Adaptive-Hybrid Harmony Search Algorithm for Multi-Constrained Optimum Eco-Design of Reinforced Concrete Retaining Walls

Melda Yücel, Aylin Ece Kayabekir, Gebrail Bekdaş, Sinan Melih Nigdeli, Sanghun Kim and Zong Woo Geem
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Melda Yücel: Department of Civil Engineering, Istanbul University—Cerrahpaşa, Avcılar, Istanbul 34320, Turkey
Aylin Ece Kayabekir: Department of Civil Engineering, Istanbul University—Cerrahpaşa, Avcılar, Istanbul 34320, Turkey
Gebrail Bekdaş: Department of Civil Engineering, Istanbul University—Cerrahpaşa, Avcılar, Istanbul 34320, Turkey
Sinan Melih Nigdeli: Department of Civil Engineering, Istanbul University—Cerrahpaşa, Avcılar, Istanbul 34320, Turkey
Sanghun Kim: Department of Civil and Environmental Engineering, Temple University, Philadelphia, PA 19122, USA
Zong Woo Geem: College of IT Convergence, Gachon University, Seongnam 13120, Korea

Sustainability, 2021, vol. 13, issue 4, 1-19

Abstract: In the optimum design of reinforced concrete (RC) structural members, the robustness of the employed method is important as well as solving the optimization problem. In some cases where the algorithm parameters are defined as non-effective values, local-optimum solutions may prevail over the existing global optimum results. Any metaheuristic algorithm can be effective to solve the optimization problem but must give the same results for several runs. Due to the randomization nature of these algorithms, the performance may vary with respect to time. The essential and novel work done in this study is the comparative investigation of 10 different metaheuristic algorithms and two modifications of harmony search (HS) algorithm on the optimum cost design of RC retaining walls constrained with geotechnical and structural state limits. The employed algorithms include classical ones (genetic algorithm (GA), differential evaluation (DE), and particle swarm optimization (PSO)), proved ones on structural engineering applications (harmony search, artificial bee colony, firefly algorithm), and recent algorithms (teaching–learning-based optimization (TLBO), flower pollination algorithm (FPA), grey wolf optimization, Jaya algorithm (JA)). The modifications of HS include adaptive HS (AHS) concerning the automatic change of algorithm parameters and hybridization of AHS with JA that is developed for the investigated problem. According to the numerical investigations, recent algorithms such as TLBO, FPA, and JA are generally the best at finding the optimum values with less deviation than the others. The adaptive-hybrid HS proposed in this study is also competitive with these algorithms, while it can reach the best solution by using a lower population number which can lead to timesaving in the optimization process. By the minimization of material used in construction via best optimization, sustainable structures that support multiple types of constraints are provided.

Keywords: reinforced concrete retaining wall; optimum design; metaheuristics; harmony search; Jaya algorithm; hybrid algorithm (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
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