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100 results about "Travelling salesman problem" patented technology
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The travelling salesman problem (TSP) asks the following question: "Given a list of cities and the distances between each pair of cities, what is the shortest possible route that visits each city and returns to the origin city?" It is an NP-hard problem in combinatorial optimization, important in operations research and theoretical computer science.
Data analysis-based automatic route programming method and system thereof
The invention discloses a data analysis-based automatic route programming method and a system thereof. The method comprises the following steps: obtaining user's interest point information, matching the user's interest point information with interest point information preserved in a database in advance, and outputting a coordinate list containing the interest point coordinate information; clustering interest points according to the coordinate list; carrying out travelling salesman problem solving for the interest points contained in each of clustered group results generated after the clustering and the coordinate list, and outputting a shortest path; calculating the ideal time consumption of the shortest path; calculating whole-course ideal consumption days according to preset play time every day, dividing, and determining the initial starting point and the initial ending point every day; selecting a residence place having a shortest distance to the initial ending point that day and the initial starting point the next day, and adding the residence place to the shortest path; and adding residence places to all the divided days until route programming is wholly completed.
Owner:江苏云智星河网络科技股份有限公司
Unmanned aerial vehicle (UAV) flight path generation method and device, storage medium and equipment
ActiveCN107943072ABest local flight pathBest global flight pathNavigational calculation instrumentsForecastingPath generationUncrewed vehicle
Owner:SHENZHEN UNIV
Electric power inspection robot path planning method based on simulated annealing ant colony algorithm
ActiveCN109141430AIncrease speedGuaranteed feasibilityNavigational calculation instrumentsPath lengthTransformer
The invention discloses an electric power inspection robot path planning method based on a simulated annealing ant colony algorithm. The method includes the steps: building a map according to an outdoor transformer substation environment, planning the running path and stop points of an electric power inspection robot and building a topological map according to coordinate information of the stop points; acquiring the local shortest path of two optional inspection points by the aid of a classical Dijkstra algorithm according to inspection tasks, and building an undirected graph; transforming a global optimal path planning problem into a multi-target traveling salesman problem according to path lengths and the number of passing stop points, and planning a global optimal path on the basis of the undirected graph by the simulated annealing ant colony algorithm; replacing a local path in the global optimal path by the local shortest path to obtain a complete final path. The method is high inconvergence rate and global searching ability and has the advantages of low complexity, high feasibility and high speed.
Owner:NANJING UNIV OF SCI & TECH
Systems and methods for solving combinatorial problems
ActiveUS20130282636A1Quantum computersNanoinformaticsTheoretical computer scienceTravelling salesman problem
Systems and methods to solve combinatorial problems employ a permutation network which may be modeled after a sorting network where comparators are replaced by switches that controllably determine whether inputs are swapped or are left unchanged at the outputs. A quantum processor may be used to generate permutations by the permutation network by mapping the state of each switch in the network to the state of a respective qubit in the quantum processor. In this way, a quantum computation may explore all possible permutations simultaneously to identify a permutation that satisfies at least one solution criterion. The Travelling Salesman Problem is discussed as an example of a combinatorial problem that may be solved using these systems and methods.
Owner:D WAVE SYSTEMS INC
Method for a deeper search in a time-limited image satellite planning environment
InactiveUS20110025554A1Less timeReduce computing timeCosmonautic vehiclesInstruments for comonautical navigationTravelling salesman problemSatellite
The present invention relates to image satellite planning, and more particularly to a method for allowing a deeper search for high value targets in a time-limited planning environment. In an exemplary embodiment, a method of computing an ordered subset of targets includes using an approximation for the time needed for the satellite to re-orient to a new target, rather than calculating each maneuver time between targets. By approximating the maneuver time rather than calculating it, the calculation time is reduced. Each iteration through the traveling salesman problem takes less time, and more iterations can be accomplished between imaging windows. The iterative process can search deeper into the traveling salesman problem to find a better solution.
