An evolutionary approach to capacitated resource distribution by a multiple-agent team

Authors:
Mudassar Hussain;Bahram Kimiaghalam;Abdollah Homaifar;Albert Esterline;Bijan Sayyarodsari
Affiliations:
NASA Autonomous Control and Information Technology Center, Department of Electrical Engineering, North Carolina A&T State University, Greensboro, NC;NASA Autonomous Control and Information Technology Center, Department of Electrical Engineering, North Carolina A&T State University, Greensboro, NC;NASA Autonomous Control and Information Technology Center, Department of Electrical Engineering, North Carolina A&T State University, Greensboro, NC;NASA Autonomous Control and Information Technology Center, Department of Electrical Engineering, North Carolina A&T State University, Greensboro, NC;Pavilion Technologies, Austin, TX
Venue:
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Year:
2003

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Abstract

A hybrid implementation of an evolutionary metahueristic scheme with local optimization has been applied to a constrained problem of routing and scheduling a team of robotic agents to perform a resource distribution task in a possibly dynamic environment. In this paper a central planner is responsible for planning routes and schedules for the entire team of cooperating robots. The potential computational complexity of such a centralized solution is addressed by an innovative genetic approach that transforms the task of multiple route design into a special manifestation of the traveling salesperson problem. The key advantage of this approach is that globally optimal or near optimal solutions can be produced in a timeframe amenable for real-time implementation. The algorithm was tested on a set of standard problems with encouraging results.