Title: Adaptive Wave Function Collapse for Optimization Problems

Jincheng Zhang

Published Sep 7, 2026• 0 citations

Abstract

This paper presents an innovative approach to optimization problems, leveraging Adaptive Wave Function Collapse (AWFC) to significantly improve the efficiency of finding optimal solutions. Traditional optimization methods often struggle with complex landscapes, requiring exhaustive search. AWFC dynamically collapses the wave function of potential solutions, enabling the exploration of multiple solution spaces simultaneously and drastically reducing the computational burden. We introduce a novel algorithm incorporating quantum-inspired principles, allowing for a more targeted and efficient search process. The paper details the implementation of the AWFC algorithm, its performance analysis, and its potential applications across diverse optimization scenarios. Specifically, we demonstrate its effectiveness in a range of problems, including the Traveling Salesman Problem and the Quadratic Assignment Problem, showcasing a substantial improvement in solution time compared to conventional methods.

DOI: 10.5281/zenodo.22637519

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