Black Hole Algorithm for Sustainable Design of Counterfort Retaining Walls

Víctor Yepes,José García,José V Martí

doi:10.3390/su12072767

Abstract

The optimization of the cost and CO 2 emissions in earth-retaining walls is of relevance, since these structures are often used in civil engineering. The optimization of costs is essential for the competitiveness of the construction company, and the optimization of emissions is relevant in the environmental impact of construction. To address the optimization, black hole metaheuristics were used, along with a discretization mechanism based on min–max normalization. The stability of the algorithm was evaluated with respect to the solutions obtained; the steel and concrete values obtained in both optimizations were analyzed. Additionally, the geometric variables of the structure were compared. Finally, the results obtained were compared with another algorithm that solved the problem. The results show that there is a trade-off between the use of steel and concrete. The solutions that minimize CO 2 emissions prefer the use of concrete instead of those that optimize the cost. On the other hand, when comparing the geometric variables, it is seen that most remain similar in both optimizations except for the distance between buttresses. When comparing with another algorithm, the results show a good performance in optimization using the black hole algorithm.

Highlights

The economic sustainability and social development of most countries depend directly on the reliable and lasting behavior of their infrastructure [1]
There has been a lot of research in the area of metaheuristics in recent years, and a large number of algorithms have been developed. Most of these algorithms have been inspired by physical, chemical, and biological systems [26]. As examples of these heuristic search algorithms that belong to this category, we find particle swarm optimization (PSO), harmony search (HS) [27], threshold acceptance (TA), simulated annealing (SA) [28,29], threshold acceptance (TA), genetic algorithms (GA), ant colonies (ACO), genetic algorithms (GA), whale optimization (WO), cuckoo search (CS), and black hole (BH), among others
This article studies a parametric optimization of a buttressed earth-retaining wall using a discrete black hole algorithm

Summary

Introduction

The economic sustainability and social development of most countries depend directly on the reliable and lasting behavior of their infrastructure [1]. Infrastructures have special relevance because they strongly influence economic activity, growth, and employment. These activities have a significant impact on the environment, have irreversible effects, and can compromise the present and future of society. We find that cement is one of the materials that generates large amounts of emissions. The optimization of structures that use large amounts of cement is critical. It is essential to develop lines of research in sustainable construction [4,5], energy consumption [6,7], and in the study of the cycle of the CO2 emissions made by concrete structures [8]. The great challenge is to have an infrastructure capable of maximizing its social benefit without compromising its sustainability [9]

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Conclusion