XOR binary gravitational search algorithm with repository: Industry 4.0 applications

Mojtaba Ahmadieh Khanesar*, Ridhi Bansal, Giovanna Martínez-Arellano, David T. Branson

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

6 Citations (Scopus)


Industry 4.0 is the fourth generation of industry which will theoretically revolutionize manufacturing methods through the integration of machine learning and artificial intelligence approaches on the factory floor to obtain robustness and speed-up process changes. In particular, the use of the digital twin in a manufacturing environment makes it possible to test such approaches in a timely manner using a realistic 3D environment that limits incurring safety issues and danger of damage to resources. To obtain superior performance in an Industry 4.0 setup, a modified version of a binary gravitational search algorithm is introduced which benefits from an exclusive or (XOR) operator and a repository to improve the exploration property of the algorithm. Mathematical analysis of the proposed optimization approach is performed which resulted in two theorems which show that the proposed modification to the velocity vector can direct particles to the best particles. The use of repository in this algorithm provides a guideline to direct the particles to the best solutions more rapidly. The proposed algorithm is evaluated on some benchmark optimization problems covering a diverse range of functions including unimodal and multimodal as well as those which suffer from multiple local minima. The proposed algorithm is compared against several existing binary optimization algorithms including existing versions of a binary gravitational search algorithm, improved binary optimization, binary particle swarm optimization, binary grey wolf optimization and binary dragonfly optimization. To show that the proposed approach is an effective method to deal with real world binary optimization problems raised in an Industry 4.0 environment, it is then applied to optimize the assembly task of an industrial robot assembling an industrial calculator. The optimal movements obtained are then implemented on a real robot. Furthermore, the digital twin of a universal robot is developed, and its path planning is done in the presence of obstacles using the proposed optimization algorithm. The obtained path is then inspected by human expert and validated. It is shown that the proposed approach can effectively solve such optimization problems which arises in Industry 4.0 environment.

Original languageEnglish
Article number6451
JournalApplied Sciences (Switzerland)
Issue number18
Publication statusPublished - Sept 2020

Bibliographical note

Funding Information:
Funding: This work is funded and supported by the Engineering and Physical Sciences Research Council (EPSRC) under grant number: EP/R021031/1—New Industrial Systems: Chatty Factories.

Publisher Copyright:
© 2020 by the authors.


  • Assembly task planning
  • Discrete binary optimization problems
  • Gravitational search algorithm (GSA)
  • Physic inspired optimization algorithms
  • Universal robot


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