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An ant algorithm for optimization of hole-making operations

COMPUTERS & INDUSTRIAL ENGINEERING 2007年第2期52卷 308-319页

作者： Ghaiebi, Heidar Solimanpur, Maghsud Urmia Univ Fac Engn Dept Mech Engn Orumiyeh Iran

This paper deals with the optimization of hole-making operations in conditions where a hole may need several tools to get completed. The objective of interest in the considered problem is to minimize the summation of tool airtime and tool switch time. This objective is affected by the sequence through which each operation of each hole is done. The problem is formulated as a 0-1 non-linear mathematical model. An ant algorithm is developed to solve the proposed mathematical model. The paper includes an illustrative example which shows the application of the proposed algorithm to optimizing the sequence of hole-making operations in a typical industrial part. The performance of the proposed algorithm is tested through solving six benchmark problems. The computational experience conducted in this research indicates that the proposed method is both effective and efficient. (c) 2007 Elsevier Ltd. All rights reserved.

关键词： hole-making optimization ant algorithms drilling

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antares: an ant-Inspired P2P Information System for a Self-Structured Grid

Antares: an Ant-Inspired P2P Information System for a Self-S...

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2nd International Conference on Bio-Inspired Models of Network, Information and Computing Systems

作者： Forestiero, Agostino Mastroianni, Carlo Spezzano, Giandomenico ICAR CNR Inst High Performace Comp & Networks I-87036 Arcavacata Di Rende CS Italy

ISBN: (纸本)9781424436491

This paper introduces antares, a bio-inspired algorithm that exploits ant-like agents to build a P2P information system in Grids. The work of agents is tailored to the controlled replication and relocation of metadata documents that describe Grid resources. These descriptors are indexed through binary strings that can either represent topics of interest, specifically in the case that resources are text documents, or be the result of the application of a locality preserving hash function, that maps similar resources into similar keys. Agents travel the Grid through P2P interconnections and, by the application of ad hoc probability functions, they copy and move descriptors so as to locate descriptors represented by identical or similar keys into neighbor Grid hosts. The effectiveness of the antares algorithm has been verified by event-driven simulation which proves that ant operations allow to achieve replication and spatial sorting of descriptors. The resulting information system is here referred to as self-structured, because it exploits the self-organizing characteristics of ant-inspired agents, and also because the association of descriptors to hosts is not pre-determined but easily adapts to the varying conditions of the Grid. This self-structured organization combines the benefits of both unstructured and structured P2P information systems. Indeed, being basically unstructured, antares is easy to maintain in a dynamic Grid, in which joins and departs of hosts can be frequent events. On the other hand, the aggregation and spatial ordering of descriptors can improve the rapidity and effectiveness of discovery operations, and also enables range queries, which are beneficial features typical of structured systems.

关键词： ant algorithms Grid Information Dissemination Information System Peer-to-Peer

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Binary ant Algorithm 07

Binary Ant Algorithm

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Annual Conference of Genetic and Evolutionary Computation Conference

作者： Fernandes, Carlos M. Rosa, Agostinho C. Ramos, Vitorino Univ Tecn Lisboa LaSEEB P-1049001 Lisbon Portugal

ISBN: (纸本)9781595936974

When facing dynamic optimization problems the goal is no longer to find the extrema, but to track their progression through the space as closely as possible. Over these kind of over changing, complex and ubiquitous real-world problems, the explorative-exploitive Subtle Counterbalance character of our Current state-of, the-art search algorithms should be biased towards an increased explorative behavior. While counterproductive in classic problems, the main and obvious reason of using it in severe dynamic problems is simple: while we engage Ourselves in exploiting the extrema, the extrema moves elsewhere. In order to tackle this Subtle compromise, we propose a novel algorithm for optimization in dynamic binary landscapes, stressing the role of negative feedback mechanisms. The Binary ant Algorithm (BAA) mimics some aspects of social insects' behavior. Like ant Colony Optimization (ACO), BAA acts by building pheromone maps over a graph of possible trails representing pseudo-solutions of increasing quality to a specific optimization problem, Main differences rely on the way this search space is represented and provided to the colony in order to explore/exploit it, while and more important, we enrol in providing strong evaporation to the problem-habitat. By a process of pheromone reinforcement and evaporation the artificial insect's trails over the graph converge to regions near the ideal solution of the optimization problem. Over each generation, positive feedbacks made available by pheromone reinforcement consolidate the best solutions found so far, while enhanced negative feedbacks given by the evaporation mechanism provided the system With Population diversity and fast self-adaptive characteristics, allowing BAA to be particularly suitable for severe complex dynamic optimization problems. Experiments made with some well known test functions frequently used in the Evolutionary algorithms' research field illustrate the efficiency of the proposed method. BAA was also co

