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Minimizing the drilling robot arm movement by the advanced Dhouib-Matrix-4 metaheuristic

Souhail Dhouib

Concurrent Engineering Research and Applications2025https://doi.org/10.1177/1063293x241311734article
AJG 1
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0.37

What the paper says

Drilling holes on a Printed Circuit Board is a complicated task and it is usually ensured via a Computer Numerical Control (CNC) machine using a drilling robot arm. Commonly, to increase the performance of the CNC, the movement of its robot arm is minimized via the optimization of the holes drilling route. Hence, different metaheuristics are used to plan the shortest drilling route. In this purpose, we designed a novel metaheuristic namely Dhouib-Matrix-4 (DM4) and in this paper DM4 is enhanced with a Tabu list (T) and adapted to plan the shortest route for the drilling robot arm: the proposed method is entitled Dhouib-Matrix-4-Tabu (DM4-T). In fact, DM4-T combines two techniques in a multi-start structure: (i) An initial basic solution is generated using the novel Dhouib-Matrix-TSP1 heuristic (ii) this initial solution is intensified via the innovative Far-to-Near local search technique with the Tabu list. Experimental results indicate the performance and robustness of DM4-T to solve several instances up to 2152 holes. Indeed, DM4- T outperforms several existing metaheuristics in the literature such as Genetic Algorithm, Ants Colony Optimization, Integrated Genetic Simulated Annealing and Modified Shuffled Frog Leaping Algorithm.

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https://doi.org/https://doi.org/10.1177/1063293x241311734

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@article{souhail2025,
  title        = {{Minimizing the drilling robot arm movement by the advanced Dhouib-Matrix-4 metaheuristic}},
  author       = {Souhail Dhouib},
  journal      = {Concurrent Engineering Research and Applications},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1177/1063293x241311734},
}

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.