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hMod: A software framework for assembling highly detailed heuristics algorithms

机译:hMod:用于组装高度详细的启发式算法的软件框架

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Software design and component reuse for heuristic algorithms have gained in relevance; however, further innovation is needed. In this context, hMod is presented as a software framework suited for implementing heuristic algorithms, with a focus on intensive reuse of highly cohesive operator and data components within algorithmic structures, making it possible to dynamically (re)configure and manage such a structure. Rather than a fast-prototyping tool, hMod supports heuristic implementation in the long term, whereby complexity can escalate from simple operators to major hyperheuristic architectures. In its core resides a novel object-oriented representation of algorithms through a pattern-like implementation, namely, algorithm assembling (AA). Additionally, it incorporates component integration features, such as dependency injection mechanisms. hMod has been mentioned in previous research, in which hyperheuristic methods were implemented and evaluated from an optimization perspective. In this work, a description of the framework is presented from the software design perspective, including the AA model, its architecture, and a detailed presentation of the main features of the framework. Previous hMod applications have demonstrated that it supports not only the software design requirements of heuristic algorithms but performance standards as well. Available sources of the framework can be found in http://gitlab.com/eurra/hmod.
机译:启发式算法的软件设计和组件重用已获得相关性;但是,还需要进一步的创新。在这种情况下,hMod作为适合于实施启发式算法的软件框架而呈现,其重点是算法结构内高凝聚力的运算符和数据组件的密集复用,从而可以动态(重新)配置和管理这种结构。 hMod并非长期使用快速原型工具,而是长期支持启发式实施,因此复杂性可能会从简单的运算符升级为主要的超启发式架构。它的核心是通过类似模式的实现,即算法组装(AA),以新颖的面向对象的方式表示算法。此外,它还包含组件集成功能,例如依赖项注入机制。在先前的研究中已经提到了hMod,其中从优化的角度实施并评估了超启发式方法。在这项工作中,从软件设计的角度对框架进行了描述,包括AA模型,其体系结构以及框架主要功能的详细描述。以前的hMod应用程序已证明,它不仅支持启发式算法的软件设计要求,而且还支持性能标准。该框架的可用资源可在http://gitlab.com/eurra/hmod中找到。

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