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Multicast transmission corresponds to send data to several destinations, often involving requirements of Quality of Service (QoS) and Traffic Engineering (TE). These multiple requirements lead to the need of optimizing a set of conflicting objectives subject to constraints. Starting from the well-known evolutionary algorithm SPEA2, two formulations for the Routing problem were considered, minimizing...
In this work, a multiobjective genetic algorithm-based model for multicast flow routing with QoS and Traffic Engineering requirements is discussed. Two heuristics for subtree reconnection are investigated, applicable in crossover and mutation operators. Experiments with three multiobjective evolutionary algorithms (NSGA-II, SPEA and SPEA2) and the proposed heuristics are carried on, whose results...
Multicast transmission corresponds to send data to several destinations often involving requirements of Quality of Service (QoS) and Traffic Engineering (TE). This work investigates new evolutionary models to tackle Multicast Flow Routing in a Pareto multiobjective perspective. Two multiobjective evolutionary algorithms (SPEA and SPEA2) were applied as the underlying search of such models. QoS and...
One of the main problems in mobile agent migration is planning out an optimal migration path according to the agent tasks and other restrictions when agents migrate to several other hosts. The ant colony algorithm, which has the characteristic of parallelism, positive feedback and heuristic search, is a new evolutionary algorithm and is extremely suitable to the mobile agent migration problem. But...
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