I am somewhat new to programming, and what I know about Sympy, Numpy, Scipy 
and GEKKO have been mostly self-taught within the last six-seven weeks, so 
I apologize if this inquiry seem elementary.

I am writing my master's thesis within industrial economics, and am 
currently analyzing a Hotelling model. The model I am analyzing consists of 
two stages: first stage, firms establishes themselves along a Hotelling 
line (an unit interval), and on the second stage these firms compete in 
prices (the second stage will always be simultaneous). The goal is to have 
this model work for n-number of firms. I have found Sympy extremely useful 
in finding explicit expressions for prices wrt. locations. These prices are 
inserted into their respective profit functions. From here on out, I am 
dependent on solving the model numerically to arrive at equilibrium 
locations.

Since lambdifying these expressions and defining callable functions for 
them are straight-forward, solving the first stage simultaneous is not 
problematic using Scipy's minimize (or fsolve on the FOCs). But I am also 
analyzing what happens when the firms establishes one-by-one. Making this 
stage dynamic is quite another world of hurt for me, and so far I have only 
eyed hope the GEKKO-package could be my savior. Unfortunately this package 
is not compatible with Sympy expressions or the same methods that work with 
Scipy (See another inquiry I made regarding this on the APMonitor Google 
Group <https://groups.google.com/forum/#!topic/apmonitor/3dPmJu-T4AM> ).

This is where I hope this community can assist me: Either by suggesting an 
alternate way of dynamically optimize my first stage for n-number of firms 
where I may use my expressions, or, I assume more realistically, some way 
of converting my Sympy-expressions into expressions that can be used in 
GEKKO.

Kind regards,
Martin Festøy

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