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检索条件"主题词=ant algorithms"

共 229 条记录，以下是81-90 订阅

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A non-Hybrid ant Colony Optimization Heuristic for Convergence Quality

A non-Hybrid Ant Colony Optimization Heuristic for Convergen...

引用

IEEE International Conference on Systems, Man, and Cybernetics (SMC)

作者： Krynicki, Kamil Houle, Michael E. Jaen, Javier Univ Politecn Valencia Dept Sistemas Informat & Computac Cami de Vera S-N E-46022 Valencia Spain Natl Inst Informat Chiyoda Ku Tokyo 1018430 Japan

ISBN: (纸本)9781479986965

ant Colony Optimization has proven to be an important optimization technique. It has provided a solid base for solving classical computational problems, networks routing problems and many others. Nonetheless, algorithms within the ant Colony metaheuristic have been shown to struggle to reach the global optimum of the search space, with only a few select ones guaranteed to reach it at all. On the other hand, ant Colony-based hybrid solutions that address this issue suffer from either severely decreased efficiency or low scalability and are usually static and custom-made, with only one particular use. In this paper we present a generic and robust solution to this problem, restricted rigorously to the ant Colony Optimization paradigm, named Angry ant Framework. It adds a new dimension - a dynamic, biologically-inspired pheromone stratification, which we hope can become the objective of further state-of-the-art research. We present a series of experiments to enable a discussion on the benefits provided by this new framework. In particular, we show that Angry ant Framework increases the efficiency, while at the same time improving the flexibility, the adaptability and the scalability with a very low computational investment.

关键词： ACO algorithms ant algorithms ant colony optimization Metaheuristics

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Design and Classification of ant Metaheuristics

Design and Classification of Ant Metaheuristics

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22nd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP)

作者： Zufferey, Nicolas Univ Geneva HEC CH-1211 Geneva 4 Switzerland

ISBN: (纸本)9781479927289

ant algorithms are well-known metaheuristics which have been widely studied and used since two decades. Generally, an ant is a constructive heuristic able to build a solution from scratch. However, other types of ant algorithms have recently emerged: the discussion is thus not limited by the common framework of the constructive ant algorithms. The goal of this paper is on the one hand to classify and benchmark the ant algorithms, and on the other hand to put forward the successful elements of these methods. Moreover, the performance of the different types of ant algorithms is evaluated according to several criteria, and not only according to the quality of the obtained solutions.

关键词： ant algorithms population-based metaheuristics

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ant Metaheuristic with Adapted Personalities for the Vehicle Routing Problem 6th

Ant Metaheuristic with Adapted Personalities for the Vehicle...

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6th International Conference on Computational Logistics (ICCL)

作者： Zufferey, Nicolas Farres, Jaime Glardon, Remy Univ Geneva GSEM Geneva Sch Econ & Management CH-1211 Geneva 4 Switzerland Univ Politecn Cataluna ETSEIB Barcelona Spain Ecole Polytech Fed Lausanne LGPP Lausanne Switzerland

ISBN: (纸本)9783319242644;9783319242637

At each generation of an ant algorithm, each ant builds a solution step by step by adding an element to it. Each choice is based on the greedy force (short term profit or heuristic information) and the trail system (central memory which collects information during the search process). Usually, all the ants of the population have the same characteristics and behaviors. In contrast in this paper, a new type of ant metaheuristic is proposed. It relies on the use of ants with different personalities. Such a method has been adapted to the well-known vehicle routing problem, and even if it does not match the best known results, its performance is encouraging (on one benchmark instance, new best results have however been found), which opens the door to a new ant algorithm paradigm.

关键词： Evolutionary metaheuristics ant algorithms Vehicle routing problem Combinatorial optimization

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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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A Hybrid ant-Based System for Gate Assignment Problem

A Hybrid Ant-Based System for Gate Assignment Problem

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3rd International Workshop on Hybrid Artificial Intelligence Systems

作者： Pintea, Camelia-M. Pop, Petrica C. Chira, Camelia Dumitrescu, D. Univ Babes Bolyai Cluj Napoca 400084 Romania North Univ Baia Mare 430083 Romania

ISBN: (纸本)9783540876557

This paper presents an ant system coupled with a local search applied to an over-constrained airport gate assignment problem (AGAP). In the airport gate assignment problem we are interested in selecting and allocating aircrafts to the gates such that the total passenger connection time is minimized. Our algorithm uses pheromone trail information to perform modifications on AGAP solutions, unlike traditional ant systems that use pheromone trail information to construct complete solutions. The algorithm is analyzed and compared with tabu search heuristic and ant Colony System metaheuristic.

