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      The biological principles of swarm intelligence

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      Swarm Intelligence
      Springer Nature

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          Ant system: optimization by a colony of cooperating agents.

          An analogy with the way ant colonies function has suggested the definition of a new computational paradigm, which we call ant system (AS). We propose it as a viable new approach to stochastic combinatorial optimization. The main characteristics of this model are positive feedback, distributed computation, and the use of a constructive greedy heuristic. Positive feedback accounts for rapid discovery of good solutions, distributed computation avoids premature convergence, and the greedy heuristic helps find acceptable solutions in the early stages of the search process. We apply the proposed methodology to the classical traveling salesman problem (TSP), and report simulation results. We also discuss parameter selection and the early setups of the model, and compare it with tabu search and simulated annealing using TSP. To demonstrate the robustness of the approach, we show how the ant system (AS) can be applied to other optimization problems like the asymmetric traveling salesman, the quadratic assignment and the job-shop scheduling. Finally we discuss the salient characteristics-global data structure revision, distributed communication and probabilistic transitions of the AS.
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            Models of division of labor in social insects.

            Division of labor is one of the most basic and widely studied aspects of colony behavior in social insects. Studies of division of labor are concerned with the integration of individual worker behavior into colony level task organization and with the question of how regulation of division of labor may contribute to colony efficiency. Here we describe and critique the current models concerned with the proximate causes of division of labor in social insects. The models have identified various proximate mechanisms to explain division of labor, based on both internal and external factors. On the basis of these factors, we suggest a classification of the models. We first describe the different types of models and then review the empirical evidence supporting them. The models to date may be considered preliminary and exploratory; they have advanced our understanding by suggesting possible mechanisms for division of labor and by revealing how individual and colony-level behavior may be related. They suggest specific hypotheses that can be tested by experiment and so may lead to the development of more powerful and integrative explanatory models.
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              Ant Algorithms for Discrete Optimization

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                Author and article information

                Journal
                Swarm Intelligence
                Swarm Intell
                Springer Nature
                1935-3812
                1935-3820
                October 17 2007
                July 17 2007
                : 1
                : 1
                : 3-31
                Article
                10.1007/s11721-007-0004-y
                5829fbb1-6644-4e2c-b4bc-a83af83d72c9
                © 2007
                History

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