Land combat scenario planning: a multiobjective approach

Authors:
Ang Yang;Hussein A. Abbass;Ruhul Sarker
Affiliations:
Defence and Security Applications Research Centre (DSA), University of New South Wales, Australian Defence Force Academy, Canberra, ACT, Australia;Defence and Security Applications Research Centre (DSA), University of New South Wales, Australian Defence Force Academy, Canberra, ACT, Australia;Defence and Security Applications Research Centre (DSA), University of New South Wales, Australian Defence Force Academy, Canberra, ACT, Australia
Venue:
SEAL'06 Proceedings of the 6th international conference on Simulated Evolution And Learning
Year:
2006

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Abstract

The simulation of land combat operations is a complex task. The space of possibilities is exponential and the performance criteria are usually in conflict; thus finding a sweet spot in this complex search space is a hard task. This paper focuses on the effect of population size and mutation rate on the performance of NSGA–II, as the evolutionary multiobjective optimization technique, to decide on the composition of forces using a complex land combat multi-agent scenario planning tool.