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In this paper we present the initial experimental results that we obtained with deploying our distributed agent-based system for Ant Colony Optimization (ACODA) on a computer cluster. The novelty of ACODA consists in agent-based modeling and distribution of the problem environment that is explored by the ants to determine an optimal solution. The effect of this approach is that ants' migration is...
This paper presents an improved algorithm for transmission expansion planning based on ant colony optimization, which is a heuristic optimization method showing several advantages compared to traditional methods. A grid model for the Nordic Area, Great Britain and a combination of both are used to show the performance of the optimization process. The focus of the work is to develop a tool for transmission...
Ant two-way parallel searching strategy is adopted to accelerate searching speed, but it is clearly seen that this tactic loses some feasible paths and even loses optimal path, so a new ants meeting judgment method is proposed in this paper. At the same time pheromone gain is added to allocate initial pheromone reasonably in order to deal with slow searching speed brought by equivalence distributing...
The Hungarian algorithm used in ontology matching sometimes cannot get the solution since this algorithm does not converge when dealing with special data. In order to solve this problem, this paper presents an improved ant colony optimization for ontology matching problem (ACOM). We utilize many kinds of rating functions which are also called base matchers to evaluate the distance of two ontology...
In order to make good use of the limited energy, ant colony optimization (ACO) was applied to inter-cluster routing mechanism. An uneven clustering routing algorithm for Wireless Sensor Networks (WSNs) based on ant colony optimization (ACO) was proposed. The algorithm utilized the dynamic adaptability and optimization capabilities of the ant colony to get the optimum route between the cluster head...
We present our initial work on the design and implementation of an efficient channel assignment and routing architecture for multi-radio and multichannel wireless mesh networks (WMNs). Our proposed scheme is derived from the principle of Ant Colony Optimization (ACO) in which smart ants (agents) perform the routing and channel assignment to stochastically solve a dynamic network optimization problem...
Cellular networks provide a range of communication services and are the principal wireless technology for domestic and business users. However, in cellular networks, an accident or a storm or a malicious action may cause a base station to fail and so be unable to provide radio coverage to sections of users. Such base station failures also might result in user congestion to nearby operational base...
Ant Colony Optimization (ACO) is a novel bionic evolutionary algorithm for solving complex combinatorial optimization problems. This research approach lies at initial stage at present, and a new adaptive ant algorithm is proposed for the traditional ant algorithm easily appears precocious and stagnation behavior phenomenon in this paper. And the traditional parameter of pheromone of ant colony algorithm...
There has been quite some research on the development of tools and techniques for grid systems, yet some important issues, e.g., grid service reliability and task scheduling in the grid, have not been sufficiently studied. For some grid services which have large subtasks requiring time-consuming computation, the reliability of grid service could be rather low. To resolve this problem, this paper introduces...
In this paper, we have proposed a novel algorithm based on Ant Colony Optimization (ACO) for finding near-optimal solutions for the Multi-dimensional Multi-choice Knapsack Problem (MMKP). MMKP is a discrete optimization problem, which is a variant of the classical 0-1 Knapsack Problem and is also an NP-hard problem. Due to its high computational complexity, exact solutions of MMKP are not suitable...
This paper identifies the key aspects of perishable food distribution problem in metropolis. A multi-objective model of vehicle routing problem with time window is constructed including fixed vehicle cost, operation cost, shelf life loss and default cost. In order to reduce the increase distribution cost via meeting the time window, two-generation Ant Colony Optimization with ABC customer classification...
The proposed work presented a modified MAX-MIN Ant System (MMAS) algorithm to solve the routing problem, in which known demand are supplied from a store house with parallel routes for new local search. Routing Problem is an optimization problem and solved to nearly optimum by heuristics. The objective of routing issues is to use a fleet of vehicles with specified capacity to serve a number of users...
The use of a swarm of autonomous robots for bushfire fighting is studied in this work. A novel distributed and behavioral control strategy, the Ant System with Negative Feedback (ASNF), is proposed. Inspired by real ants behavior under crowded conditions, ASNF differs from existing ant based algorithms by introducing a new pheromone, the Crowded Pheromone (CP), into the algorithmic framework. In ASNF,...
In DTNs, due to the unique characteristic of frequent partitioning, multicasting is a considerably different and challenging problem. Moreover, the single data multicast is different from multiple data multicast. In this paper, The mathematics model of multiple data multicast for DTNs is established, and the ant colony optimization algorithm introduce to solve the multiple data multicast problem....
In this paper, an improved ant colony optimization based approach for image edge detection is proposed. The algorithm use ant colony clustering approach to extract edge feature. The approach set the heuristics information function and the initial cluster, thus avoiding the search blindness which carried out by traditional ant colony algorithm. And a series of simulation experiments demonstrate the...
In CBR system, the case base is becoming increasingly larger with the incremental learning which results in the decline of case retrieval efficiency and its weaker performance. Aiming at such weakness of CBR system, this article proposes a novel case retrieval method based on Hybrid Ant-Fish Clustering Algorithm (HA-FC). At beginning of algorithm, we get rough cluster sets utilizing the advantage...
On-ramp control is the most effective and extensive way to improve freeway capacity. A proportional-integral (PI) control method based on ant colony optimization (ACO) is proposed to regulate the number of vehicles entering a freeway entrance point. First, a macroscopic traffic flow model is established. Then the basic principles of ant colony algorithm are formulated and the steps of ACO algorithm...
Algorithm parameters' influence on performance of ACOR (extension of ant colony optimization) is analyzed in this paper. Parameter establishment in ACOR is a multi-factor and multi-level optimization problem. And uniform design is introduced for solutions of high quantity to this problem through fewer experiments. This method is proved to be feasible and valid by simulation analysis in this paper.
Advertising income is a vital source of revenue for television stations. The arrangements made when customers purchase television advertising time should consider customer requirements, relevant laws and regulations, and the need to fill all available advertising time. This study presents an ant colony optimization (ACO) heuristic for establishing an effective and simple mechanism for solving the...
This paper is concerned with the problem of path planning in discrete-time pursuit-evasion games (PEGs) with obstacles. We present the so-called I-ACO (Improved Ant Colony Optimization) algorithm to plan paths for pursuers with efficiency and collision avoidance. The I-ACO algorithm can be divided into two modes, i.e. Approaching Mode and Capturing Mode, according to whether the evaders are sensed...
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