Owner:BAILEY DAVID A
Improved genetic algorithm-based traveling salesman problem solving method
InactiveCN107122843ASolving NP-hard problemsImprove efficiencyForecastingGenetic algorithmsMutation probabilityImproved algorithm
The invention discloses a method for solving the traveling salesman problem based on an improved genetic algorithm. The steps include: aiming at the TSP problem, encoding the path using a decimal number string; calculating the total length, and then judging the total length; after encoding On the search space U of the decimal number string path, define the fitness function f(x), and define the population size n, the crossover probability Pc, the mutation probability Pm and the number of iterations T; in the search space U, randomly generate n individuals s1, s2, s3, ..., sn, constitute the initial population S0 = {s1, s2, s3, ..., sn}, set the current iteration number t = 0; according to the fitness function f(x), evaluate the individual fitness in the population , if t<T, then end the step, otherwise perform the genetic operation step; the individual with the highest fitness obtained through the genetic operation step is the optimal solution of the traveling salesman problem solving method. Based on the traditional genetic algorithm, the present invention optimizes the traveling salesman problem to achieve the purpose of improving the shortcoming that the algorithm is prone to premature convergence and optimizing the search efficiency.
Owner:SOUTH CHINA UNIV OF TECH
Ant colony optimization-differential evolution fusion method for solving traveling salesman problems
InactiveCN101520858AStrong global search capabilityFast convergenceGenetic modelsForecastingGlobal optimizationTravelling salesman problem
The invention discloses an ant colony optimization-differential evolution fusion method for solving traveling salesman problems, which comprises the following steps: (1) algorithm parameters are initialized; (2) an ant colony is initialized; (3) a first iteration is carried out; (4) a mutation operation and an interlace operation are carried out to the pheromones of various squads from the second generation, so as to generate new pheromones; (5) the first squad is selected; (6) the ants of each squad establish the respective optimal path in accordance with the primitive pheromones; (7) the ants of each squad establish the respective optimal path in accordance with the new pheromones; (8) the two optimal paths are compared to pick out the pheromones with a better result of path optimization; (9) the pheromones of various ant squads are updated and passed down to the next generation; (10) the sixth step is carried out again until all squads finish the calculation; (11) the optimal path of the current generation and the length thereof are determined; (12) the fourth step is carried out again to carry out the calculation of the next generation until the termination condition is met; and (13) the whole optimal path and the length thereof are determined. The method has better astringency and stronger global optimization capability and is an effective way to solve the large-scale and complicated optimization problems such as traveling salesman problems, etc.
Owner:BEIHANG UNIV
Method for arranging heat in steel making continuous casting production process
InactiveCN102117359AVersatilitySolve infeasible problemsSpecial data processing applicationsTravelling salesman problemMaterials science
The invention discloses a method for arranging heat in a steel making continuous casting production process, and the method comprises the following steps sequentially: establishing a local database and selecting plate blanks from a pool according to the contract; selecting a furnace plate blank to be arranged from the pool and establishing a heat planning model; converting the heat planning model into a prospective traveling salesman problem; solving a heat planning prospective travel business problem model based on an intelligent optimization algorithm and finding an optimal heat plan; and arranging the plate blanks into the furnace as a main character according to the determined optimal heat plan. By using the method for arranging heat, the heat arranging plan is arranged without pre-determining the time of heat to be arranged. By using the invention, one plan is arranged in several seconds, the time can be precise to second, the utilization rate of the equipment is greatly improved and the steel making continuous casting yield is remarkably improved.
Owner:HOHAI UNIV CHANGZHOU
Throughput capacity-maximized unmanned aerial vehicle trajectory planning method
ActiveCN109857143AGuaranteed flight rangeMeet the needs of ground multi-point communicationPosition/course control in three dimensionsCapacity optimizationTravelling salesman problem
The invention discloses a throughput capacity-maximized unmanned aerial vehicle trajectory planning method, and belongs to the field of unmanned aerial vehicle communication. The method comprises thefollowing steps of: S1, establishing an unmanned aerial vehicle-ground communication system model, and determining a throughput capacity optimization target function via a track of the unmanned aerialvehicle and transmission power; S2, setting distance thresholds, grouping a plurality of randomly distributed ground nodes according to the thresholds, and analyzing influences, on the groups, of different distance thresholds; S3, after the grounding, calculating the geometric center of each group so as to determine a flight center of the unmanned aerial vehicle, solving traveling salesman problems to solve shortest flight path problems of the unmanned aerial vehicle, and determining a communication sequence, for the grouped ground nodes, of the unmanned aerial vehicle; S4, determining an optimum flight radius, an optimum flight speed and an optimum flight circle number of the unmanned aerial vehicle; and S5, during the optimization, firstly optimizing the track under the condition that the track is certain, optimizing the track under the condition that the power is certain, and finally carrying out combined optimization, so as to improve the system throughput.
