888 results about "Pheromone" patented technology

A Swarm Autonomous Routing Algorithm (SARA) is performed by simple communication node devices for node to node communications in a network, especially a Mobile Ad hoc NETwork (MANET). Each node maintains a table of pheromone values for known neighbor nodes. Pheromone values are dynamic for adapting to a dynamic arrangement of nodes, and are updated either passively or actively. Routing tables are not used. When a node receives a packet, it uses the pheromone table to simply determine whether or not to forward (rebroadcast) the packet to a neighbor node, and if possible, determines and indicates the best neighbor node for next forwarding the packet. Destination Zone Routing (DZR) and Swarm Location Service (SLS) are alternative enhancements of SARA that can be used for more efficient routing when nodes are location aware/knowledgeable. SLS may also be used to improve routing algorithms other than SARA.

The invention provides an unmanned aircraft route planning method based on combination of Voronoi diagram and ant group optimizing algorithm. Firstly a model is established in accordance with properties of various threaten sources, e. g. landform, radar, missile and anticraft gun, and the unmanned aircraft route cost includes threaten costs and fuel oil costs; then initial pheromone values are given to each edge of the Voronoi diagram, enabling an ant to begin the search from the Voronoi node nearest to the start point. The marching Voronoi edge is selected based ob the status shift rule, then the search at the Voronoi node nearest to the target point is finished; And when all the ants have finished their own candidate route selection, the pheromones at each edge of the Voronoi diagram are updated in accordance with the improving and updating rules, wherein the pheromones at edges with no ant passing by are evaporated, and the process is repeated until an optimal unmanned aircraft route is found out. The method is characterized by good real-time and high-speed performance, and the found route is closer to the actual optimal unmanned aircraft route.

A composition comprising a mixture of fatty acids such as, linoleic, oleic and palmitic acids or deriviatives thereof dervived from secretions o mammalian mammary glands. The compositions can be utilized to decrease stress, anxiety and aggressiveness in mammals.

The invention relates to wireless self organized network energy saving needed route method based on ant colony optimization. The route building includes the following steps: broadcasting state information of asking ant to search network and store in each node reverse information pheromone list; responding the anti while receiving the request and selecting one neighbor node as the next step reverse source node; building the route from the source node to destination node. The route maintenance is that energy parameter is inducted; and new route finding process will be forced to do to avoid node from dying untimely while node energy consumption is overmuch.

The invention discloses a mobile robot path planning method based on an ant colony algorithm under a dynamic environment. The method comprises the following steps of 1, modeling the environment by using a grating method; 2, building local diffusion information pheromone tau''rs; 4, computing a transition probability; 5, adding a feasible node S into a tabu table; 6, completing paths; 7, acquiringthe shortest path via path information recorded in the tabu table; 8, updating pheromone matrix elements; and 9, finding the optimal path via iteration, that is to say an algorithm ending condition ismet, and outputting a final result. According to the ant colony algorithm based on a potential field method provided by the invention, the faster convergence speed and optimizing ability are provided, the local diffusion information pheromone has relative good smoothness, the collaboration ability of individual ants is further enhanced, the local cross paths are reduced, the quantity of lost antsis reduced, and thus the ant colony algorithm is converged to the global optimum with the faster speed, and meanwhile also achieves the diversity of learning, and the defect that an artificial potential field method is easy to trap in the local optimum is overcome.

The invention discloses a method for path planning based on an improved ant colony algorithm. Compared with the classical ant colony algorithm, the method has the following improvements: (1) a constant pheromone evaporation coefficient is adjusted to be an adaptive pheromone evaporation coefficient, and the size of the coefficient is changed adaptively along with increase in number of iterations of an ant colony method; a local optimum path is preferentially selected by adopting a rule that the number of inflection points is small on the basis that different paths are identical in length; (3) a path simplifying rule is adopted for the local optimum path, whether each passing node in the path and the starting node are neighboring nodes or not is judged, and redundant nodes on the path are eliminated; and (4) a pre-sorting rule is adopted when pheromone updating is performed on the path passing by an ant colony before, and only the top 1/3 of paths in path length sorting are updated. According to the above improvements, the method can effectively reduce the algorithm convergence time of the ant colony algorithm and improve the operating efficiency.

