Ant Colony Optimization Modelling for Task Allocation in Multi-Agent
System for Multi-Target

Ant Colony Optimization Modelling for Task Allocation in Multi-Agent
System for Multi-Target

task allocation, multi-agent system, multiple tasks, ACO

Task allocation in multi-agent system can be defined as a problem of allocating a number of agents to the task. One of the
problems in task allocation is to optimize the allocation of heterogeneous agents when there are multiple tasks which require
several capabilities. To solve that problem, this research aims to modify the Ant Colony Optimization (ACO) algorithm so that
the algorithm can be employed for solving task allocation problems with multiple tasks. In this research, we optimize the
performance of the algorithm by minimizing the task completion cost as well as the number of overlapping agents. We also
maximize the overall system capabilities in order to increase efficiency. Simulation results show that the modified ACO
algorithm has significantly decreased overall task completion cost as well as the overlapping agents factor compared to the
benchmark algorithm.

Iis Rodiah1
, Medria Kusuma Dewi Hardhienata2
, Agus Buono3
, Karlisa Priandana4

Iis Rodiah1
, Medria Kusuma Dewi Hardhienata2
, Agus Buono3
, Karlisa Priandana4

27-12-2022

Fajar bagus W

PDF

Indonesia

Text