Using genetic algorithms in effects-based planning
2013 (English)In: Proceedings of the 2013 IEEE International Conference on Systems, Man, and Cybernetics (SMC), IEEE Computer Society, 2013, 438-443 p.Conference paper (Refereed)
In this paper, we propose a genetic algorithm-based method for evaluation of operational plans within effects-based planning. We formulate the effects-based planning problem as a bi-objective optimization problem, in which the distance from the initial state to the current state (g) and the distance from the current state to the desired end state (h) are minimized. To solve the problem, we adopt Non-dominated Sorting Genetic Algorithm-II (NSGA-II). Considering an expeditionary operation scenario, we simulate a subset of possible plans and present the decision maker with a set of promising plans which are capable of approaching the desired end state efficiently. In order to discuss the efficiency and effectiveness of the algorithm, we compare the results of NSGA-II with the results of A*. The computational results show that NSGA-II is much more efficient than A* with regard to g. On the other hand A* is a little more effective with regard to h.
Place, publisher, year, edition, pages
IEEE Computer Society, 2013. 438-443 p.
, IEEE International Conference on Systems Man and Cybernetics Conference Proceedings, ISSN 1062-922X
Effects-based planning, Genetic algorithms, Optimization, Path planning, Search algorithms
IdentifiersURN: urn:nbn:se:kth:diva-139367DOI: 10.1109/SMC.2013.80ISI: 000332201900074ScopusID: 2-s2.0-84893539170ISBN: 978-1-4799-0652-9OAI: oai:DiVA.org:kth-139367DiVA: diva2:685992
The 2013 IEEE International Conference on Systems, Man, and Cybernetics, 13-16 Oct. 2013 Manchester, UK
QC 201401282014-01-102014-01-102014-04-24Bibliographically approved