Links in a system may be displayed at varying prominence based on user interaction with the links. Link paths chosen by users become apparent by virtue of display prominence of the links. A link may be displayed with greater or lesser prominence corresponding to the propensity of users to interact with the link. Prominence values that affect a prominence at which links are displayed may be modified based on user interaction information. Prominence values may further automatically decay, possibly over time or according to user interaction with the links. Using and modifying prominence values in this manner, links that emerge with greater prominence may form one or more “paths” that users can readily follow. Much as in the natural world where pheromones deposited by ants attract other ants to desirable paths, user interaction information can be advantageously used to automatically identify more desirable link paths to a resource.

The invention relates to a mobile robot path planning method and system based on an improved ant colony algorithm. The mobile robot path planning method comprises the following steps of 1 environment modeling, 2 initial pheromone distribution and 3 optimal path searching and optimal path outputting. According to the mobile robot path planning method and system based on the improved ant colony algorithm, improvement is conducted on a previous traditional ant colony algorithm in the initial pheromone distribution aspect, ants can guide optimization of the ants at the beginning, and the early convergence speed is obviously increased; meanwhile initial parameters are reasonably selected, for instance, selection of pheromone evaluation, a result does not run into a locally optimal solution or has difficulty in forming an optimal solution, reasonable improvement is conducted on a pheromone update mode, the situation of running into the locally optimal solution can be effectively avoided, and the working efficiency and working reliability of the robot can be improved.

The invention relates to a mobile robot path planning method and system based on a genetic ant colony algorithm. The mobile robot path planning method includes the steps that 1, modeling is conducted on the environment by establishing a coordinate system; 2, part of optimal solutions obtained through the genetic algorithm are converted to pheromones initial values of the ant colony algorithm; 3, optimum path search is conducted again through the ant colony algorithm, after optimum path search is ended, interlace operation is conducted on paths meeting the requirements of conditions, and the optimum path is finally obtained. The mobile robot path planning method and system overcome inevitable defects existing in a single ant colony algorithm, in other words, the ant colony algorithm is greater in blindness at the initial stage of search, the ant colony algorithm and the genetic algorithm are complementary in advantages, the search range of path search is shortened, and search efficiency of the optimum path is improved.

The present invention relates to compositions and methods for attracting bed bugs with novel attractants and new and improved methods to enable their use to attract, monitor or trap bed bugs for surveying, monitoring, mitigation and management purposes. Known mammal pheromones were discovered to be useful as bed bug kairomone attractants. A method of delivering non-volatile attractants by using the attractive heat source to heat and volatilize the attractants was discovered to be the optimal method to disseminate the kairomones. A new method of generating low levels of carbon dioxide is disclosed, and the combination of kairomones, carbon dioxide and heat is shown to attract bed bugs.

The invention discloses an optimization method of the shortest emergency logistics path based on the fish swarm ant colony algorithm. The congestion factor is introduced into the basic ant colony algorithm to solve the optimization problem of the shortest emergency logistics path and enhance the search for emergency logistics. The ability to optimize the best solution for the path reduces the possibility of the basic ant colony algorithm falling into a local optimum. (1) Input the number of ants, the maximum number of iterations and the maximum load capacity of the vehicle, select the emergency situation, and input the importance of residual pheromone, the importance of heuristic pheromone, evaporation coefficient and intensity coefficient; (2) Find the shortest emergency logistics route : (1) Establish the model of the shortest emergency logistics route optimization problem; (2) The solution process of the model; (3) Display the distribution route results and the performance comparison results of the algorithm in solving the shortest emergency logistics route optimization problem. The optimization scheme for finding emergency logistics routes in the present invention is more efficient.

