Titlebook: Swarm Intelligence; 8th International Co Marco Dorigo,Mauro Birattari,Thomas Stützle Conference proceedings 2012 Springer-Verlag Berlin Hei

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Fibroid

Task Partitioning via Ant Colony Optimization for Distributed Assemblytition general 2- and 3-D assembly tasks into N separate subtasks. The objective is to determine an allocation or partitioning strategy that minimizes the workload imbalance between the robots that allow for maximum assembly parallelization. This objective is achieved by extending ACO to apply to a

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The Self-adaptive Comprehensive Learning Particle Swarm Optimizer the particle swarm optimization (PSO) algorithm are critical to its success. This paper proposes that the control parameters of PSO be embedded in the position vector of particles and dynamically adapted while the search is in progress, relieving the user from specifying appropriate values before t

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Towards Swarm Calculus: Universal Properties of Swarm Performance and Collective Decisionsor artificial swarms. The ideal would be a ‘swarm calculus’ that allows to calculate key features such as expected swarm performance and robustness on the basis of a few parameters. A?path towards this ideal is to find methods and models that have maximal generality. We report two models that might

Offbeat

A Hybrid Particle Swarm Optimization Algorithm for the Open Vehicle Routing Problem popular supply chain management problems, the Open Vehicle Routing Problem. The Open Vehicle Routing Problem (OVRP) is a variant of the classic vehicle routing problem in which the vehicles do not return in the depot after the service of the customers. The proposed algorithm for the solution of the

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AcoSeeD: An Ant Colony Optimization for Finding Optimal Spaced Seeds in Biological Sequence Searchsed to improve the quality and sensitivity of searching, for example, in seeded alignment methods. Finding optimal spaced seeds is a NP-hard problem. In this study we introduce an application of an Ant Colony Optimization (ACO) algorithm to address this problem in a metaheuristics framework. This me

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