PCIA: A Path Construction Imitation Algorithm for Global Optimization

TL;DR

This paper introduces PCIA, a novel metaheuristic algorithm inspired by human path construction behaviors, demonstrating high competitiveness on various optimization problems.

Contribution

The paper presents a new metaheuristic algorithm, PCIA, inspired by human route construction, with demonstrated effectiveness on multiple optimization problems.

Findings

PCIA outperforms several existing metaheuristic algorithms.

PCIA is effective on both mathematical and constrained optimization problems.

The algorithm shows high competitiveness across tested problems.

Abstract

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.