first, I’d like to thank you for the great software. I think AIMMS is great. About the problem. It's probably easy for the experts among you to solve. So far, I haven't found the right solution.
I am developing a model to analyze cost efficient pathways for the ramp-up of production plants for renewable fuels over several periods (t). I consider different plant generations (g), where a lant of a newer generation has "better" characteristics than the ones of the older generation.
The addition of plants into the system is defined by a free variable "PLANT_COMMISSIONING(t,g)". Based on this, the overall plant infrastructure is defined with various other variables and constraints.
I would now like to integrate the "behaviour" that a new plant generation can only be built if plants of the previous generation have been built beforehand (upscaling), e.g. if a minimum number of plants of the previous generation have been built beforehand. I am looking for an MIP approach for this.
I have already searched in various forums and tried out Big-M approaches, indicator constraint approaches and binary variable approaches. So far without success (maybe I simply implemented it wrong). I would be happy to provide more information about the model, but first I would need to know what information exactly would be helpful.
I would appreciate any helpful comments.
With best regards and many thanks in advance.