Deadline Date: 31 May 2026
Optimization of composite structures has become a cornerstone of modern engineering design, offering significant potential for enhancing structural performance, minimizing weight, and improving cost-effectiveness across a wide range of industrial applications — from aerospace and automotive engineering to civil and marine structures. By leveraging optimization methodologies, engineers can systematically determine the optimal combination of materials, fiber orientations, stacking sequences, and geometrical configurations to meet specific mechanical, thermal, and durability requirements under diverse loading and environmental conditions.
Contemporary optimization approaches such as gradient-based methods, genetic algorithms, topology optimization, and multi-objective metaheuristics have expanded the design space exploration beyond traditional trial-and-error methods. These computational techniques enable designers to efficiently handle complex, nonlinear, and multi-constraint problems inherent to composite materials, leading to innovative, lightweight, and structurally efficient solutions. Moreover, the integration of artificial intelligence (AI) and machine learning (ML) is revolutionizing predictive modeling, surrogate-based optimization, and design automation for composite structures.
The aim of this special issue is to gather cutting-edge research and novel methodologies that advance the optimization, design, and analysis of composite materials and structures. It seeks to provide a comprehensive platform for showcasing recent progress in algorithmic development, computational modeling, and experimental validation that drive innovation in high-performance and sustainable composite systems.
This special issue welcomes original research articles, review papers, and case studies addressing (but not limited to) the following areas:
Advanced optimization methods for the design and analysis of composite structures
AI- and machine learning–based frameworks for simulation and optimization of composite responses
Topology and shape optimization of composite components for weight and stiffness efficiency
Genetic algorithms, metaheuristics, and multi-objective optimization in composite material design
Multi-scale and multi-physics modeling approaches integrated with optimization strategies
Surrogate modeling and response surface methods for design space exploration
Reliability-based and robust design optimization of composite systems
Experimental validation and data-driven optimization frameworks
By bridging the gap between theoretical developments and practical applications, this special issue aims to advance the understanding and implementation of optimization-driven design in composite engineering. It aspires to serve as a valuable reference for researchers, practitioners, and industry professionals seeking to develop next-generation composite structures that are lighter, stronger, and more sustainable through intelligent optimization methodologies.