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An effective solution to numerical and multi-disciplinary design optimization problems using chaotic slime mold algorithm

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A Correction to this article was published on 27 July 2021

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Abstract

Slime mold algorithm (SMA) is a recently developed meta-heuristic algorithm that mimics the ability of a single-cell organism (slime mold) for finding the shortest paths between food centers to search or explore a better solution. It is noticed that entrapment in local minima is the most common problem of these meta-heuristic algorithms. Thus, to further enhance the exploitation phase of SMA, this paper introduces a novel chaotic algorithm in which sinusoidal chaotic function has been combined with the basic SMA. The resultant chaotic slime mold algorithm (CSMA) is applied to 23 extensively used standard test functions and 10 multidisciplinary design problems. To check the validity of the proposed algorithm, results of CSMA has been compared with other recently developed and well-known classical optimizers such as PSO, DE, SSA, MVO, GWO, DE, MFO, SCA, CS, TSA, PSO-DE, GA, HS, Ray and Sain, MBA, ACO, and MMA. Statistical results suggest that chaotic strategy facilitates SMA to provide better performance in terms of solution accuracy. The simulation result shows that the developed chaotic algorithm outperforms on almost all benchmark functions and multidisciplinary engineering design problems with superior convergence.

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Authors and Affiliations

  1. School of Electronics and Electrical Engineering, Lovely Professional University, Phagwara, Punjab, India

    Dinesh Dhawale & Vikram Kumar Kamboj

  2. Department of Electrical Engineering, Priyadarshini College of Engineering, Nagpur, Maharashtra, India

    Dinesh Dhawale

  3. Department of Electronics and Communication Engineering, Bhagat Phool Singh Mahila Vishwavidyalaya, Khanpur Kalan, Haryana, India

    Priyanka Anand

  4. Schulich School of Engineering, University of Calgary, Alberta, Canada

    Vikram Kumar Kamboj

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Dhawale, D., Kamboj, V.K. & Anand, P. An effective solution to numerical and multi-disciplinary design optimization problems using chaotic slime mold algorithm. Engineering with Computers 38 (Suppl 4), 2739–2777 (2022). https://doi.org/10.1007/s00366-021-01409-4

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