Integrating the artificial bee colony metaheuristic with Dhouib-Matrix-TSP1 heuristic for holes drilling problems

ABSTRACT

In this article, an innovative hybrid optimization method is proposed based on the integration of the Artificial Bee Colony metaheuristic and the Dhouib-Matrix-TSP1 heuristic to overcome the tool path minimization problem. The proposed methodology consists firstly of providing different feasible solutions by implementing Dhouib-Matrix-TSP1 with several descriptive statistical metrics. Then, these solutions will become a part of the initial population of the Artificial Bee Colony that will perform this population in order to generate the optimal solution. To validate and compare the proposed method, several experimental instances of multi-hole making are simulated. The used dataset consists of four rectangular layouts and two circular layouts with an arrangement from 25 to 2600 holes. Results show that the proposed method outperforms the standard metaheuristics with an improvement rate between 0.24% and 9.35%. The obtained improvements concern simultaneously the minimal path length, the mean path length, and the SD of path lengths.

Graphical Abstract

KEYWORDS:

• Artificial intelligence
• algorithms – heuristics and meta-heuristics
• engineering management
• materials handling – robotics

Article highlights

• Minimizing the holes drilling path is an NP-hard problem.

• A hybrid metaheuristic ABC-DM-TSP1 is proposed.

• An initial population is created by the heuristic DM-TSP1 for the ABC metaheuristic.

• Performance of the ABC-DM-TSP1 metaheuristic is compared with other methods.

• Results show that ABC-DM-TSP1 overcomes all other swarm methods.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/21681015.2022.2158499