Reactive tabu search in unmanned aerial reconnaissance simulations
Proceedings of the 30th conference on Winter simulation
An Ant Colony Optimization Algorithm for Multiple Travelling Salesman Problem
ICICIC '06 Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 1
Constrained Multi-objective Task Assignment for UUVs Using Multiple Ant Colonies System
CCCM '08 Proceedings of the 2008 ISECS International Colloquium on Computing, Communication, Control, and Management - Volume 01
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
Multi-objective optimization for dynamic task allocation in a multi-robot system
Engineering Applications of Artificial Intelligence
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This paper presents a dynamic task allocation algorithm for multiple robots to visit multiple targets. This algorithm is specifically designed for the environment where robots have dissimilar starting and ending locations. And the constraint of balancing the number of targets visited by each robot is considered. More importantly, this paper takes into account the dynamicity of multi-robot system and the obstacles in the environment. This problem is modeled as a constrained MTSP which can not be transformed to TSP and can not be solved by classical Ant Colony System (ACS). The Modified Ant Colony System (MACS) is presented to solve this problem and the unvisited targets are allocated to appropriate robots dynamically. The simulation results show that the output of the proposed algorithm can satisfy the constraints and dynamicity for the problem of multi-robot task allocation.