Improved Colony Algorithm Research Articles

The Risk Element Transmission Model of Power Restoration Based on Dynamic Improved Ant Colony Algorithm

In order to restore power supply of a complex distribution network in the most economical way, proposed a dynamic improved ant colony algorithm. It’s used to select the path of supply restoration. Improved the original pheromone update mechanism of ant colony algorithm and update the increment of pheromone dynamically. It not only takes into account the inherent loss in the chosen route for power restoration, but also considers the economic losses in every region caused by time delay. This algorithm can find approximate extreme solutions quickly and avoid trapping in local minima. It can minimum the total economic loss of the electric interruption, and provide a reliable basis for the economic decision-making of the power recovery.

Training Algorithm of BP Networks Based on Improved Ant Colony Algorithm

This study proposes a new method to search optimal parameters of BP networks based on improved ant colony algorithm. The algorithm proposed that each ant searches only around the best solution of the previous iteration with, which can reduce search space fast. is proposed for improving the solution performance to reach global optimum fairly quickly. Simulation results indicate that optimize parameters of BP networks with this method can not only overcome the limitations both the slow convergence and the local extreme values by basic BP algorithm, but also improve the learning ability and generalization ability.

The Application of an Improved Ant Colony Algorithm in Mobile Robot Path Planning

This paper presents an improved ant colony algorithm to plan an optimal collision-free path for mobile robot in complicated static environment. Based on the work space model with grid method, simulated foraging behavior of ants and to serve the mobile robot path planning, update the conventional ant colony algorithm with some special functions. To avoid mobile robot path deadlock, a dead-corner table is established and the penalty function is used to update the trail intensity when an ant explores a dead—corner in the path searching. The simulation results show that the algorithm can improve performance of path planning obviously, and the algorithm is simple and effective.

An Improved Ant Colony Algorithm for the Vehicle Routing Problem in Time-Dependent Networks

Vehicle routing is an important combinatorial optimization problem. In real transport networks,the travel speed and travel time of roads have large time-variability and randomness. The study of vehicle routing problem in time-dependent network has even more practical value than static network VRP problem. This paper combines the features of time-dependent networks and gives the mathematical models of the time-dependent vehicle routing problem. On this basis, the traditional ant colony optimization algorithm is improved. A new path transfer strategy of ants and new dynamic pheromone update strategy applicable to time-dependent network are proposed. Based on these strategies, the improved ant colony algorithm is given for solving the vehicle routing problem in time-dependent networks. The simulation results show that the algorithm can effectively solve the vehicle routing problem in time-dependent network and has better computational efficiency and convergence speed.

Improved Ant Colony Algorithm and Its Simulation Study

Improved Ant Colony Algorithm and Its Simulation Study

Improved Ant Colony Algorithm to Solve the Aircraft Landing Problem

Scheduling aircraft landing is a complex task encountered by most of the control towers. In this paper, we study the aircraft landing problem (ALP) in the multiple runway case. We present in the first part, a mathematical formulation of the problem with a linear and nonlinear objective function. In the second part, we consider the static case of the problem where all data are known in advance and we present a new heuristic for scheduling aircraft landing on a single runway, this heuristic is incorporated into an ant colony algorithm to solve the multiple runway case.

The Improved Ant Colony Algorithm to predict Longitudinal Long-term Uneven Settlement of Shield Tunnel in Soft Soil

The Improved Ant Colony Algorithm to predict Longitudinal Long-term Uneven Settlement of Shield Tunnel in Soft Soil

Optimal Path Selection for Mine Emergency Rescue Based on Improved Ant Colony Algorithm

It is the primary task to ensure the safety of lives and property of underground workers with the increasing amount of coal mining. Under the actual complex environment of coal, all kinds of uncertian factors should be considered except for the distance for the selection of the optimal path to reduce casualties. Aiming at the defect of the lower solution accuracy and tending to fall into local optimal solution of the basic ant colony algorithm(ACA), an improved ant colony algorithm is presented based on the model of ACA. Experiment results show that the new algorithm can get better results.

