  In this paper, we address the problem of synthesizing optimal path plans in a
2D subject to spatio-temporal and thermal constraints. Our solution consists of
reducing the path planning problem to a Mixed Integer Linear Programming (MILP)
problem. The challenge is in encoding the implication constraints in the path
planning problem using only conjunctions that are permitted by the MILP
formulation. Our experimental analysis using an implementation of the encoding
in a Python toolbox demonstrates the feasibility of our approach in generating
the optimal plans.
