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Artificial ant algorithm for Constrained Optimization

Journal of Systems Science and Systems Engineering 2001年第1期13卷 57-61页

作者： MA Liang, WANG Long de College of Management, University of Shanghai for Science and Technology, Shanghai 200093, China College of Management University of Shanghai for Science and Technology Shanghai 200093 China

：In this paper, we propose a new artificial ant algorithm for solving constrained optimization problems in general case. Numerical examples show that it is effective and robust.

关键词： ant algorithm constrained optimization

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Analysis on a mobile agent-based algorithm for network routing and management

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IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS 2003年第3期14卷 193-202页

作者： Sum, J Shen, H Leung, CS Young, G Hong Kong Polytech Univ Dept Comp Hong Kong Hong Kong Peoples R China Japan Adv Inst Sci & Technol Grad Sch Informat Sci Tatsunokuchi Ishikawa 9231292 Japan City Univ Hong Kong Dept Elect Engn Kowloon Hong Kong Peoples R China Calif State Polytech Univ Pomona Dept Comp Sci Pomona CA 91768 USA

ant routing is a method for network routing in the agent technology. Although its effectiveness and efficiency have been demonstrated and reported in the literature, its properties have not yet been well studied. This paper presents some preliminary analysis on an ant algorithm in regard to its population growing property and jumping behavior. For synchronous networks, three main results are shown. First, the expected number of agents in a node is shown to be no more than (1 + max(i){\Omega(i)\})km, where \Omega(i)\ is the number of neighboring hosts of the ith host, k is the number of agents generated per request, and m is the average number of requests. Second, the expected number of jumps of an agent is shown to be no larger than (1 + max(i){\Omega(i)\}). Third, it is shown that for all p greater than or equal to (1 + max(i){\Omega(i)\})km, the probability of the number of agents in a node exceeding p is not greater than integral(p)(infinity) P(x)dx, where P(x) is a normal distribution function with mean and variance given by Mean = (1 + max(i){\Omega(i)\})km,Var. = 2km(1 + max(i){\Omega(i)\}) + (km(2)(1 + max(i){\Omega(i)\})(2) / (1+2 max(i){\Omega(i)\}). The first two results are also valid for the case when the network is operated in asynchronous mode. All these results conclude that as long as the value max(i){\Omega(i)\}) is known, the practitioner is able to design the algorithm parameters, such as the number of agents being created for each request, k, and the maximum allowable number of jumps of an agent, in order to meet the network constraint.

关键词： mobile agents routing algorithms networking routing ant algorithm

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A control framework for ant-based routing algorithms

A control framework for ant-based routing algorithms

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Congress on Evolutionary Computation (CEC)

作者： Leith, C Takahara, G Queens Univ Dept Math & Stats Kingston ON K7L 3N6 Canada

ISBN: (纸本)0780378040

We propose a new framework for ant-based routing algorithms which addresses the trade-off between effective and timely discovery of optimal routes, and the desire to keep data traffic flowing smoothly. The approach utilizes a database of stored delay estimates on routes to build separate routing tables for ants and data packets. This decoupling results in better control of responsiveness to load or topology fluctuations since the tables can evolve at different rates, according to different rules. The presented architecture also features guaranteed loop-free routes for data packets.

关键词： ant algorithm dynamic routing updates with memory control of responsiveness loop-free routes

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Multi colony ant algorithms

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JOURNAL OF HEURISTICS 2002年第3期8卷 305-320页

作者： Middendorf, M Reischle, F Schmeck, H Katholische Univ Eichstatt Fachgrp Informat D-85072 Eichstatt Germany Univ Karlsruhe Inst Angew Informat & Formale Beschreibungsverfah D-76128 Karlsruhe Germany

In multi colony ant algorithms several colonies of ants cooperate in finding good solutions for an optimization problem. At certain time steps the colonies exchange information about good solutions. If the amount of exchanged information is not too large multi colony ant algorithms can be easily parallelized in a natural way by placing the colonies on different processors. In this paper we study the behaviour of multi colony ant algorithms with different kinds of information exchange between the colonies. Moreover we compare the behaviour of different numbers of colonies with a multi start single colony ant algorithm. As test problems we use the Traveling Salesperson problem and the Quadratic Assignment problem.

关键词： ant algorithm quadratic assignment traveling salesperson problem

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Multicast routing based on ant algorithm for delay-bounded and load-balancing traffic

Multicast routing based on ant algorithm for delay-bounded a...

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25th Annual IEEE Conference on Local Computer Networks (LCN 2000)

作者： Lu, GY Liu, ZM Zhou, Z Beijing Univ Posts & Telecommun Sch Telecommun Engn Beijing 1000876 Peoples R China

ISBN: (纸本)0769509126

Multicast routing is to find the paths from a service node re ail multicast destinations. In this paper;based on mrt algorithm;we propose a distributed multicast routing scheme with delay-bounded and load-balancing traffic in real-time communications. We first describe ant algorithm model and give ant-network model, then present art approach using ant algorithm to optimize the multicast routes with delay-bounded and load-balancing traffic. Finally simulation has been done to show the efficiency of the algorithm in the environment of OPNET simulation software, and the simulation results show that the proposed approach can find the best optimal multicast routes which can satisfy the delay-bounded requirement avoid to congested nodes.

