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Intelligent System to Emergencies Based on Ant Colony Optimization.

机译：基于蚁群优化的突发事件智能系统。

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摘要

The shortest path problem is a typical problem of optimization. This paper presents the ant colony opti- mization (ACO) algorithm to solve a problem of routing vehicles in a Fire Department of Leon, Mexico. In this work, diverse components are described to characterize this prob- lem through the use of a bioinspired algorithm. The algo- rithm was developed in Java, thus obtaining a tool which determines the best tracks to the vehicles. An experiment was realized to probe the validations, the results were used to compare it with Dijkstra algorithm and determine the quality of results. The future work of this research is determine an innovative perspective related to pheromone evaporation and as this topic is determinative to found and remember the best solutions quickly, additionally we compare it with a code from other postgraduate students trying to imple- ment an algorithm similar to Logistics but using a PSO and another with cultural algorithms.
机译：最短路径问题是优化的典型问题。本文提出了一种蚁群优化（ACO）算法，以解决墨西哥莱昂市消防局的车辆选路问题。在这项工作中，描述了多种组件以通过使用生物启发算法来表征此问题。该算法是用Java开发的，因此获得了一种确定车辆最佳行驶轨迹的工具。实现了一个实验以验证验证，将结果与Dijkstra算法进行比较并确定结果的质量。这项研究的未来工作是确定与信息素蒸发有关的创新观点，因为该主题对于迅速找到并记住最佳解决方案具有决定性作用，此外，我们将其与其他尝试实现类似算法的研究生的代码进行了比较。物流，但使用PSO和其他具有文化算法的产品。

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