PCIA: A Path Construction Imitation Algorithm for Global Optimization
This is an incremental improvement for optimization practitioners, offering a new algorithm for global optimization tasks.
The authors tackled global optimization by proposing PCIA, a new metaheuristic algorithm inspired by human path construction, and found it highly competitive against popular and latest algorithms on 53 mathematical and 13 constrained optimization problems.
In this paper, a new metaheuristic optimization algorithm, called Path Construction Imitation Algorithm (PCIA), is proposed. PCIA is inspired by how humans construct new paths and use them. Typically, humans prefer popular transportation routes. In the event of a path closure, a new route is built by mixing the existing paths intelligently. Also, humans select different pathways on a random basis to reach unknown destinations. PCIA generates a random population to find the best route toward the destination, similar to swarm-based algorithms. Each particle represents a path toward the destination. PCIA has been tested with 53 mathematical optimization problems and 13 constrained optimization problems. The results showed that the PCIA is highly competitive compared to both popular and the latest metaheuristic algorithms.