关键词： ant algorithms Swarm Intelligence Stigmergy Dynamic Optimization

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Using taxonomies for content-based routing with ants

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COMPUTER NETWORKS 2007年第16期51卷 4514-4528页

作者： Michlmayr, Elke Pany, Arno Kappel, Gerti Vienna Univ Technol Womens Postgrad Coll Internet Technol Inst Software Technol & Interact Syst Vienna Austria Vienna Univ Technol Business Informat Grp Inst Software Technol & Interact Syst Vienna Austria

This paper presents the SEmant algorithm, a distributed content-based routing algorithm for peer-to-peer networks based on the ant Colony Optimization meta-heuristic. Under the assumption that the shared content in the network is annotated according to a taxonomy, it is possible to determine the hierarchical relationships between queries, and to exploit this information to improve the routing process. The experimental results presented in this paper show that the performance of content-based peer-to-peer search is highly dependent on the content distribution in the network and on the network's topology. It can be improved by exploiting the information provided by the underlying taxonomy. The degree of improvement is proportional to the degree of coherence in the content distribution. (c) 2007 Elsevier B.V. All rights reserved.

关键词： peer-to-peer search ant algorithms taxonomies

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A proof of convergence for ant algorithms

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INFORMATION SCIENCES 2004年第1-4期160卷 267-279页

作者： Badr, A Fahmy, A Cairo Univ Fac Comp & Informat Dept Comp Sci Cairo Egypt

A proof of convergence for ant algorithms is developed. ant algorithms were modeled as branching random processes: the branching random walk and branching Wiener process to derive rates of birth and death of ant paths. Substitution is then carried out in birth-death processes which proves that a stable distribution is surely reached. This indicates that ant algorithms converge with probability one. This analogy models ant algorithms complexity parameters such as the number of cycles, the degrees of freedom of problem and the number of ants. (C) 2003 Elsevier Inc. All rights reserved.

关键词： ant algorithms branching random walk branching Wiener process birth-death process convergence

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Geographical cells: Location-aware adaptive routing scheme for ad-hoc networks

Geographical cells: Location-aware adaptive routing scheme f...

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International Conference on Computer as a Tool (EUROCON 2007)

作者： Kudelski, Michal Pacut, Andrzej Warsaw Univ Technol Inst Control & Computat Engn PL-00665 Warsaw Poland

ISBN: (纸本)9781424408122

We introduce an novel approach to information management in ad-hoc networks, based on geographical cells concept. Geographical cells are used to comprise the information within the geographical location. We apply this approach to solve the problem of routing in ad-hoc networks for various mobility models. We show that the geographical cells approach may improve the overall performance of the underlying routing mechanism.

关键词： ad-hoc networks adaptive routing ant algorithms geographical routing information management

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Stigmergic Optimization in Dynamic Binary Landscapes 07

Stigmergic Optimization in Dynamic Binary Landscapes

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22nd ACM Symposium on Applied Computing

作者： Fernandes, Carlos Ramos, Vitorino Rosa, Agostinho C. Univ Tecn Lisbon LaSEEB P-1049001 Lisbon Portugal

ISBN: (纸本)9781595934802

Hereafter we introduce a novel algorithm for optimization in dynamic binary landscapes. The Binary ant Algorithm (BAA) mimics some aspects of real social insects' behavior. Like ant Colony Optimization (ACO), BAA acts by building pheromone maps over a grid of possible trails that represent solutions to an optimization problem. Main differences rely on the way this search space is represented and provided to the colony in order to explore/exploit it. Then, by a process of pheromone reinforcement and evaporation the artificial insect trails converge to regions near the problem solution or extrema. The negative feedback granted by the evaporation mechanism provides the self-organized system with population diversity and self-adaptive characteristics, allowing BAA to be particularly suitable for hard Dynamic Optimization Problems (DOP), where extrema continuously changes at severe speeds.

