Revolutionizing multi-objective interval traveling salesperson problem: A novel approach with interval arithmetic

Abstract

A groundbreaking study employs interval arithmetic to address the challenging multi-objective interval traveling salesperson problem. Customizing methods like a nearest neighbor, branch and bound, two-way heuristics, and dynamic programming effectively resolve this complex problem. Preserving interval values without the need for classical form conversion is a significant advantage. Researchers validated this approach through extensive experiments, consistently demonstrating superior outcomes compared to existing methods. These algorithmic approaches were optimized for Python 3.11 64-bit to enhance processing speed and efficiency.