CGO and SNS Optimization Algorithm for the Structures with Discontinuous and Continuous Variables

Area of Science:

• Structural Engineering
• Optimization Algorithms
• Computational Mechanics

Background:

• Planar truss structures require efficient size reduction methods.
• Minimizing structural weight while adhering to stress and displacement constraints is crucial.

Purpose of the Study:

• To investigate discontinuous and continuous optimization approaches for planar truss structures.
• To compare the effectiveness of Chaos Game Optimization (CGO) and Social Network Search (SNS) algorithms.

Main Methods:

• Member section area was treated as the decision variable.
• Weight minimization served as the objective function.
• Stress and displacement limits acted as constraints.

Main Results:

• Social Network Search (SNS) yielded the most cost-effective results for discontinuous-size optimization.
• Chaos Game Optimization (CGO) provided the most cost-effective solutions for continuous-size optimization.

Conclusions:

• Both CGO and SNS are effective optimization algorithms for planar truss structures.
• The choice between CGO and SNS depends on whether the size optimization is discontinuous or continuous.