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A fast convergence EO-based multi-objective optimization algorithm using archive evolution path and its application to engineering design problems

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Abstract

Time-consuming objective functions are inevitable in practical engineering optimization problems. This kind of function makes the implementation of metaheuristic methodologies challenging since the designer must compromise between the quality of the final solution and the overall runtime of the optimization procedure. This paper proposes a novel multi-objective optimization algorithm called FC-MOEO/AEP appropriate for highly time-consuming objective functions. It is based on an equilibrium optimizer equipped with an archive evolution path (AEP) mechanism. The AEP mechanism considers the evolutionary trajectory of the decision space and anticipates the potential regions for optimal solutions. Besides having a high convergence rate, the newly proposed approach also possesses an intelligent balance between exploration and exploitation capabilities, enabling the algorithm to effectively avoid getting stuck in the local Pareto. To assess the efficacy of the FC-MOEO/AEP, a range of mathematical optimization problems and three real-world structural design problems were employed. In order to gauge the method's performance against other approaches, a novel performance indicator known as convergence speed was introduced and utilized, in addition to standard metrics. The numerical findings demonstrate the robust and consistent performance of the FC-MOEO/AEP in tackling complex multi-objective problems.

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Authors and Affiliations

  1. School of Civil Engineering, Iran University of Science and Technology, P.O. Box 16846-13114, Tehran, Iran

    Majid Ilchi Ghazaan, Pedram Ghaderi & Amirali Rezaeizadeh

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  1. Majid Ilchi Ghazaan
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MIG: Conceptualization, Supervision, Writing—Review and Editing PG: Conceptualization, Supervision, Writing—Review and Editing AR: Software, Formal analysis, Validation, Writing—Original Draft.

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Correspondence to Majid Ilchi Ghazaan.

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Ilchi Ghazaan, M., Ghaderi, P. & Rezaeizadeh, A. A fast convergence EO-based multi-objective optimization algorithm using archive evolution path and its application to engineering design problems. J Supercomput 79, 18849–18885 (2023). https://doi.org/10.1007/s11227-023-05362-5

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