Owner:DALIAN UNIV
Method for planning logistics paths on basis of bisectors of store point groups
ActiveCN106355291AAvoid searchingAvoid comparative calculationsForecastingLogisticsLogistics managementPlanning approach
Owner:HUNAN UNIV OF SCI & TECH
Multi-unmanned aerial vehicle cooperative task planning method based on clustering and genetic algorithm
ActiveCN112731967AHigh energy consumptionReduce error rateCharacter and pattern recognitionPosition/course control in three dimensionsCluster algorithmSimulation
The invention belongs to the technical field of unmanned aerial vehicle systems, and particularly relates to a multi-unmanned aerial vehicle cooperative task planning method based on clustering and a genetic algorithm. According to the method, point cluster division of a plurality of task points is completed based on a K-means clustering algorithm, a multi-unmanned aerial vehicle collaborative planning energy consumption optimal track problem is simplified into a traveling salesman problem of a plurality of single unmanned aerial vehicles, a genetic algorithm is improved, a UAV waypoint planning optimization algorithm is provided based on the improved genetic algorithm to carry out track optimization, so that the energy consumption of the unmanned aerial vehicles is optimal, the problem that the actual energy consumption value is increased due to the environmental influence in the flight process and the route planning cannot be executed is avoided, and the flight efficiency and the energy utilization rate are improved.
Owner:中科大数据研究院
Self-adaptive particle swarm optimization method solving traveling salesman problem
InactiveCN108830372AQuality improvementFast convergenceData processing applicationsArtificial lifeImproved algorithmLearning factor
The invention discloses a self-adaptive particle swarm optimization method solving a traveling salesman problem. On the basis of existing standard particle swarm optimization, backward learning is adopted for initializing particle population, and an inertia weight w and a learning factor c of particle swarm optimization are regulated adaptively along with increase of number of iteration, so that the optimization capability of particle swarm optimization is improved; and in the later period of particle swarm optimization, chaotic local search is introduced so as to prevent particle swarm optimization from falling into local optimum. The improved algorithm is tested through a standard function, an obtained result is obviously superior to that of the standard PSO, and improved particle swarmoptimization is applied to optimization solution of the traveling salesman problem, so as to obtain a better optimization result.
Owner:HUBEI UNIV OF TECH
Unmanned aerial vehicle cooperative reconnaissance path planning method based on energy consumption fairness
ActiveCN110414722AIncreased energy fairnessDone successfullyNavigational calculation instrumentsForecastingDecompositionUncrewed vehicle
The invention discloses an unmanned aerial vehicle cooperative reconnaissance path planning method based on energy consumption fairness, and the method comprises the steps: calculating a path coveringall target points through employing an algorithm of a traveling salesman problem, and enabling the total energy consumption of the path to be minimum; distributing the N reconnaissance target pointsto K unmanned aerial vehicles by using a path decomposition algorithm and obtaining an initial path of each unmanned aerial vehicle; and forming a closed path of the K unmanned aerial vehicles by adding the initial path of each unmanned aerial vehicle and the path of the unmanned aerial vehicle flying from the starting point to the reconnaissance area. According to the invention, the maximum energy consumption of the unmanned aerial vehicles is effectively reduced, the energy consumption fairness between the unmanned aerial vehicles is improved, and smooth completion of a reconnaissance task is ensured.
