Title :
A Solution to a Species of Unlimited Equipment Support Problem by ACO
Author :
Deng Xiang-yang ; Gong Jian ; Zhou Jing-bo ; Peng Le ; Hou Huai-yi
Author_Institution :
Dept. of Electr. & Inf. Eng., Naval Aeronaut. & Astronaut. Univ., Yantai, China
Abstract :
This paper presents a new Ant Colony Optimization (ACO) algorithm to solve a species of unlimited equipment support problem (UESP). The equipment support has become more and more important in battlefields, and it involves a large number of executors and supported units. When comes a support mission, to assign an executor for each supported unit as soon as possible is the key step to solve the problem. By mapping the supported units to visited nodes, and attaching an executor for each node step by step, the UESP is modeled as a multistage decision making problem (MDMP), and it is proved to be a kind of NP-complete problem. The paper proposes the ACO-uesp to solve the problem. Its artificial ants traverse the nodes to construct a route as a solution, and after iteration, the pheromone trail increment is computed based on the assignment´s time cost. Finally, the experimental tests show that the modified algorithm for UESP is effective.
Keywords :
ant colony optimisation; artificial life; computational complexity; decision making; ACO algorithm; NP-complete problem; UESP; ant colony optimization; artificial ant; multistage decision making problem; pheromone trail increment; support mission; unlimited equipment support problem; Ant colony optimization; Dynamic scheduling; Manufacturing; Optimization; Stochastic processes; Traveling salesman problems; Vehicle dynamics; ACO-uesp; Equipment Support; Mission Assignment; Mission Scheduling optimization;
Conference_Titel :
Information Technology, Computer Engineering and Management Sciences (ICM), 2011 International Conference on
Conference_Location :
Nanjing, Jiangsu
Print_ISBN :
978-1-4577-1419-1
DOI :
10.1109/ICM.2011.311