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A novel variant of the salp swarm algorithm for engineering optimization

Jia Fuyun, Luo Sheng, Yin Guan, Ye Yin

Journal of Artificial Intelligence and Soft Computing Research

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2023

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Vol. 13. No. 3

131--149

EN

There are many design problems need to be optimized in various fields of engineering, and most of them belong to the NP-hard problem. The meta-heuristic algorithm is one kind of optimization method and provides an effective way to solve the NP-hard problem. Salp swarm algorithm (SSA) is a nature-inspired algorithm that mimics and mathematically models the behavior of slap swarm in nature. However, similar to most of the meta-heuristic algorithms, the traditional SSA has some shortcomings, such as entrapment in local optima. In this paper, the three main strategies are adopted to strengthen the basic SSA, including chaos theory, sine-cosine mechanism and the principle of quantum computation. Therefore, the SSA variant is proposed in this research, namely SCQ-SSA. The representative benchmark functions are employed to test the performances of the algorithms. The SCQ-SSA are compared with the seven algorithms in high-dimensional functions (1000 dimensions), seven SSA variants and six advanced variants on benchmark functions, the experiment reveals that the SCQ-SSA enhances resulting precision and alleviates local optimal problems. Besides, the SCQ-SSA is applied to resolve three classical engineering problems: tubular column design problem, tension/compression spring design problem and pressure vessel design problem. The design results indicate that these engineering problems are optimized with high accuracy and superiority by the improved SSA. The source code is available in the URL: https://github.com/ye-zero/SCQSSA/tree/main/SCQ-SSA.

2

Planning the location of facilities in the supply chain using the firefly meta-innovation algorithm

Shayannia Sayed Ahmad

Foundations of Computing and Decision Sciences

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2022

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Vol. 47, No. 4

433--454

EN

Analysis of supply chain location issues and decision-making regarding the location of facilities in the supply chain is one of the most important issues in the decision-making of governments, organizations and companies. Undoubtedly, the correct location of facilities has very important effects on economic benefits, providing appropriate services and customer satisfaction. Supply chain issue is one of the most widely used issues in today's competitive world and location issues are among the most used issues in designing supply chain networks to improve and reduce costs and increase competitiveness. The facilities under consideration include warehouses and distribution centers, which have been solved with the aim of reducing transportation costs. And then the two methods are compared. The problem is solved in small, medium and large dimensions and finally it was concluded that the firefly algorithm had a better performance than the genetic algorithm.

3

Modified blind naked mole-rat algorithm applied to electromagnetic design problems

Taherdangkoo Mohammad

Archives of Electrical Engineering

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2021

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Vol. 70, nr 2

167--380

EN

In this paper,we proposed a modified meta-heuristic algorithm based on the blind naked mole-rat (BNMR) algorithm to solve the multiple standard benchmark problems. We then apply the proposed algorithm to solve an engineering inverse problem in the electromagnetic field to validate the results. The main objective is to modify the BNMR algorithm by employing two different types of distribution processes to improve the search strategy. Furthermore, we proposed an improvement scheme for the objective function and we have changed some parameters in the implementation of the BNMR algorithm. The performance of the BNMR algorithm was improved by introducing several new parameters to find the better target resources in the implementation of a modified BNMR algorithm. The results demonstrate that the changed candidate solutions fall into the neighborhood of the real solution. The results show the superiority of the propose method over other methods in solving various mathematical and electromagnetic problems.