Owner:ARMY ENG UNIV OF PLA
Negative feedback self-adaptive mechanism kinematic chain isomorphism identification method for ant colony algorithm
InactiveCN103632196AOvercome the disadvantage of easy convergence to local optimumOvercome speedGenetic modelsSpecial data processing applicationsLocal optimumTopological graph
The invention relates to a negative feedback self-adaptive mechanism kinematic chain isomorphism identification method for an ant colony algorithm. The method comprises the following steps of forming a topological graph corresponding to the structure of the mechanism kinematic chain; ranking the mechanism framework of the kinematic chain according to structural feature, wherein the step of ranking mainly comprises two steps of layering of the topological graph and initial ranking in the layer; obtaining structural feature set of the mechanism, and converting into a depressed TSP (traveling salesman problem); introducing negative feedback mechanism and self-adaptive parameter adjustment into the ant colony algorithm, and working out condition maximum structural codes corresponding to the structural feature set of the two mechanisms through the improved anti colony algorithm; judging whether the condition maximum structural codes are equal, wherein if the condition maximum structural codes are equal, the two mechanisms are isomorphism, and if the condition maximum structural codes are not equal, the two mechanisms are not isomorphism. According to the method, the defect of the ant colony algorithm that local optimum is likely to be converged is overcome, and the global searching ability and rate of convergence of the ant colony algorithm in operation can be guaranteed.
Owner:JIANGSU UNIV
Article processing apparatus, generation method and computer-readable storage medium
ActiveUS20140336811A1Computer controlDigital data processing detailsInformation processorTravelling salesman problem
An article processing apparatus having a movable member for processing an article, includes an information processor configured to generate a transition order of states of the movable member. The information processor is configured to respectively set a plurality of clusters each including, as a plurality of nodes, a plurality of states that the movable member may take, with respect to a plurality of regions of the article, respectively set a plurality of costs with respect to a plurality of combinations of two nodes respectively belonging to two clusters different from each other of the plurality of clusters, and generate the transition order by obtaining, based on the plurality of clusters and the plurality of costs, as a solution of a traveling salesman problem, an order of traveling a plurality of nodes obtained by selecting one node from each of the plurality of clusters.
Owner:CANON KK
Method of using reuse strategy-based intelligent swarm algorithm to optimize dynamic traveling salesman problem (TSP)
ActiveCN108053059ASolid mathematical foundationNarrow down the search spaceForecastingLeast costTravelling salesman problem
The invention discloses a method of using a reuse strategy-based intelligent swarm algorithm to optimize a dynamic traveling salesman problem (TSP). A traditional traveling salesman problem needs finding of a Hamiltonian circuit with a least cost in a static searching space, but actually, certain application which is in a real world and can use the traveling salesman problem as models is not all static, and city sets and weight matrices in the problem models thereof dynamically change. In dynamic environments, a searching result in a last environment can be reused by a swarm under a new environment and is thus learned, thus a searching space of the problem can be reduced, and thus the algorithm is enabled to obtain a better path by searching in shorter time. The invention provides a dynamic travel-salesman modeling method with more realistic meaning and a strategy of reusing historical searching results. In experiment, dynamic performance of the optimization method is tested through setting different-degree changes of environments, and it is proved that the optimization method is reasonable and effective under all the different dynamic environments.
Owner:SOUTH CHINA UNIV OF TECH
Article processing apparatus, generating method, and computer-readable storage medium
InactiveUS20150006230A1Optimize timingForecastingResourcesInformation processorTravelling salesman problem
An article processing apparatus, having a movable member for article processing, includes an information processor configured to set a plurality of clusters each of which includes, as a plurality of nodes, a plurality of candidates of a transition order of states of the movable member with respect to each of a plurality of target regions of an article, set a plurality of costs respectively to a plurality of combinations of two nodes which respectively belong to two mutually different clusters of the plurality of clusters, and generate a transition order of states of the movable member over the plurality of target regions by obtaining, as a solution of a traveling salesman problem, an order of traveling through a plurality of nodes each selected from each of the plurality of clusters, based on the plurality of clusters and the plurality of costs.
