Resource allocation and scheduling in multi-agent systems present challenges due to complex interactions and decentralization. This survey paper provides a comprehensive analysis of distributed algorithms for addressing the distributed resource allocation (DRA) problem over multi-agent systems. It covers a significant area of research at the intersection of optimization, multi-agent systems, and distributed consensus-based computing. The paper begins by presenting a mathematical formulation of the DRA problem, establishing a solid foundation for further exploration. Real-world applications of DRA in various domains are examined to underscore the importance of efficient resource allocation, and relevant distributed optimization formulations are presented. The survey then delves into existing solutions for DRA, encompassing linear, nonlinear, primal-based, and dual-formulation-based approaches. Furthermore, this paper evaluates the features and properties of DRA algorithms, addressing key aspects such as feasibility, convergence rate, and network reliability. The analysis of mathematical foundations, diverse applications, existing solutions, and algorithmic properties contributes to a broader comprehension of the challenges and potential solutions for this domain.

翻译：多智能体系统中的资源分配与调度因复杂的交互和去中心化特性而面临挑战。本综述论文全面分析了面向多智能体系统分布式资源分配问题的各类分布式算法，涵盖优化、多智能体系统与分布式共识计算交叉领域的重要研究方向。论文首先建立分布式资源分配问题的数学表述，为后续探索奠定坚实基础；通过考察各领域的实际应用案例，阐明高效资源分配的重要性，并给出相关的分布式优化表述形式。随后综述现有解决方案，包括线性/非线性方法、基于原变量的方法及对偶公式化方法。此外，本文评估了分布式资源分配算法的特性与性能，重点分析可行性、收敛速率及网络可靠性等关键要素。对数学基础、多元应用、现有解决方案及算法特性的系统分析，有助于深入理解该领域的挑战与潜在解决路径。