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

Amber Srivastava, Srinivasa M. Salapaka

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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(2M) 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.

Original languageEnglish (US)
Title of host publication2017 American Control Conference, ACC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3956-3961
Number of pages6
ISBN (Electronic)9781509059928
DOIs
StatePublished - Jun 29 2017
Event2017 American Control Conference, ACC 2017 - Seattle, United States
Duration: May 24 2017May 26 2017

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619

Other

Other2017 American Control Conference, ACC 2017
CountryUnited States
CitySeattle
Period5/24/175/26/17

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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