TY - GEN
T1 - Multi-agent path planning problem under a multi-objective optimization framework
AU - Nielsen, Izabela
AU - Bocewicz, Grzegorz
AU - Saha, Subrata
N1 - Publisher Copyright:
© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2021
Y1 - 2021
N2 - In this study, a mixed-integer programming formulation is developed for a team of homogeneous sensing agents under a bi-objective optimization framework to solve a discrete open-loop centralized multi-agent search and rescue path planning problem. The first objective represents the maximization of probability of target detection to ensure the success of mission planning and the second objective represents minimization of the cumulative path length of all the agents to ensure resource utilization and ensure adequate area coverage. A two-phase fuzzy programming technique is used to find the Pareto optimal solution. Numerical experiments are conducted with CPLEX to evaluate the effectiveness of the solution procedure with varying number of agents, and the impact of the size of a grid-based rectangular map with a sparsely distributed non-cooperative finite number of stationary targets.
AB - In this study, a mixed-integer programming formulation is developed for a team of homogeneous sensing agents under a bi-objective optimization framework to solve a discrete open-loop centralized multi-agent search and rescue path planning problem. The first objective represents the maximization of probability of target detection to ensure the success of mission planning and the second objective represents minimization of the cumulative path length of all the agents to ensure resource utilization and ensure adequate area coverage. A two-phase fuzzy programming technique is used to find the Pareto optimal solution. Numerical experiments are conducted with CPLEX to evaluate the effectiveness of the solution procedure with varying number of agents, and the impact of the size of a grid-based rectangular map with a sparsely distributed non-cooperative finite number of stationary targets.
KW - Mixed-integer programming
KW - Multi-agent path planning
KW - Search and rescue
UR - http://www.scopus.com/inward/record.url?scp=85089613421&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-53829-3_1
DO - 10.1007/978-3-030-53829-3_1
M3 - Article in proceeding
AN - SCOPUS:85089613421
SN - 978-3-030-53828-6
T3 - Advances in Intelligent Systems and Computing
SP - 5
EP - 14
BT - Distributed Computing and Artificial Intelligence, Special Sessions, 17th International Conference, DCAI 2020
A2 - Rodríguez González, Sara
A2 - Prieto, Javier
A2 - González-Briones, Alfonso
A2 - Gola, Arkadiusz
A2 - Katranas, George
A2 - Ricca, Michela
A2 - Loukanova, Roussanka
A2 - Loukanova, Roussanka
PB - Springer VS
T2 - 17th International Symposium on Distributed Computing and Artificial Intelligence, DCAI 2020
Y2 - 17 June 2020 through 19 June 2020
ER -