Differentiated Creative Search (DCS)

The DCS algorithm leverages teamwork, creativity, and knowledge for superior optimization problem-solving.
272 Downloads
Updated 14 Aug 2024
This work introduces Differentiated Creative Search (DCS), a groundbreaking optimization algorithm that revolutionizes traditional decision-making systems in complex environments. Differing from conventional differential evolution methods, DCS integrates a unique knowledge-acquisition process with a creative realism paradigm, thereby transforming optimization strategies. The primary aim of DCS is to enhance decision-making efficacy by employing a newly proposed dual-strategy approach that balances divergent and convergent thinking within a team-based framework. High-performing members apply divergent thinking using the DCS/Xrand/Linnik(α,σ) strategy, which incorporates existing knowledge and Linnik flights. Conversely, the rest of the team harnesses convergent thinking through the DCS/Xbest/Current-to-2rand strategy, which combines insights from both the team leader and fellow members. This division of labor, coupled with a strategy tailored to the performance levels of team members, allows for a dynamic and effective decision-making process. The methodology of DCS involves iterative cycles of divergent and convergent thinking, supported by a differentiated knowledge-acquisition process and retrospective assessments.
Related Paper :
The Differentiated Creative Search (DCS): Leveraging differentiated knowledge-acquisition and creative realism to address complex optimization problems. Available at https://doi.org/10.1016/j.eswa.2024.123734
Code Repository:
The MATLAB implementation of DCS is also available at https://github.com/minikku/Differentiated-Creative-Search.
Cite As :
Duankhan, P., Sunat, K., Chiewchanwattana, S., & Nasa-ngium, P. (2024). The Differentiated Creative Search (DCS): Leveraging Differentiated knowledge-acquisition and Creative realism to address complex optimization problems. Expert Systems with Applications, 123734. https://doi.org/10.1016/j.eswa.2024.123734

Cite As

Duankhan, P., Sunat, K., Chiewchanwattana, S., & Nasa-ngium, P. (2024). The Differentiated Creative Search (DCS): Leveraging differentiated knowledge-acquisition and creative realism to address complex optimization problems. Expert Systems with Applications, 252(123734), Article 123734. https://doi.org/10.1016/j.eswa.2024.123734

MATLAB Release Compatibility
Created with R2023a
Compatible with R2021a to R2023b
Platform Compatibility
Windows macOS Linux

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!
Version Published Release Notes
1.0.1

See release notes for this release on GitHub: https://github.com/minikku/Differentiated-Creative-Search/releases/tag/v1.0.1

1.0.0

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.