关键词： ant algorithms Stigmergy Dynamic Optimization

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An ant-based clustering algorithm for manufacturing cell design

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2006年第11-12期28卷 1182-1189页

作者： Kao, Y Fu, SC Tatung Univ 40 Dept Informat Management Taipei 104 Taiwan

This paper proposes a new part clustering algorithm that uses the concept of ant-based clustering in order to resolve machine cell formation problems. The three-phase algorithm mainly utilizes distributed agents which mimic the way real ants collect similar objects to form meaningful piles. In the first phase, an ant-based clustering model is adopted to form the initial part families. For the purpose of part clustering, a part similarity coefficient is modified and used in the similarity density function of the model. In the second phase, the K-means method is employed in order to achieve a better grouping result. In the third phase, artificial ants are used again to merge the small, refined part families into larger part families in a hierarchical manner. This would increase the flexibility of determining the number of final part families for the factory layout designer. The proposed algorithm has been developed into a software system called the ant-based part clustering system (APCS). In addition to part family formation, APCS performs the tasks of machine assignment and performance evaluation. Finally, performance evaluation of the proposed algorithm was conducted by testing some well-known problems from literature. The evaluation results show that the algorithm is able to solve the cell formation problems effectively.

关键词： ant algorithms cell formation problems cellular manufacturing

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Division of Labor in a Group of Robots Inspired by ants' Foraging Behavior

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ACM TRANSACTIONS ON AUTONOMOUS AND ADAPTIVE SYSTEMS 2006年第1期1卷 4-25页

作者： Labella, Thomas H. Dorigo, Marco Deneubourg, Jean-Louis Univ Libre Bruxelles IRIDIA B-1050 Brussels Belgium Univ Libre Bruxelles CENOLI B-1050 Brussels Belgium

In this article, we analyze the behavior of a group of robots involved in an object retrieval task. The robots' control system is inspired by a model of ants' foraging. This model emphasizes the role of learning in the individual. Individuals adapt to the environment using only locally available information. We show that a simple parameter adaptation is an effective way to improve the efficiency of the group and that it brings forth division of labor between the members of the group. Moreover, robots that are best at retrieving have a higher probability of becoming active retrievers. This selection of the best members does not use any explicit representation of individual capabilities. We analyze this system and point out its strengths and its weaknesses.

关键词： algorithms Performance Adaptive systems ant algorithms bio-inspired systems adaptation

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A high level stigmergic programming language

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2nd International Conference on Natural Computation (ICNC 2006)

作者： Mason, Zachary Efficient Frontier Inc Mountain View CA USA

ISBN: (纸本)3540459073

Terrestrial social insects build architecturally complex nests despite their limited sensors, minimal individual intelligence and the lack of a central control system. [3] Many of the nest structures emerge as a response of the individual insects to pheremones, which the insects themselves can emit.[2] The work in [4] extrapolated from social insect building behavior to a system where the behavior of homogenous swarms of virtual agents could be designed to build simple structures. Like termites, these agents have no memory and limited sensors, and the macroscopic structure emerges from their interactions with their immediate environments. This paper presents Stigcode, a swarm programming language that permits more complex structures to be more conveniently specified. A StigCode program is a description of a target structure that is compiled into a set of reactions to pheremone concentrations for the swarm agents. Though not Turing-Universal(1), StigCode provides a syntax for defining re-usable, composable design elements. In keeping with the entomorphic theme, In the manner of ant and termite nests, StigCode architectures can do limited self-repair.

关键词： stigmergy swarm intelligence stigmergic programming ant algorithms self-organization

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