The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This article proposed an algorithm for solving traveling salesman problem from the perspective of geometry. At a given planar point distribution, search remote border points and connect these points to form a polygon circuit called outer ring including all the points, according to the same principle, search a polygon inner ring circuit among the points that aren't in outer ring. According to the principle...
Artificial immune algorithm has rapid and random overall search ability, but cannot utilize system feedback information sufficiently, which results in redundancy and iteration as well as low solving efficiency. Ant colony algorithm has distributed parallel overall search ability, and can be converged on optimal path by the accumulation and update of information pheromone, but there is a lack of early...
There has been growing interest in studying combinatorial optimization problems by clustering strategy, with a special emphasis on the traveling salesman problem (TSP). Since TSP naturally arises as a sub problem in many transportation, manufacturing and various logistics application, this problem has caught much attention of mathematicians and computer scientists. A clustering strategy will decompose...
By integrating the advantages of both PSO algorithm and ant colony algorithm, we present a hybrid discrete PSO algorithm with ant search for solving traveling salesman problem (TSP). In this algorithm, particle swarm search firstly, and worse chromosomes of the particle swarm is replaced by solutions obtained from ant colony search, so as to increase the diversity and improve the quality of the particle...
A new hybrid method iterative extended changing crossover operators which can efficiently obtain the optimum solution of the traveling salesman problem through flexibly alternating ant colony optimization (ACO) which simulates process of learning swarm intelligence in ants' feeding behavior and edge assembly crossover (EAX) which has been recently noticed as an available method for efficient selection...
The traveling salesman problem (TSP) is widely used in many real world problems. It is very important to design efficient algorithms for this problem. The key issue in TSP is that the computation cost will increase rapidly with the increasing of the size of the problem. To overcome the shortcoming, in this paper a novel evolutionary algorithm based on a clustering algorithm is proposed for TSP. The...
To resolve the contradictory among accelerating convergence, premature and stagnation in conventional ant colony algorithm, this paper proposes a novel ant colony algorithm with emphasis on data processing and dynamic city choice. Considering the importance of distance data, the proposed algorithm processes the data effectively. And it introduces symmetry and the number of allowed paths to adaptively...
A novel max-min ant system algorithm is proposed for the problem of setting pheromone trail value which is caused by uncertainty of the objective function value. The upper and lower bounds of pheromone are determined according to the range of objective function value by a random sampling. And the update quantity of pheromone is determined. As result of this process is not using the objective function...
Artificial immune algorithm has the ability of doing a global searching quickly and stochastically. But it can't make use of enough output information, and hence do a large redundancy repeat searching for the optimal solution, which reduces the efficiency of algorithm. Ant colony algorithm is convergent on the optimal path through pheromone accumulation an renewal, and has the ability of parallel...
A new improved algorithm called geese-inspired hybrid particle swarm optimization (geese-HPSO) was proposed based on the generalized PSO (GPSO) model and inspired by the characteristics of geese's flight. The new algorithm redesigned the updating operator for each particle as follows. For one thing, each particle intercrossed with the corresponding particle of the sorted population, which made the...
To avoid premature convergence and stagnation problems in classical ant colony system, a novel multi-behavior based multi-colony ant algorithm (MBMCAA) is proposed. The ant colony is divided into several sub-colonies; the sub-colonies have their own population evolved independently and in parallel according to four different behavior options, and update their local pheromone and global pheromone level...
In the ant colony system (ACS) algorithm, ants build tours mainly depending on the pheromone information on edges. The parameter settings of pheromone updating in ACS have direct effect on the performance of the algorithm. However, it is a difficult task to choose the proper pheromone decay parameters ?? and ?? for ACS. This paper presents a novel version of ACS algorithm for obtaining self-adaptive...
Aiming at the poor performance of convergence of ant colony optimization (ACO), in this paper, a novel pheromone initialization strategy of ACO for the traveling salesman problem (TSP) is put forward. More precisely, the pheromone matrix of a specific ACO algorithm is initialized by the minimal spanning tree (MST) information. Simulation results demonstrate that the proposed strategy could improve...
In previous study, we have proposed EHBSA within the EDA framework for permutation domains, and showed better performance than traditional GAs. The important feature of EHBSA is to use partial solutions from previous generations. In this paper, we analyze the effectiveness of using partial solutions using a wide range of problem sizes, without local search, and incorporating two types of local search...
The Transient Chaotic Neural Network (TCNN) and the Noisy Chaotic Neural Network (NCNN) have been proved their searching abilities for solving combinatorial optimization problems(COPs). The chaotic dynamics of the TCNN and the NCNN are believed to be important for their searching abilities. However, in this paper, we propose a strategy which cuts off the rich dynamics such as periodic and chaotic...
Currently, ant colony optimization (ACO) metaheuristic becomes the most prominent techniques applied in TSP. It is based on the cooperation of a complex society of ants through a chemical substance called pheromone. Several versions of metaheuristic ACOs' have been developed through several improvement processes to produce better algorithm. Past research has proposed a dynamic ant colony system with...
By analyzing the deficiency of traditional genetic algorithm in solving the Traveling Salesman Problem, an improved genetic algorithm is proposed for TSP. In this paper, the ordinal real-number encoder is used for chromosome encoding and ordered crossover operators is advanced that utilizes local and global information to construct offspring. In order to guarantee global convergence, heuristic knowledge...
This study examines combinations of different binary and unary operators to construct genetic algorithms for solving the traveling salesperson problem. Uniform order-based crossover, heuristic crossover, and edge recombination, are evaluated with inversion and reciprocal exchange mutations. Edge recombination was valuable in converging in the shortest number of generations, and order-based crossover...
In this paper, we discuss the process of low-volume and high-mix PCB assembly production in the electronic assembly industry and aim at an effective scheduling method to determine assembly sequence of different types of PCBs to reducing whole production time. The optimization problem can be modeled as an approximate traveling salesman problem (TSP) when considering the effect of machine setup time...
In this paper TSP (Traveling Salesman Problem) under dual constraints which any ant of colony can get stagnation or delay at any time but traffic network obstruction is not allowed is discussed in detail .The amended algorithm of MMAS (Max-Min Ant System) is put forward based on virtual broken factor. Compared with some other algorithms, it effectively protects network from potential safety hazard...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.