout ants have some differences from common ants, they calculate each route's muta- tion probability of the current optimal solution using path evaluation model and search around the optimal solution according to the mutation probability. Simulation on TSP shows that the improved algorithm has high efficiency and robustness. 展开更多
关键词 ant colony optimization heuristic algorithm scout ants path evaluation model traveling salesman problem.
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Weapon target assignment problem satisfying expected damage probabilities based on ant colony algorithm 被引量:26
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作者 Wang Yanxia Qian Longjun Guo Zhi Ma Lifeng 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2008年第5期939-944,共6页
A weapon target assignment (WTA) model satisfying expected damage probabilities with an ant colony algorithm is proposed. In order to save armament resource and attack the targets effectively, the strategy of the we... A weapon target assignment (WTA) model satisfying expected damage probabilities with an ant colony algorithm is proposed. In order to save armament resource and attack the targets effectively, the strategy of the weapon assignment is that the target with greater threat degree has higher priority to be intercepted. The effect of this WTA model is not maximizing the damage probability but satisfying the whole assignment result. Ant colony algorithm has been successfully used in many fields, especially in combination optimization. The ant colony algorithm for this WTA problem is described by analyzing path selection, pheromone update, and tabu table update. The effectiveness of the model and the algorithm is demonstrated with an example. 展开更多
关键词 weapon target assignment ant colony algorithm optimization.
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Ant colony optimization algorithm and its application to Neuro-Fuzzy controller design 被引量:11
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作者 Zhao Baojiang Li Shiyong 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2007年第3期603-610,共8页
An adaptive ant colony algorithm is proposed based on dynamically adjusting the strategy of updating trail information. The algorithm can keep good balance between accelerating convergence and averting precocity and s... An adaptive ant colony algorithm is proposed based on dynamically adjusting the strategy of updating trail information. The algorithm can keep good balance between accelerating convergence and averting precocity and stagnation. The results of function optimization show that the algorithm has good searching ability and high convergence speed. The algorithm is employed to design a neuro-fuzzy controller for real-time control of an inverted pendulum. In order to avoid the combinatorial explosion of fuzzy rules due tσ multivariable inputs, a state variable synthesis scheme is employed to reduce the number of fuzzy rules greatly. The simulation results show that the designed controller can control the inverted pendulum successfully. 展开更多
关键词 neuro-fuzzy controller ant colony algorithm function optimization genetic algorithm inverted pen-dulum system.
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Novel Approach to Nonlinear PID Parameter Optimization Using Ant Colony Optimization Algorithm 被引量:11
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作者 Duan Hai-bin Wang Dao-bo Yu Xiu-fen 《Journal of Bionic Engineering》 SCIE EI CSCD 2006年第2期73-78,共6页
This paper presents an application of an Ant Colony Optimization (ACO) algorithm to optimize the parameters in the design of a type of nonlinear PID controller. The ACO algorithm is a novel heuristic bionic algorith... This paper presents an application of an Ant Colony Optimization (ACO) algorithm to optimize the parameters in the design of a type of nonlinear PID controller. The ACO algorithm is a novel heuristic bionic algorithm, which is based on the behaviour of real ants in nature searching for food. In order to optimize the parameters of the nonlinear PID controller using ACO algorithm, an objective function based on position tracing error was constructed, and elitist strategy was adopted in the improved ACO algorithm. Detailed simulation steps are presented. This nonlinear PID controller using the ACO algorithm has high precision of control and quick response. 展开更多
关键词 ant Colony Optimization algorithm PHEROMONE nonlinear PID parameter optimization
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Design of PID controller with incomplete derivation based on ant system algorithm 被引量:6
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作者 Guanzheng TAN Qingdong ZENG Wenbin LI 《控制理论与应用(英文版)》 EI 2004年第3期246-252,共7页
A new and intelligent design method for PID controller with incomplete derivation is proposed based on the ant system algorithm ( ASA) . For a given control system with this kind of PID controller, a group of optimal ... A new and intelligent design method for PID controller with incomplete derivation is proposed based on the ant system algorithm ( ASA) . For a given control system with this kind of PID controller, a group of optimal PID controller parameters K p * , T i * , and T d * can be obtained by taking the overshoot, settling time, and steady-state error of the system's unit step response as the performance indexes and by use of our improved ant system algorithm. K p * , T i * , and T d * can be used in real-time control. This kind of controller is called the ASA-PID controller with incomplete derivation. To verify the performance of the ASA-PID controller, three different typical transfer functions were tested, and three existing typical tuning methods of PID controller parameters, including the Ziegler-Nichols method (ZN),the genetic algorithm (GA),and the simulated annealing (SA), were adopted for comparison. The simulation results showed that the ASA-PID controller can be used to control different objects and has better performance compared with the ZN-PID and GA-PID controllers, and comparable performance compared with the SA-PID controller. 展开更多
