Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.13091/3949
Title: A multi-objective genetic algorithm for the hot mix asphalt problem
Authors: Altıok, Mustafa
Alakara, Erdinç Halis
Gündüz, Mesut
Ağaoğlu, Melih Naci
Keywords: Multi-objective
Fuzzy logic
Bituminous hot mixtures
Pareto-based
Hot mix asphalt problem
Recycled Concrete Aggregate
Fuzzy-Logic
Mechanical-Properties
Silica Fume
Elevated-Temperatures
Compressive Strength
Resilient Modulus
Waste
Prediction
Moea/D
Issue Date: 2022
Publisher: Springer London Ltd
Abstract: It is desirable for the work done in any construction process to be both cost-effective and durable. A thorough consideration of the matter reveals that the optimization of real-world problems involves multiple objectives. Bituminous hot mixtures, which are widely used in motorway construction, consist of aggregate and bitumen. The ratio between the different types of aggregate and bitumen forms the input to the real-world problem defined in this article, and the results of a test of the obtained asphalt in three different fields form the output. Our aim is to optimize these three outputs simultaneously to obtain a solution space with the most appropriate inputs. To optimize this problem, a new multi-objective optimization approach is proposed and tested in various ways and is finally adapted to the hot mix asphalt problem. Since the mathematical model of the objective function for this problem is fairly difficult, a fuzzy logic expert system is developed to act as the objective function. We believe that our approach to solving complex problems such as these forms a significant contribution to the literature.
Description: Article; Early Access
URI: https://doi.org/10.1007/s00521-022-08095-3
https://hdl.handle.net/20.500.13091/3949
ISSN: 0941-0643
1433-3058
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections

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