Showing 3 results for Ant Colony
K. Eshgee and M. Kazemi,
Volume 23, Issue 1 (7-2004)
Abstract
In this paper, a new algorithm for solving the single loop routing problem is presented. The purpose of the single loop routing problem(SLRP) is to find the shortest loop for an automated guided vehicle covering at least one edge of each department of a block layout. First it shown that this problem can be represented as a graph model. Then a meta-heuristic algorithm based on and colony system is developed for ALRP by using the properties of the graph model. Computational results show the efficiency of the proposed algorithm in comparison with other techniques for solving SLRP.
M. Eftekhari, B. Daei, and S. D. Katebi,
Volume 25, Issue 1 (7-2006)
Abstract
A novel version of Ant Colony Optimization (ACO) algorithms for solving continuous space problems is presented in this paper. The basic structure and concepts of the originally reported ACO are preserved and adaptation of the algorithm to the case of continuous space is implemented within the general framework. The stigmergic communication is simulated through considering certain direction vectors which are memorized. These vectors are normalized gradient vectors that are calculated using the values of the evaluation function and the corresponding values of object variables.
The proposed Gradient-based Continuous Ant Colony Optimization (GCACO) method is applied to several benchmark problems
and the results are compared and contrasted with other population-based algorithms such as Evolutionary Strategies (ES), Evolutionary Programming (EP), and Genetic Algorithms (GA). The results obtained from GCACO compare satisfactorily with those of other algorithms and in some cases are superior in terms of accuracy and computational demand.
R. Moeini,
Volume 36, Issue 1 (9-2017)
Abstract
In this paper, the features of Ant Colony Optimization Algorithm (ACOA) are used to find optimal size for sewer network. Two different formulations are proposed. In the first formulation, pipes diameters and in the second formulation, nodal elevations of sewer network are taken as decision variables of the problem. In order to evaluate the performance of different ACOAs, four algorithms of Ant System, Elitist Ant System, Ranked Ant System and Max-Min Ant System are used to solve this optimization problem. Different test examples are solved using two proposed formulations for each ACOAs and the results are presented and compared with other available results. The results indicate the efficiency of the proposed methods in the solation of sewer network design optimization problem and the results of Max-Min Ant System are better in comparison with other ACOAs.