The invention relates to a scheduling method for a semiconductor production line based on multi-ant-colony optimization. The method comprises the following steps of: determining bottleneck processing areas of the semiconductor production line, wherein processing areas, of which average utilization rate exceeds 70 percent, of equipment are regarded as the bottleneck processing areas; setting the number of ant colonies as the number of the bottleneck processing areas, and initializing a multi-ant-colony system; parallelly searching scheduling schemes of all bottleneck processing areas by all ant colony systems; restraining and integrating the scheduling schemes of all bottleneck processing areas into one scheduling scheme for all bottleneck processing areas according to a procedure processing sequence, and deducing the scheduling schemes of other non-bottleneck processing areas by using the scheduling scheme and the procedure processing sequence as restraint to obtain the scheduling scheme of the whole semiconductor production line; and judging whether program ending conditions are met, if so, inputting the scheduling scheme which is optimal in performance, otherwise, updating pheromones of the ant colonies by using the scheduling scheme which is current optimal in performance, and guiding a new round of searching process. The method has the advantages that: an important practical value is provided for solving the optimal dispatching problem of the semiconductor production line; and important instructional significance is provided for improving the production management level of semiconductor enterprises of China.

The invention discloses a dynamic dispatching method on the base of pheromone in semi-conductive product line, which comprises the following steps: first, storing pheromone variation of each WIP which relates to the WIP delivery date, holding time of waiting processing equipment, pure processing time and production periodic multiplication factor; second, storing pheromone variation which relates to equipment load; then, integrating the WIP pheromone variation and relating equipment pheromone variation, generating a selective variation of each WIP; finally, elaborating them on the equipment according to the method which consists of short-term and long-term function index to improve multi-function index production or making system.

Pheromone compositions based on a combination of squalene, linoleic acid and 1-docosanol are described. The compositions are useful for behavior modification in mammals that exhibit undesirable or harmful stress-related behaviors.

This invention relates to methods of formulating steroid pheromones as novel stable emulsions. These emulsions can be used for administration of the steroid pheromones to living organisms such as humans or pigs in place of current organic solvent or pressurized aerosol formulations that present hazards in both shipping and application. Uses relating to pigs are in stimulation of sexual maturation, diagnosis of the onset and timing of oestrus in female pigs, and inducing boars to accept dummy sows. The water-based emulsions can include 5α-androst-16-en-3-one and 3α-hydroxy-5α-androst-16-ene for administration to pigs. The use of water-based emulsions eliminates the need for formulation of the steroid pheromones in organic solvents, delivery of these pheromones as pressurized aerosols, and following the precautions required to reduce hazards during shipping and handling. The water-based emulsions allow for treatment of living organisms where a liquid organic solvent formulation or aerosol of the pheromones might be harmful to the organism or a substrate.

The invention belongs to the field of unmanned ship global path planning and particularly relates to an unmanned ship global path multi-target planning method based on the improved ant colony algorithm. The method comprises steps of establishing a marine environment map model by utilizing a Maklink graph theory; improving a path heuristic information strategy to obtain a path average value; designing an ant pheromone volatilization adaptive adjustment strategy; designing a strategy combining local pheromone updating and global pheromone updating; improving the state transition probability of anext node searched by an ant colony through a heading angle deviation factor of an unmanned ship; and designing an evaluation function by integrating the requirements of the shortest global path length, the least optimization iteration times of the improved ant colony algorithm, the lowest path smoothing coefficient and the like. The method is advantaged in that multiple targets such as a globalpath distance of marine navigation of an unmanned surface vehicle, the iteration frequency of optimizing the global path by improving the ant colony algorithm and the smoothness coefficient of the planned global path are comprehensively considered, the optimal global path of marine navigation of the unmanned surface vehicle is finally planned, and the method has relatively high safety.

The invention discloses an emergency logistic route optimization method based on an improved ant colony algorithm. The method comprises the steps of: constructing a multi-target static route optimizing model with minimum delivery time and minimum delivery cost serving as a target, and determining constraint conditions of the optimizing model, such as the emergency supply flows of temporary transfer stations, the fairness, and the vehicle-mounted capacity; using the ant colony algorithm to search for all routes, ordering the routes according to the lengths of the found routes after that all ants complete once searching, attaching a corresponding pheromone increment to each ant finding each route according to the route lengths; and setting upper and lower bounds of the pheromone, updating the pheromone of each route, completing traversal of all disaster points, determining a total target function value of each route and determining the optimal route and the optimal target function value. According to the invention, the ant colony algorithm is improved on the aspects of pheromone updating, pheromone limiting and the like, the convergence rate and the solving quality are increased and a theoretical basis is provided for the optimizing of the emergency route.

