  Capability planning problems are pervasive throughout many areas of human
interest with prominent examples found in defense and security. Planning
provides a unique context for optimization that has not been explored in great
detail and involves a number of interesting challenges which are distinct from
traditional optimization research. Planning problems demand solutions that can
satisfy a number of competing objectives on multiple scales related to
robustness, adaptiveness, risk, etc. The scenario method is a key approach for
planning. Scenarios can be defined for long-term as well as short-term plans.
This paper introduces computational scenario-based planning problems and
proposes ways to accommodate strategic positioning within the tactical planning
domain. We demonstrate the methodology in a resource planning problem that is
solved with a multi-objective evolutionary algorithm. Our discussion and
results highlight the fact that scenario-based planning is naturally framed
within a multi-objective setting. However, the conflicting objectives occur on
different system levels rather than within a single system alone. This paper
also contends that planning problems are of vital interest in many human
endeavors and that Evolutionary Computation may be well positioned for this
problem domain.
