  In this paper we study a continuous time, optimal stochastic investment
problem under limited resources in a market with N firms. The investment
processes are subject to a time-dependent stochastic constraint. Rather than
using a dynamic programming approach, we exploit the concavity of the profit
functional to derive some necessary and sufficient first order conditions for
the corresponding Social Planner optimal policy. Our conditions are a
stochastic infinite-dimensional generalization of the Kuhn-Tucker Theorem. The
Lagrange multiplier takes the form of a nonnegative optional random measure on
[0,T] which is flat off the set of times for which the constraint is binding,
i.e. when all the fuel is spent. As a subproduct we obtain an enlightening
interpretation of the first order conditions for a single firm in Bank (2005).
In the infinite-horizon case, with operating profit functions of Cobb-Douglas
type, our method allows the explicit calculation of the optimal policy in terms
of the `base capacity' process, i.e. the unique solution of the Bank and El
Karoui representation problem (2004).