关键词 PID controller Incomplete derivation Parameter tuning ant system algorithm Genetic algorithm Simulated annealing
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Satellite Constellation Design with Adaptively Continuous Ant System Algorithm 被引量:5
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作者 He Quan Han Chao 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2007年第4期297-303,共7页
The ant system algorithm (ASA) has proved to be a novel meta-heuristic algorithm to solve many multivariable problems. In this paper, the earth coverage of satellite constellation is analyzed and a n + 1^ -fold cov... The ant system algorithm (ASA) has proved to be a novel meta-heuristic algorithm to solve many multivariable problems. In this paper, the earth coverage of satellite constellation is analyzed and a n + 1^ -fold coverage rate is put forward to evaluate the coverage performance of a satellite constellation. An optimization model of constellation parameters is established on the basis of the coverage performance. As a newly developed method, ASA can be applied to optimize the constellation parameters. In order to improve the ASA, a rule for adaptive number of ants is proposed, by which the search range is obviously enlarged and the convergence speed increased. Simulation results have shown that the ASA is more quick and efficient than other methodV211.71s. 展开更多
关键词 ant system algorithm satellite constellation optimization design coverage performance adaptive adjusting
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Optimization of Air Route Network Nodes to Avoid ″Three Areas″ Based on An Adaptive Ant Colony Algorithm 被引量:8
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作者 Wang Shijin Li Qingyun +1 位作者 Cao Xi Li Haiyun 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI CSCD 2016年第4期469-478,共10页
Air route network(ARN)planning is an efficient way to alleviate civil aviation flight delays caused by increasing development and pressure for safe operation.Here,the ARN shortest path was taken as the objective funct... Air route network(ARN)planning is an efficient way to alleviate civil aviation flight delays caused by increasing development and pressure for safe operation.Here,the ARN shortest path was taken as the objective function,and an air route network node(ARNN)optimization model was developed to circumvent the restrictions imposed by″three areas″,also known as prohibited areas,restricted areas,and dangerous areas(PRDs),by creating agrid environment.And finally the objective function was solved by means of an adaptive ant colony algorithm(AACA).The A593,A470,B221,and G204 air routes in the busy ZSHA flight information region,where the airspace includes areas with different levels of PRDs,were taken as an example.Based on current flight patterns,a layout optimization of the ARNN was computed using this model and algorithm and successfully avoided PRDs.The optimized result reduced the total length of routes by 2.14% and the total cost by 9.875%. 展开更多
关键词 air route network planning three area avoidance optimization of air route network node adaptive ant colony algorithm grid environment
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Improved Multi-objective Ant Colony Optimization Algorithm and Its Application in Complex Reasoning 被引量:3
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作者 WANG Xinqing ZHAO Yang +2 位作者 WANG Dong ZHU Huijie ZHANG Qing 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2013年第5期1031-1040,共10页
The problem of fault reasoning has aroused great concern in scientific and engineering fields.However,fault investigation and reasoning of complex system is not a simple reasoning decision-making problem.It has become... The problem of fault reasoning has aroused great concern in scientific and engineering fields.However,fault investigation and reasoning of complex system is not a simple reasoning decision-making problem.It has become a typical multi-constraint and multi-objective reticulate optimization decision-making problem under many influencing factors and constraints.So far,little research has been carried out in this field.This paper transforms the fault reasoning problem of complex system into a paths-searching problem starting from known symptoms to fault causes.Three optimization objectives are considered simultaneously: maximum probability of average fault,maximum average importance,and minimum average complexity of test.Under the constraints of both known symptoms and the causal relationship among different components,a multi-objective optimization mathematical model is set up,taking minimizing cost of fault reasoning as the target function.Since the problem is non-deterministic polynomial-hard(NP-hard),a modified multi-objective ant colony algorithm is proposed,in which a reachability matrix is set up to constrain the feasible search nodes of the ants and a new pseudo-random-proportional rule and a pheromone adjustment mechinism are constructed to balance conflicts between the optimization objectives.At last,a Pareto optimal set is acquired.Evaluation functions based on validity and tendency of reasoning paths are defined to optimize noninferior set,through which the final fault causes can be identified according to decision-making demands,thus realize fault reasoning of the multi-constraint and multi-objective complex system.Reasoning results demonstrate that the improved multi-objective ant colony optimization(IMACO) can realize reasoning and locating fault positions precisely by solving the multi-objective fault diagnosis model,which provides a new method to solve the problem of multi-constraint and multi-objective fault diagnosis and reasoning of complex system. 展开更多