Owner:CANON KK
Method and device for collecting data by sink nodes of wireless sensor network
InactiveCN102685861AGuaranteed accuracyReduce multi-hop transmissionEnergy efficient ICTPower managementLine sensorPath length
The invention relates to a method and device for collecting data by sink nodes of a wireless sensor network, belonging to the technical field of network communication. The method comprises the following steps of: firstly, generating a network topology of sensor nodes according to position information and communication radiuses of the sensor nodes and determining a minimum connected dominating set according to the generated network topology; then acquiring the shortest traversal path length of the minimum connected dominating set according to a TSP (Travelling Salesman Problem); and finally, if the shortest traversal path length of the minimum connected dominating set is smaller than or equal to a threshold value, considering the minimum connected dominating set as a sink node set, and collecting data of all sink nodes in the sink node set through the shortest traversal path of the minimum connected dominating set. According to the embodiment of the invention, multi-hop transmission of a wireless sensor is effectively reduced under the condition of ensuring the data delay requirement in the sensor network, the data transmission accuracy is ensured and the energy consumption is reduced.
Owner:BEIJING UNIV OF POSTS & TELECOMM
Three-dimensional space multi-target path planning method combining RRT algorithm and ant colony algorithm
ActiveCN109211242AImprove good performanceAvoid redundant calculationsNavigational calculation instrumentsThree-dimensional spacePlanning approach
The invention discloses a three-dimensional space multi-target path planning method combining an RRT algorithm and an ant colony algorithm. According to the method, a linear line distance between target points is used as an initial path cost, a multi-target path planning problem in a three-dimensional space is converted into a travelling salesman problem with a known path cost, then optimization solution is performed on the travelling salesman problem by using the ant colony algorithm, the passing times of ants on the path between the target points and the optimal solution in each iteration are recorded in the optimization process, if the passing times of ants of the path between two target points exceed a threshold, or the path is contained in the optimal solution of certain iteration, the three-dimensional space path between the two target points is planned by using the RRT algorithm, the initial path cost between the two target points is replaced with the planned path distance, andafter a certain number of iterations, a three-dimensional space path that returns to the starting point after passing by all target points and has a total path cost tending to be minimized can be found.
Owner:ZHEJIANG UNIV
Method for Determining a Sequence for Drilling Holes According to a Pattern using Global and Local Optimization
A method determines a sequence for drilling holes in a workpiece according to a pattern by first partitioning the holes in the pattern into packets. A global sequence of the packets is determined by solving a global traveling salesman problem (TSP), and a local sequence of the holes in each packet is determined by solving a local TSP for each packet. Then, the local sequences of the holes are joined according to the global sequence of the packets to determine a complete sequence for drilling the holes.
Owner:MITSUBISHI ELECTRIC RES LAB INC
Polynomial method for detecting a Hamiltonian circuit
An NP-complete problem can be transformed in polynomial time into any known NP problem. The Hamiltonian circuit problem may be transformed into any other known NP problem (such as the Traveling Salesman problem) and has applications in any context that can be represented by a graph, map, or network structure. The reverse calculation of this transformation from any NP problem into the NP-complete Hamiltonian circuit problem also has a polynomial running time. The composition of this reverse calculation from any known NP problem to the Hamiltonian circuit problem with the polynomial running time of the given algorithm together form a polynomial running time algorithm. Therefore, with this polynomial running time calculation result given for detecting the presence of a Hamiltonian circuit in an undirected graph, it has been shown that P equals any known NP problem or NP. Hence the existence of this Hamiltonian circuit detection algorithm proves P=NP.
Owner:KRIEGER CYNTHIA ANN HARLAN
Unmanned aerial vehicle migration trajectory generation method and device, electronic device and storage medium
ActiveCN109447326ASafety aerial videoContinuous aerial videoForecastingMultiple aircraft traffic managementThree-dimensional spaceTravelling salesman problem
The present application relates to an unmanned aerial vehicle migration trajectory generation method and device, an electronic device and a storage medium. The method comprises the following steps ofobtaining a drawing path on a map, preprocessing the drawing path to generate a first path; determining a candidate region of interest and a sampling viewpoint in three-dimensional space according tosample points of the first path; determining local candidates according to the candidate region of interest and the sampling viewpoint, and obtaining a local candidate cost function of the local candidates; generating the local migration trajectory according to the path between different local candidates, and obtaining the local migration trajectory cost function of the local migration trajectory;and according to the local candidate cost function and the local migration trajectory cost function, constructing the cluster traveling salesman problem, and obtaining the global migration trajectoryby solving the cluster traveling salesman problem. The unmanned aerial vehicle can shoot the safe and continuous aerial video by flying according to the migration trajectory generated via the method.
