Abstract

A promising direction for solving complex optimization problems in construction is the heuristic approach, which is due to the objective ambiguity of the construction industry and provides a choice from a set of solutions based on analogy, similarity, similarity of the heuristic model or algorithm, which will take into account the experience of natural process to obtain a solution of complex many modal, many parametric and multicriterial problems, and the objective function of the activity is complex, very extreme, with gaps, with obstacles sometimes poorly defined (as a fuzzy function on fuzzy sets). It should be noted that the observation of natural neural networks, social forms of existence, populations and species is currently relevant and widely used. At one time, bionics gave impetus to the development of technical physics and engineering in general. In information technology, the study of wildlife processes can accelerate the development, creation and use of algorithms and mechanisms for processing information in wildlife, which are the result of long-term evolutionary selection. Such algorithms are called algorithms based on metaphor (metaheuristics or metaphor). To use metaphors to understand the strategy used, the method must be translated into the language of the applied field – construction and mathematical methods – in standard optimization terminology. An overview of the currently most common heuristic models and algorithms is performed, taking into account their features and areas of application. The features that are characteristic of construction tasks and the reasons for which they are due, and the relationships that are assigned to them. The main tasks solved in the construction industry for application in relation to their heuristic optimization are defined and considered. Based on the concepts of construction tasks, fields of construction tasks, information object of construction tasks, the analysis of the choice of metaphor for the task in the construction industry is carried out and the scheme of selection of metaphor is offered.

Highlights

  • (2010) Handbook of Metaheuristics (International Series in Operations Research & Management Science), Kluwer

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