The invention discloses a cloud environment task scheduling method based on an improved ant colony algorithm. On the basis of the conventional ant colony algorithm, a rest-life-pheromone (RLP) concept is introduced; by comparing the RLPs of ant brothers in the searching process, repeated search can be effectively eliminated, and searching accuracy is improved; and by adoption of a method for computing the quantity of the ant brothers, the quantity of ants can be dynamically changed under the specific conditions of loads and tasks of cloud environment, so a system is not overloaded, and the searching accuracy is ensured. Compared with the prior art, the cloud environment task scheduling method based on the improved ant colony algorithm has the advantages that requirements of a user on task execution time can be met to the greatest extent, and the allocation efficiency and execution efficiency of the tasks are improved.

Disclosed in the invention is an ant colony algorithm-based high-energy efficiency wireless sensor network routing method. The method comprises three parts: cluster establishment, transmission in cluster, and transmission between clusters. When a multi-hop relay node is selected, a heuristic ant colony intelligent algorithm is employed to search a multi-hop transmission route; and during the searching process, an expectation importance influence is eliminated and a probability for node selection is completely decided by the link pheromone concentration. And when a local link pheromone is updated, a dump energy minimum value of a collaboration zone node is multiplied by link pheromone increasing degree Q and then the result is divided by transmission energy consumption, thereby completing updating. According to the new pheromone updating method, the dump energy and the transmission energy consumption of the node are scaled appropriately and then are introduced to the link pheromone updating; and when the dump energy of the collaboration zone node at the next hop is increased and the transmission energy consumption is reduced, the node can be selected. Therefore, when the routing method is used, total energy consumption of the network can be reduced; the dump energy of the network nodes can be balanced; and the working life of the network can be prolonged.

The invention provides a multi-unmanned aerial vehicle (UAV) track planning method based on a culture ant colony search mechanism, which includes the following steps: (1) carrying out mesh generationon a standard space according to a grid method; (2) building a multi-UAV track planning model, including the number of UAVs, the start and end points and a threat model; (3) initializing the start point and the end point; (4) initializing an ant colony algorithm, including: initializing an ant colony and calculating a heuristic factor and a guide factor; and (5) assigning all ants to an initial node, and updating taboo knowledge; selecting next node for transfer according to the taboo knowledge and the state transfer probability until there is no optional node or a destination node is selected, updating historical knowledge, and updating pheromones according to the historical knowledge; and outputting a shortest path if the maximum number of iterations is achieved, and continuing the process until U multi-UAV optimal multi-path tracks are obtained. The problem that it is difficult to find the optimal flight tracks of unmanned aerial vehicles due to slow search and heavy computing burden is solved, and multi-UAV track planning is realized.

The invention relates to the technical field of route planning methods, in particular to an improved ant colony path planning algorithm based on non-uniform modeling. The improved ant colony path planning algorithm considers the shortcomings of a uniform modeling scheme to modeling in a complex environment, and quadtree modeling is proposed to obtain a non-uniform grid model; the improved ant colony path planning algorithm based on a non-uniform grid model is provided, the non-uniform grid model is used as a basis for improving a basic ant colony algorithm, the distance between a node and an obstacle is considered during selection of a path point, and the distance between a node to be selected and the obstacle is considered during the selection of the path point; an 'ant-cycle' pheromone update way is adopted, and the pheromone size is limited when the global pheromone is updated; a simulation experiment shows that the non-uniform grid model is superior to a uniform grid model, and theimproved ant colony algorithm is faster in convergence rate and can get a path which better meets the needs of underwater vehicles in the complex environments compared with other basic ant colony algorithms.