Combined resource allocation and route optimization in multiagent networks: A scalable approach

This paper presents an algorithm to solve the simultaneous resource allocation and route optimization problem first presented in [1]. This NP hard problem entails finding simultaneously the locations of resources (or service or communication exchanges) in a multi-agent network as well as determining multihop routes from individual agents to a common destination through a network of resource nodes in such a way that the total cost of communication from all agents to the destination center is minimized. The main contribution of this article is that it develops a solution approach that scales better than the existing algorithm in [1]. The number of design variables in the algorithm presented in [1] grows exponentially O(2^M) with the number of resources M; whereas in the algorithm proposed in this paper, the number of design variables are only of the order O(M). The proposed algorithm incorporates certain constraints that result from the law of optimality, which results in the reduction of the design parameter space. This algorithm, which is based on Maximum Entropy Principle (MEP), guarantees local minima and is heuristically designed to seek the global minimum.