关键词 fault reasoning ant colony algorithm Pareto set multi-objective optimization complex system
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Ant Colony Algorithm for Solving QoS Routing Problem 被引量:3
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作者 SUNLi-iuan WANGLiang-jun WANGRu-chuan 《Wuhan University Journal of Natural Sciences》 EI CAS 2004年第4期449-453,共5页
Based on the state transition rule, the local updating rule and the global updating rule of ant colony algorithm, we propose an improved ant colony algorithm of the least\|cost quality of service (QoS) unicast rou... Based on the state transition rule, the local updating rule and the global updating rule of ant colony algorithm, we propose an improved ant colony algorithm of the least\|cost quality of service (QoS) unicast routing. The algorithm is used for solving the routing problem with delay, delay jitter, bandwidth, and packet loss\|constrained. In the simulation, about 52.33% ants find the successful QoS routing , and converge to the best. It is proved that the algorithm is efficient and effective. 展开更多
关键词 ant colony algorithm QOS unicast routing
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An effective multi-level algorithm based on ant colony optimization for graph bipartitioning 被引量:3
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作者 冷明 郁松年 +1 位作者 丁旺 郭强 《Journal of Shanghai University(English Edition)》 CAS 2008年第5期426-432,共7页
Partitioning is a fundamental problem with applications to many areas including data mining, parellel processing and Very-large-scale integration (VLSI) design. An effective multi-level algorithm for bisecting graph... Partitioning is a fundamental problem with applications to many areas including data mining, parellel processing and Very-large-scale integration (VLSI) design. An effective multi-level algorithm for bisecting graph is proposed. During its coarsening phase, an improved matching approach based on the global information of the graph core is developed with its guidance function. During the refinement phase, the vertex gain is exploited as ant's heuristic information and a positive feedback method based on pheromone trails is used to find the global approximate bipartitioning. It is implemented with American National Standards Institute (ANSI) C and compared to MeTiS. The experimental evaluation shows that it performs well and produces encouraging solutions on 18 different graphs benchmarks. 展开更多
关键词 rain-cut GRAPH bipartitioning multi-level algorithm ant colony optimization (ACO)
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Two-Dimension Path Planning Method Based on Improved Ant Colony Algorithm 被引量:4
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作者 Rong Wang Hong Jiang 《Advances in Pure Mathematics》 2015年第9期571-578,共8页
Nowadays, path planning has become an important field of research focus. Considering that the ant colony algorithm has numerous advantages such as the distributed computing and the characteristics of heuristic search,... Nowadays, path planning has become an important field of research focus. Considering that the ant colony algorithm has numerous advantages such as the distributed computing and the characteristics of heuristic search, how to combine the algorithm with two-dimension path planning effectively is much important. In this paper, an improved ant colony algorithm is used in resolving this path planning problem, which can improve convergence rate by using this improved algorithm. MAKLINK graph is adopted to establish the two-dimensional space model at first, after that the Dijkstra algorithm is selected as the initial planning algorithm to get an initial path, immediately following, optimizing the select parameters relating on the ant colony algorithm and its improved algorithm. After making the initial parameter, the authors plan out an optimal path from start to finish in a known environment through ant colony algorithm and its improved algorithm. Finally, Matlab is applied as software tool for coding and simulation validation. Numerical experiments show that the improved algorithm can play a more appropriate path planning than the origin algorithm in the completely observable. 展开更多
关键词 PATH PLANNING DIJKSTRA Improved ant COLONY algorithm
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Quantum-inspired ant algorithm for knapsack problems 被引量:3
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作者 Wang Honggang Ma Liang Zhang Huizhen Li Gaoya 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2009年第5期1012-1016,共5页
The knapsack problem is a well-known combinatorial optimization problem which has been proved to be NP-hard. This paper proposes a new algorithm called quantum-inspired ant algorithm (QAA) to solve the knapsack prob... The knapsack problem is a well-known combinatorial optimization problem which has been proved to be NP-hard. This paper proposes a new algorithm called quantum-inspired ant algorithm (QAA) to solve the knapsack problem. QAA takes the advantage of the principles in quantum computing, such as qubit, quantum gate, and quantum superposition of states, to get more probabilistic-based status with small colonies. By updating the pheromone in the ant algorithm and rotating the quantum gate, the algorithm can finally reach the optimal solution. The detailed steps to use QAA are presented, and by solving series of test cases of classical knapsack problems, the effectiveness and generality of the new algorithm are validated. 展开更多
关键词 knapsack problem quantum computing ant algorithm quantum-inspired ant algorithm.
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