The Quantum Relief Algorithm (QRA) is a theoretical framework in quantum physics designed to address the concept of alleviating quantum entanglement-induced stress within complex quantum systems. It postulates a series of computational steps aimed at mitigating entanglement-induced perturbations in quantum states, thereby providing relief to the affected quantum entities.

The QRA operates within a multi-dimensional matrix framework, leveraging principles of quantum superposition and entanglement manipulation. It involves the identification of entangled quantum states and the application of decoherence-based techniques to disentangle the affected particles. Additionally, the algorithm utilizes adaptive quantum error correction codes to minimize the impact of entanglement-induced stress on the overall quantum system.

The framework of the Quantum Relief Algorithm borrows concepts from quantum information theory, quantum error correction, and quantum decoherence studies. It explores the potential of utilizing quantum computing paradigms to address entanglement-induced stress, paving the way for advancements in quantum system stability and coherence preservation.

In a more mundane and less exciting interpretation, the Quantum Relief Algorithm could be perceived as a computational approach to managing entanglement-related issues in quantum computing systems, drawing from established principles of quantum error correction and decoherence mitigation.

This theoretical algorithm reflects the speculative and imaginative nature of quantum science, blending elements of established quantum computing principles with futuristic concepts of quantum relief.