关键词： ant algorithms assignment problems constraints t-test

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A Study of ant-Based Pheromone Spaces for Generation Perturbative Hyper-Heuristics 23

A Study of Ant-Based Pheromone Spaces for Generation Perturb...

引用

Genetic and Evolutionary Computation Conference (GECCO)

作者： Singh, Emilio Pillay, Nelishia Univ Pretoria Hatfield Gauteng South Africa

ISBN: (纸本)9798400701191

Recent work has shown the potential of ant algorithms for generation constructive hyper-heuristics. This paper extends the previous research by presenting a novel ant algorithm that is used to drive the heuristic search for a generation perturbative hyper-heuristic, the other type of generation hyper-heuristic. The ant-based generation perturbative hyper-heuristic is presented and compared against existing heuristics in two combinatorial domains, the movie scene scheduling and capacitated vehicle routing problems, to assess the heuristic generation efficacy. The comparison is further extended by assessing the effect of different pheromone maps (1D, 2D and 3D) on the ant-based hyper-heuristic, an important factor in the previous study. The results showed that, in both domains, the hyper-heuristic was able to generate perturbative heuristics that were competitive or better than the existing heuristics. Furthermore, the type of pheromone map was relevant to the hyper-heuristic performance as the 3D map performed best for the first domain and the 1D map for the second, confirming the trend shown in previous research, as well as the validity of ant algorithms for generation perturbative hyper-heuristics.

关键词： Generation perturbative hyper-heuristics ant algorithms discrete optimization

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The Effect of Pheromone in ant-based Hyper-heuristic

The Effect of Pheromone in Ant-based Hyper-heuristic

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2nd International Conference on Mechanics and Control Engineering (ICMCE 2013)

作者： Abd Aziz, Zalilah Univ Teknol MARA Fac Comp Sci & Math Shah Alam 40450 Selangor Malaysia

ISBN: (纸本)9783037859087

ant algorithms mimic the behavior of the ants where their important behavior is the ability to find the shortest path between food sources and their nest despite being almost blind. In the algorithms, as ants travel, they deposit a chemical substance called pheromone which;together with visibility values is used to make decisions. This paper investigates the effects of pheromone values on solving a routing problem;the capacitated vehicle routing problem (CVRP) In our approach, in order to produce a generalized approach, we developed an ant-based hyper-heuristic where pheromone and visibility values consider a non-domain specific knowledge. In this paper, we propose to provide all visited heuristics with some amount of pheromone. The distribution of pheromone values will be distributed proportioned to the performance done by the ants. This is to encourage the exploration of new edges that might lead to better solutions. We show that our results are better when compared to two other ant algorithm hyper-heuristics in the literature.

关键词： ant algorithms hyper-heuristic pheromone vehicle routing problem

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ant-Based Generation Constructive Hyper-heuristics for the Movie Scene Scheduling Problem 10th

Ant-Based Generation Constructive Hyper-heuristics for the M...

引用

10th International Conference on the Theory and Practice of Natural Computing (TPNC)

作者： Singh, Emilio Pillay, Nelishia Univ Pretoria Dept Comp Sci Pretoria South Africa

ISBN: (纸本)9783030904258;9783030904241

The task of generation constructive hyper-heuristics concerns itself with generating new heuristics for problem domains via some kind of mechanism that combines low-level heuristic components into new heuristics. The movie scene scheduling problem is a recently developed combinatorial problem for which there are relatively few low-level heuristics. This paper focused on the application of a novel ant-based generation constructive hyper-heuristic to develop new constructive heuristics for the problem. The ant-based generation constructive hyper-heuristic was applied to create components that were themselves produced from existing heuristics and domain knowledge regarding the movie scene scheduling problem. The results of the research demonstrated that the ant-based hyper-heuristic was successful in the domain. It outperformed the existing set of human-derived constructive heuristics across a wide variety of problem classes and over several instances within the movie scene scheduling problem. The success of this research suggests that other hyper-heuristic methods, such as a generation perturbative one, could be applied to the movie scene scheduling problem in the future.

关键词： Generation constructive hyper-heuristics ant algorithms Discrete combinatorial optimization

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An ant-algorithm for the weighted minimum hitting set problem

An ant-algorithm for the weighted minimum hitting set proble...

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IEEE Swarm Intelligence Symposium

作者： Cincotti, A Cutello, V Pappalardo, F Univ Catania Dept Math & Comp Sci I-95125 Catania Italy

We present an ant-based algorithm for finding good, near optimal solutions to Weighted Minimum Hitting Set problem. We compare our results with the ones obtained by a Greedy procedure and by an ad hoc genetic algorithm.

ISBN: (纸本)0780379144

关键词： ant algorithms weighted minimum hitting set combinatorial optimization NP-complete problems

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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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