为解决车辆分配问题，对一个多元优化组合元数据库进行了开发和实施
Diseño e implementación de una meta-heurística multi-poblacional de optimización combinatoria enfocada a la resolución de problemas de asignación de rutas a vehículos
摘要：
交通运输是当今社会的一个重要领域，无论是商业部门还是公民。有不同种类的运输系统，每一种都有自己的特点。同样，各种知识领域可以有效地处理交通规划。大多数与运输和物流相关的问题具有共同的特征，因此它们可以建模为优化问题，能够将它们视为其他一般问题的特殊情况。这些问题属于组合优化领域。这类问题大多异常复杂。大量的元分析学可以在文献中找到，每一种都有其优点和缺点。由于组合优化问题的高度复杂性，目前还没有一种技术能够最优地解决所有这些问题。这使得组合优化和车辆路径问题成为研究的热点。本博士论文将致力于开发一种新的元启发式算法来解决不同类型的车辆路径问题。与现有方法相比，所提出的技术提供了附加值，无论是在性能方面，还是在概念原创性方面。与验证所提出的模型的目的，所得到的结果与其他四个算法的类似的哲学得到的开发元启发式。四个著名的布线问题已被用于本实验中，以及两个经典的组合优化问题。除了基于平均值或标准差等参数的比较外，还进行了两种不同的统计检验。由于这些测试，可以肯定的是，所提出的元启发式是有竞争力的性能和概念的独创性。
英文摘要：
Transportation is an essential area in the nowadays society, both for business sector and citizenry. There are different kinds of transportation systems, each one with its own characteristics. In the same way, various areas of knowledge can deal efficiently with the transport planning. The majority of the problems related with the transport and logistics have common characteristics, so they can be modeled as optimization problems, being able to see them as special cases of other generic problems. These problems fit into the combinatorial optimization field. Much of the problems of this type have an exceptional complexity. A great amount of meta-heuristics can be found the literature, each one with its advantages and disadvantages. Due to the high complexity of combinatorial optimization problems, there is no technique able to solve all these problems optimally. This fact makes the fields of combinatorial optimization and vehicle routing problems be a hot topic of research. This doctoral thesis will focus its efforts on developing a new meta-heuristic to solve different kind of vehicle routing problems. The presented technique offers an added value compared to existing methods, either in relation to the performance, and the contribution of conceptual originality. With the aim of validating the proposed model, the results obtained by the developed meta-heuristic have been compared with the ones obtained by other four algorithms of similar philosophy. Four well-known routing problems have been used in this experimentation, as well as two classical combinatorial optimization problems. In addition to the comparisons based on parameters such as the mean, or the standard deviation, two different statistical tests have been carried out. Thanks to these tests it can be affirmed that the proposed meta-heuristic is competitive in terms of performance and conceptual originality.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