Owner:MOUTONG SCI & TECH CO LTD
Multi-UAV/UGV collaborative long-term operation path planning method based on multi-objective optimization
ActiveCN112013829AFast convergenceEfficient solutionInternal combustion piston enginesNavigational calculation instrumentsTransformation algorithmTravelling salesman problem
The invention discloses a multi-UAV / UGV collaborative long-term operation path planning method based on multi-objective optimization. The method comprises the following steps: converting a multi-taskfixed charging point problem into a traveling salesman problem for solving through a construction method of a graph of a multi-task fixed charging point problem; according to the construction method of the graph of a multi-task discrete charging point problem, converting the multi-task discrete charging point problem into an equivalent generalized traveling salesman problem to be solved by utilizing a graph conversion algorithm; using a heuristic algorithm ALFG for directly solving the generalized traveling salesman problem; and solving the UAV / UGVs long-term multi-target path planning problemby using a solving algorithm MOALP. According to the multi-UAV / UGV collaborative long-time operation path planning method based on multi-objective optimization, the operation efficiency, the operation duration and the operation range of a ground-air collaborative robot can be effectively improved, more operation task requirements are met, and the higher autonomy effect is achieved.
Owner:XIAN TECHNOLOGICAL UNIV
Load balancing scheduling method based on improved MMAS
ActiveCN111240796AAvoid Search BogsAvoid falling intoArtificial lifeEnergy efficient computingLocal optimumTheoretical computer science
The invention discloses a load balancing scheduling method based on an improved MMAS. An ant colony algorithm has high efficiency and feasibility in the aspects of a combinatorial optimization problemand an NP hard problem, and has positive feedback performance, high robustness, high distribution performance and high expansibility. Aiming at the problems that the basic ant colony algorithm is long in calculation execution time and is easy to fall into a local optimal solution to cause stagnation, the invention provides an improved maximum and minimum ant colony algorithm, which effectively eliminates the defect of long algorithm execution time in a bidirectional convergence pheromone updating mode; and then by limiting upper and lower limits of a pheromone concentration allowable value, the premature stagnation of the algorithm is overcome, the understanding range is enlarged, and the optimization is improved. By verifying a classic traveling salesman problem, the algorithm has the advantages of the basic ant colony algorithm, and experiments show that the improved algorithm has higher execution efficiency and better calculation stability.
Owner:ZHEJIANG UNIV OF TECH
Ship piloting and scheduling method based on improved discrete particle swarm optimization algorithm
The invention discloses a ship piloting and scheduling method based on an improved discrete particle swarm optimization algorithm. On the basis that various piloting and scheduling rules and habits are analyzed, a mathematical model for solving the ship piloting and scheduling problem is provided. For solving the model, the improved discrete particle swarm optimization algorithm based on dynamic particle sub-swarms is provided. For solving the problem that a large amount of non-feasible solutions exist in a conventional solving method, a method for performing particle fitness calculation by means of a pseudo travelling salesman problem solving method is provided. The model is feasible, the provided algorithm has the advantages of being high in searching speed and searching accuracy and high in stability and is suitable for solving on complicated piloting and scheduling problems.
Owner:HOHAI UNIV CHANGZHOU
Method for optimizing proton radiotherapy path in active scanning manner by considering scanning speed change
InactiveCN105654202ASimulation is accurateReduce scan timeGenetic modelsForecastingGenetic algorithmProton
The invention discloses a method for optimizing a proton radiotherapy path in an active scanning manner by considering a scanning speed change. The method comprises the steps of according to different scanning speeds of a scanning point in different positions, establishing a traveling salesman problem model with variable scanning speed; and solving a scanning path with the shortest scanning time by using a global optimization algorithm and a genetic algorithm. According to the method, a scanning speed concept is introduced, so that a real scene can be accurately simulated, the requirement of practical engineering application is basically met, and the solved scanning path is the scanning path with the shortest scanning time under the condition that the scanning speeds are different.
