A qualitative systematic review of metaheuristics applied to tension/compression spring design problem: Current situation, recommendations, and research direction
2023 (English)In: Engineering applications of artificial intelligence, ISSN 0952-1976, E-ISSN 1873-6769, Vol. 118, article id 105521Article in journal (Refereed) Published
Abstract [en]
New metaheuristic algorithms have soared over the past ten years. A common practice in proposing a new algorithm is validating it on several benchmark functions and engineering problems. Although CEC benchmark problems are specifically designed to validate the performance of new meta-heuristics, engineering design problems from pressure vessels to springs have been used in hundreds of papers to prove algorithm efficiency. To date, no benchmark practices have been established yet, i.e., researchers design their own benchmark to validate their algorithm. Thus, the high number of new algorithms combined with the high number of different benchmarking setups complicates the comparing and validating processes. In this paper, we study benchmark practices related to engineering applications. In particular, our exhaustive qualitative systematic review focuses on metaheuristics applied to the tension/compression spring design problem (TCSDP). The aim of this study is threefold: (i) evaluate where the field stands in regards of algorithm performance on the TCSDP, (ii) evaluate benchmarking practices, and (iii) facilitate future algorithm comparison. For these purposes, we first review all the existing metaheuristics applied to the TCSDP in their first publication. For each paper, we gather the data regarding the problem definition, the simulation setup, and the optimized design. We evaluated the data through several metrics to find the best-optimized design so far. Our findings and analysis concluded that the field of metaheuristics and its benchmarking practice have not reached maturity yet. Thus, we recommend some actions to address the issues and provide future research directions.
Place, publisher, year, edition, pages
Elsevier, 2023. Vol. 118, article id 105521
Keywords [en]
Benchmarking, Engineering optimization problem, Metaheuristics, Qualitative systematic review, Heuristic algorithms, Optimization, Compression springs, Current situation, Design problems, Engineering optimization problems, Metaheuristic, Optimized designs, Spring designs, Systematic Review, Tension-compression
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:hj:diva-63824DOI: 10.1016/j.engappai.2022.105521ISI: 000894964700007Scopus ID: 2-s2.0-85142904970OAI: oai:DiVA.org:hj-63824DiVA, id: diva2:1846366
2024-03-222024-03-222024-03-22Bibliographically approved