Robust Design Optimization Based on Improved Ant Colony Algorithm with Application

The basic ant colony algorithm is improved by introducing chaos model of Logistic and discrete search in order to improve the global convergence. A program of improved ant colony algorithm has been designed by using Matlab. It can be used for solving optimal design problems with continuous variables, discrete variables or mixed-discrete variables. For an electric circuit, the design problem about the robustness of electric current is discussed and a model of robust optimal design is established. The solution of established model is achieved by using the proposed method and the robustness of the electric circuit has been improved. The example shows that the proposed method is effective in engineering design.

Application of Improved Ant Colony Algorithm in QoS Routing Optimization

QoS routing for the characteristics of the ant colony algorithm is improved. First of all defect from the ant colony algorithm and to increase Network Node bound, As well as to speed up global convergence analysis of the three areas of the ant colony algorithm to improve thinking; And by improving the ant colony algorithm in the QoS routing optimization application, the details of the ant colony algorithm to improve the design and implementation steps. Finally, simulation results show that: According to the algorithm for solving the problem and get the optimal solution of the ratio of full proof of improvement in the ant colony algorithm QoS routing optimization on the effectiveness and stability.

Improved ant colony algorithm in the distribution of reactive power compensation device and optimization

Ant colony algorithm is a kind of simulation of collaborative optimization algorithm of ants foraging, imitating ants dependence information communication and social behavior, showing in the agents, on the basis of the definition of a greedy method under the guidance of the catalytic process guide each agent. Put forward improved ant colony algorithm is applied to power system of reactive power optimization, to IEEE14 node system by simulation calculation, the optimal scheme of reactive power compensation, the optimization design and improvement of ant colony algorithm of the optimization results can be more effectively at or near the optimal.

Study on Improved Ant Colony Algorithm in Dynamic Multi-Paths Route Guidance System

The traditional Dynamic Route Guidance System (DRGS) provides only the optimal path to the travelers, which may easily lead to aggregative response of the travelers and overcrowding drift. This paper presents an approach based on Ant Colony Optimization (ACO) for solving the k-shortest paths problem in DRGS. In order to improve the convergence rate, the basic ACO is improved by introducing direction function the weight coefficient of which can be adjusted to vary state transition rule and standardized transformation to eliminate the influence of the size and dimension of pheromone and heuristic information. Compared with basic ACO, simulation experiments indicate that the improved ACO is more effective and efficient.

An Improved Ant Colony Algorithm for the Shortest Path Problem in Time-Dependent Networks

Research of the shortest path problem in time-dependent networks has important practical value. An improved pheromone update strategy suitable for time-dependent networks was proposed. Under this strategy, the residual pheromone of each road can accurately reflect the change of weighted value of each road. An improved selection strategy between adjacent cities was used to compute the cities' transfer probabilities, as a result, the amount of calculation is greatly reduced. To avoid the algorithm converging to the local optimal solution, the ant colony algorithm was combined with genetic algorithm. In this way, the solutions after each traversal were used as the initial species to carry out single-point crossover. An improved ant colony algorithm for the shortest path problem in time-dependent networks based on these improved strategies was presented. The simulation results show that the improved algorithm has greater probability to get the global optimal solution, and the convergence rate of algorithm is better than traditional ant colony algorithm.

Algorithm for Low Altitude Penetration Aircraft Path Planning with Improved Ant Colony Algorithm

The ant colony algorithm is a new class of population basic algorithm. The path planning is realized by the use of ant colony algorithm when the plane executes the low altitude penetration, which provides a new method for the path planning. In the paper the traditional ant colony algorithm is improved, and measures of keeping optimization, adaptively selecting and adaptively adjusting are applied, by which better path at higher convergence speed can be found. Finally the algorithm is implemented with computer simulation and preferable results are obtained.

Searching for Agent Coalition for Single Task Using Improved Ant Colony Algorithm

Searching for Agent Coalition for Single Task Using Improved Ant Colony Algorithm