关键词： multicast ant algorithm optimization pheromone table

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QoS Multicast Routing Based on ant algorithm in Internet

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The Journal of China Universities of Posts and Telecommunications 2000年第4期7卷 12-17页

作者： LU Guo ying, LIU Ze min (School of Telecommunication Engineering, Beijing University of Posts and Telecommunications,Beijing 100876,P.R.China) School of Telecommunication Engineering Beijing University of Posts and Telecommunications Beijing 100876 P.R. China

In this paper, based on ant algorithm, we propose a QoS multicast routing scheme in Internet. We first describe ant algorithm model and give ant network model, then present an approach using ant algorithm to optimize the multicast routes with QoS constaints. Finally, simulations has been made to show the efficiency of the approach in the environment of OPNET simulation software, and the simulation results show that the proposed approach can find the best optimal multicast routes which can satisfy the delay bounded requirement and avoid congested nodes as soon as possible.

关键词： multicast ant algorithm optimization pheromone table internet

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Finding the Minimum Ratio Traveling Salesman Tour by Artificial ants

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Chinese Journal of Systems Engineering and Electronics 2003年第3期000卷

ants of artificial colony are able to generate good solutions to the famous traveling salesman problem (TSP).We propose an artificial ants algorithm for solving the minimum ratio TSP, which is more general than the standard TSP in combinatorial optimization area. In the minimum ratio TSP, another criterion concerning each edge is added, that is,the traveling salesman can have a benefit if he travels from one city to another. The objective is to minimize the ratio between total costs or distances and total benefits. The idea of this type of optimization is in some sense quite similar to that of traditional cost-benefit analysis in management science. Computational results substantiate the solution quality and efficiency of the algorithm.

关键词： Minimum ratio TraveLing salesman problem ant algorithm

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Multiple ant colonies algorithm based on colony level interactions

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IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 2000年第2期E83A卷 371-379页

作者： Kawamura, H Yamamoto, M Suzuki, K Ohuchi, A Hokkaido Univ Grad Sch Engn Sapporo Hokkaido 0608628 Japan

Recently, researchers in various fields have shown interest in the behavior of creatures from the viewpoint of adaptiveness and flexibility. ants, known as social insects, exhibit collective behavior in performing tasks that can not be carried out by an individual ant. In ant colonies. chemical substances, called pheromones, are used as a way to communicate important information on global behavior. For example. ants looking for food lay the way back to their nest with a specific type of pheromone. Other ants can follow the pheromone trail and find their way to baits efficiently. In 1991, Colorni et al. proposed the ant algorithm for Traveling Salesman Problems (TSPs) by using the analogy of such foraging behavior and pheromone communication. In the ant algorithm, there is a colony consisting of many simple ant agents that continuously visit TSP cities with opinions to prefer subtours connecting near cities and they lay strong pheromones. The ants completing their tours lay pheromones of various intensities with passed subtours according to distances. Namely, subtours in TSP tourns that have the possibility of being better tend to have strong pheromones, so the ant agents specify good regions in the search space by using this positive feedback mechanism. In this paper, we propose a multiple ant colonies algorithm that has been extended from the ant algorithm. This algorithm as several ant colonies for solving a TSP, while the original has only a single ant colony. Moreover, two kinds of pheromone effects, positive and negative pheromone effects, are introduced as the colony-level interactions. As a result of colony-level interactions, the colonies can exchange good schemata for solving a problem and can maintain their own variation in the search process. The proposed algorithm shows better performance than the original algorithm with almost the same agent strategy used in both algorithms except for the introduction of colony-level interactions.

关键词： multi-agent system ant algorithm traveling salesman problems combinatorial optimization problems

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LOST: Localization-space trails for robot teams

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IEEE TRANSACTIONS ON ROBOTICS AND AUTOMATION 2002年第5期18卷 796-812页

作者： Vaughan, RT Stoy, K Sukhatme, GS Mataric, MJ Hughes Res Labs Malibu CA 90265 USA Univ So Denmark Maersk McKinney Moller Inst Prod Technol DK-5230 Odense M Denmark Univ So Calif Dept Comp Sci Los Angeles CA 90089 USA

We describe localization-space trails (LOST), a method that enables a team of robots to navigate between places of interest in an initially unknown environment using a trail of landmarks. The landmarks are not physical;they are waypoint coordinates generated online by each robot and shared with teammates. Waypoints are specified in each robot's local coordinate system, and contain references to features in the world that are relevant to the team's task and common to all robots. Using these task-level references, robots can share waypoints without maintaining a global coordinate system. The method is tested in a series of real-world multirobot experiments. The results demonstrate that the method: 1) copes with accumulating odometry error;2) is robust to the failure of individual robots;3) converges to the best route discovered by any robot in the team. In one experiment, a team of four autonomous mobile robots performs a resource transportation task in our uninstrumented office building. Despite significant divergence of their local coordinate systems, the robots are able to share waypoints, forming and following a common trail between two predetermined locations for more than three hours, traveling a total of 8.2 km (5.1 miles) before running out of power. Designed to scale to large populations, LOST is fully distributed, with low costs in processing, memory, and bandwidth. It combines metric data about the position of features in the world with instructions on how to get from one place to another;producing something between a map and a plan.

关键词： ant algorithm autonomous robot navigation

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Multicast routing based on ant-algorithm with delay and delay variation constraints

Multicast routing based on ant-algorithm with delay and dela...

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IEEE Asia-Pacific Conference on Circuits and Systems (APCCAS-2000)

作者： Lu, GY Liu, ZM Beijing Univ Posts & Telecommun Beijing 100088 Peoples R China

ISBN: (纸本)0780362535

In this paper, based on ant algorithm, we propose a distributed multicast routing scheme with delay-bounded and delay variation constraints in real-time communications. This paper first describes ant algorithm model and gives ant network model, then presents an approach using ant algorithm to optimize the multicast routes with delay and delay-variation constraints. The great amount of simulation has been done to show efficiency of the algorithm, and the simulation results show that the proposed approach can find the best optimal multicast routes which satisfy the above constraints.

关键词： Delay constrained multicast communication ant algorithm multicast routing

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