A hybrid immune genetic algorithm with tabu search for minimizing the tool switch times in CNC milling batch-processing

Shi, Shuangyuan; Xiong, Hegen

doi:10.1007/s10489-021-02869-3

Cited by 8 publications

(3 citation statements)

References 42 publications

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“…Adaptive immune genetic algorithm is an advanced algorithm developed by a combination of various disciplines in recent years, it is developed based on immune genetics and genetic algorithm, it is an improved genetic algorithm based on biological immune mechanism. e idea of an artificial immune system mainly comes from the theory of biological immunity, and its research results have been widely used in many fields, such as data processing, optimization learning, machine control, and other fields, the research of artificial immune system has been another new research hotspot of artificial intelligence [12].…”

Section: Aiga In Multiobjective Logistics Distribution Pathmentioning

confidence: 99%

Design and Optimization of E-Commerce Logistics Distribution System Based on Multiobjective Function

Wen

2022

Journal of Control Science and Engineering

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To reduce the complexity and multiple constraints of logistics distribution routing problems, the author proposes an improved genetic algorithm, adaptive immune genetic algorithm (AIGA). The algorithm utilizes a new immune vaccine selection strategy and immune operation method, the optimization process is adaptively changed with the evolutionary algebra, combined with the parallel selection method to optimize the multiobjective logistics distribution path, and the specific steps to solve the multiobjective logistics distribution path problem are given. The experimental results show that the optimal path is calculated as 0—2—8—5—3—1—0; 0—4—7—6—0. AIGA not only efficiently converges to the optimal solution but also stabilizes to a fitness value of 66.5, reflecting better precision than IGA. The computational efficiency and convergence of the algorithm are significantly improved, which verifies the practicability and effectiveness of the algorithm. The adaptive immune genetic algorithm realizes the path optimization of complex logistics distribution, which can better change the global search performance of the original immune genetic algorithm, greatly improve the algorithm convergence speed, and achieve good results in practical applications.

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Section: Aiga In Multiobjective Logistics Distribution Pathmentioning

confidence: 99%

Design and Optimization of E-Commerce Logistics Distribution System Based on Multiobjective Function

Wen

2022

Journal of Control Science and Engineering

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“…Their version of variable neighbourhood search was used to decompose a complex and sizable solution space into simple multi-neighbourhood areas. An approach combining Tabu search, and GA was proposed by Shi and Xiong [17]. The goal of their hybrid approach was to minimize the tool changeover times in computer numerical control (CNC) milling.…”

Section: Introductionmentioning

confidence: 99%

GA-AHP Method to Support Robotic Polishing Process Planning

Wang

Ding

Dailami

et al. 2022

Digital Manufacturing Technology

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The finishing stage of mould manufacturing is generally completed via mechanical polishing and manually conducted. Not only is this the most expensive phase of the process but also is currently struggling with a deficit of skilled workers. To address these issues, and support the wider needs of Industry 4.0, the manufacturing community has investigated robotic technologies to support the polishing process. The work reported here, investigating the polishing process planning and optimization for mould manufacture is part of a larger project aiming to automate 80% of the current manual process. Presented in this article is an optimization strategy for robotic polishing process sequencing aiming at satisfying polishing sequence rules and the shortest polishing time simultaneously. A hybrid approach combining both genetic algorithm (GA) and analytical hierarchical process (AHP) is proposed based on the specific characteristics of polishing process sequencing. A multi-objective fitness function is defined using AHP including the calculation of polishing time and evaluation of polishing process rules. The proposed GA-based process sequencing has been successfully demonstrated on test piece examples.

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“…That is why, there is a continuous quest for improving the performances of the genetic algorithms. GAs have been applied successfully to various problems, see for further details [38,40,41].…”

Section: Introductionmentioning

confidence: 99%

A Comparative Study between Haploid Genetic Algorithms and Diploid Genetic Algorithms

PETROVAN¹,

Matei²,

Pop³

2022

CJM

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In this paper, we make a comprehensive comparison in terms of the quality of the achieved solutions, the corresponding execution time and impact of the genetic operators on the quality of the results between the Haploid Genetic Algorithms (HGAs) and Diploid Genetic Algorithms (DGAs). The standard genetic algorithms, referred to in our paper as HGAs are characterized by the fact that they are using a haploid representation relating an individual with a chromosome, while the DGAs are using diploid individuals which are made of two chromosomes corresponding to the dominant and recessive genes. Even though the general opinion is that DGAs do not provide much benefit as compared to classical GAs, based on extensive computational experiments, we do show that the DGAs are robust, have a high degree of consistency and perform better, sometimes almost twice as well, than the HGAs, but are slower due to the high number of operations to be performed, caused by the duplication of the genetic information. However, the quality of the solutions achieved by the DGAs compensate their relative high execution time. The better quality of the DGAs, proving the efficiency of using diploid genes, is given by the homogeneity of the population which covers the search space thoroughly and in this way being capable of avoiding the local optima.

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A hybrid immune genetic algorithm with tabu search for minimizing the tool switch times in CNC milling batch-processing

Cited by 8 publications

References 42 publications

Design and Optimization of E-Commerce Logistics Distribution System Based on Multiobjective Function

Design and Optimization of E-Commerce Logistics Distribution System Based on Multiobjective Function

GA-AHP Method to Support Robotic Polishing Process Planning

A Comparative Study between Haploid Genetic Algorithms and Diploid Genetic Algorithms

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