The objective of this paper is to demonstrate that optimal greenhouse design must account for (and be combined to) optimal climate management. We prove this by showing that different strategies and set-points to control the greenhouse ventilators result in different ¿optimal sets¿ of design parameters. We determined these optimal sets for a passive greenhouse in Almería, Spain where tomatoes were grown. The greenhouse design parameters investigated in this research were: 1) the transmission of the cover for photosynthetically active radiation (PAR), 2) the transmission of near infrared (NIR) radiation and 3) the emission coefficient for longwave radiation of the cover. Six optimal sets of design parameters were determined by maximising the marginal revenues (crop yield minus costs of design parameters), under given climate conditions, and for different ventilation control strategies. Each ventilation control strategy had different set-points for the air temperature and carbon dioxide concen¬tration to control the greenhouse ventilators. To solve this optimization problem we used a dynamic crop-greenhouse model and an optimization algorithm. The model described the combined influence of the relevant design parameters, outdoor climate and ventilation control upon economic crop yield, through their effect on indoor climate. The yearly costs of the design parameters were empirically derived from prices, physical properties and lifespan of a number of greenhouse cover materials. Results showed that indeed for different strategies and set-points to control the green¬house ventilators different ¿optimal sets¿ of design parameters and marginal revenues were obtained. For example, the difference between the highest optimal NIR trans¬mission 1.00 and the lowest optimal NIR transmission 0.40 was 60%, while the highest marginal revenues 16.94 ¿m-2 differed 18,7% with the lowest marginal revenues of 13.77 ¿ m-2. Additionally, it was found that the cover design parameters were time dependent. In conclusion, only a combined optimal control and design approach that takes into account the best climate control strategy and the time dependency of the design parameters will ensure optimal design parameters and maximum marginal revenues.