Owner:HEFEI INSTITUTES OF PHYSICAL SCIENCE - CHINESE ACAD OF SCI
Robot group cooperative active sensing method based on self-organized mapping
ActiveCN109799829ASimplify complexityAvoid local optimaPosition/course control in two dimensionsMathematical modelRadar
The invention discloses a multi-robot cooperative active sensing method based on self-organized mapping. The method includes the steps: performing first-round detection according to a calculated trackand a multi-traveling salesman problem model by a robot group to form a closed-loop path; selecting a robot with the lowest ratio of traveling budget time of reaching a target observation point to actual consumed time as a winning robot, performing iterative calculation on the path point of the winning robot by a self-organized mapping network algorithm to obtain a closed-loop path comprising thetarget observation point, and detecting a current target point according to the closed-loop path through a depth camera and a laser radar by the winning robot; traversing all target points and finishing detection. A robot group cooperative active sensing problem in a scene with a large amount of information is transformed into a multi-traveling salesman mathematical model for multi-objective pathplanning, and complexity of problems is greatly simplified. The robot path point is iteratively processed by the self-organized mapping neural network algorithm, and calculation complexity is low.
Owner:TSINGHUA UNIV
Multi-robot path planning method based on ant colony algorithm
InactiveCN110375759AHigh precisionImprove stabilityInstruments for road network navigationNODALData set
Owner:TIANJIN UNIV
Method and apparatus for applying artificial fish swarm algorithm parallel processing to TSP problems based on MIC card
The embodiments of the invention disclose a method and apparatus for applying artificial fish swarm algorithm parallel processing to Traveling Salesman Problem (TSP) problems based on a MIC card. The method includes the following steps: using a MIC card to conduct a fish warm initialization and initialization MPI processing; using MPI to identify sense of smell based on the behavior rules of an artificial fish swarm which is randomly generated after the initialization of the fish swarm, and determining the number of neighbor artificial fish; and using MPI to determine the behavior of tail-chasing, and conducting the behavior of clustering processing and the behavior of rooting processing; using MPI to acquire an optimal solution artificial fish swarm state value which is determined after the behavior of tail-chasing, the behavior of clustering, and the behavior of rooting processing. The method overcomes the limitation of current algorithms which only support serial arithmetic and of algorithms which require large amount of operation and thus result in low efficiency. The method can perfectly optimize the artificial fish swarm algorithm in solving the TSP problem and optimal results. Also, the method overcomes low efficiency of executing parallel processing when large-scale computing operation is required for a CPU due to the number limitation of chip computing units.
Owner:ELECTRIC POWER RES INST OF GUANGDONG POWER GRID
Optimal utility customized tourist attraction route planning system
PendingCN113935547AShorten the timeImprove service qualityForecastingRoute planning softwareTravelling salesman problem
According to the method, firstly, based on analysis of a tourist attraction line planning problem, the tourist attraction line planning problem is converted into a traveling salesman problem, a combinatorial optimization problem containing multiple constraint conditions is designed, and various factors in actual touring of tourists are combined, a tourist attraction route planning problem model under the constraint conditions of tourist time, designated entrances and exits and tourist utility is constructed, then ACO is adopted and improved, two kinds of route guiding type information are defined from the two aspects of distance and attraction, distance and attraction ants are correspondingly established, searching is carried out cooperatively, and an optimal route is searched, the judgment standard of the optimal path is changed into the maximum utility rather than the shortest distance, the out-of-pass element is updated by using the utility rather than the distance, ACO solution based on the optimal utility is established, finally, tourist attraction route planning software is developed, the interface is simple and elegant, the function of each module reaches the expected target, and the method is suitable for popularization and application, and the whole system operates efficiently and stably.
Owner:扆林海
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