This paper shows how agent-based stochastic approaches can provide a complementary and more flexible approach to study investment incentives and price dynamics in a real options framework. We particularly study the case of two-stage production chains in which one sector produces an intermediate product and the other the final product, and the intermediate product is traded on the spot market. An agent-based competitive model using a genetic algorithm allows us to explicitly model the behaviors and interactions of the firms competing in each subsector and trading the intermediate product with each other on a spot market, and optimal investment strategies can be identified.