Coupling Optimization using Design Structure Matrices and Genetic Algorithm

TL;DR

This paper explores the integration of Design Structure Matrices and genetic algorithms to optimize system coupling, providing tools for systems architects to identify optimal architectures within Model-Based Systems Engineering.

Contribution

It introduces a novel approach combining DSM and genetic algorithms specifically for coupling minimization in complex systems modeling.

Findings

Demonstrates effectiveness of the combined approach in reducing system coupling.

Provides a framework for integrating optimization tools into MBSE environments.

Enhances design space exploration for system architecture optimization.

Abstract

This article seeks to contribute to a nuanced understanding of the integration of Design Structure Matrix (DSM) and genetic algorithms in the context of Complex Systems modelling described within Model-Based System Engineering approach. By examining coupling minimization as a critical aspect of advanced systems engineering practices, we aim to provide a scholarly exploration, blending theoretical insights with practical applications. The objective is to equip systems architects with analytical tools integrated within their Model Based Systems Engineering (MBSE) environment for exploring the design space of component interactions, facilitating the identification of optimal system architectures.