Genetic Algorithm for Truss Optimization Problem
This method uses a Genetic Algorithm to solve the Truss problem via the GA optimization tool.
- Fix (Multiload Handling): Fixed an indexing error in ga_fitness_function.m where flattening the stress matrix caused out-of-bound errors during multiple load cases. The function now iterates explicitly over load cases and members.
- Fix (Variable Mapping): Corrected the mapping of the Compression Limit (Sigmac) vector. It now correctly uses the Group ID (GR) to assign specific stress limits to members, rather than defaulting to the first element.
- Improvement (Output Consistency): Updated run_ga_multiple.m to calculate statistics (Mean/StdDev) based on the Penalized Weight for all runs (feasible and infeasible). This ensures the ga_history_results.csv data matches the summary in FeasibilityPerformance.txt exactly.
- Fix (CSV Formatting): Implemented unique(..., 'last') for the evaluation axis generation. This removes duplicate rows at the budget limit (e.g., iteration 40) while preserving the final and best converged value.
引用格式
ibrahim aydogdu (2026). Genetic Algorithm for Truss Optimization Problem (https://ww2.mathworks.cn/matlabcentral/fileexchange/182262-genetic-algorithm-for-truss-optimization-problem), MATLAB Central File Exchange. 检索时间: .
