Efficient allocation of multi-dimensional resources in blockchain networks remains challenging due to the self-interested behavior of participating nodes, which often undermines global fairness and stability. Traditional metaheuristics such as Simulated Annealing (SA) can explore large non-convex search spaces but overlook the competitive dynamics among agents. In contrast, game-theoretic formulations capture strategic decision-making yet become computationally prohibitive in large-scale decentralized systems. To reconcile these limitations, this work introduces the Adaptive Game-Theoretic Simulated Annealing (AGTSA) algorithm. AGTSA incorporates a Nash-response mechanism that guides the search process toward equilibrium-oriented states and employs an entropy-based cooling schedule that adaptively adjusts exploration according to allocation diversity. The unified framework jointly models fairness, stability, and computational efficiency, enabling a dynamic balance between global optimization and local rationality. Experimental validation on blockchain workloads shows that AGTSA improves Dominant Resource Fairness (DRF) by 12–15% and shortens convergence time by approximately 18% relative to classical SA and Particle Swarm Optimization (PSO). The results demonstrate that integrating strategic reasoning into heuristic search substantially enhances both fairness and performance, providing a scalable and equilibrium-consistent solution for decentralized resource management.
Research Article | Open Access | Download Full Text
Volume 4 | Issue 3 | Year 2025 | Article Id: DST-V4I3P102 DOI: https://doi.org/10.59232/DST-V4I3P102
Game-Theoretic Principles and Enhanced Simulated Annealing for Multi-Resource Allocation in Blockchain Networks
Hieu Huynh Thanh
| Received | Revised | Accepted | Published |
|---|---|---|---|
| 25 Jul 2025 | 26 Aug 2025 | 20 Sep 2025 | 30 Sep 2025 |
Citation
Hieu Huynh Thanh. “Game-Theoretic Principles and Enhanced Simulated Annealing for Multi-Resource Allocation in Blockchain Networks.” DS Journal of Digital Science and Technology, vol. 4, no. 3, pp. 1-22, 2025.
Abstract
Keywords
Blockchain resource allocation, Dominant Resource Fairness (DRF), Game theory, Nash equilibrium, Simulated Annealing (SA).
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