After a career developing planning tools for my studies in communications network design, I have lots of lessons-learned to share. Off we go!
Trained as a mathematician, I developed an interest in prolog in grad school and have been both exploring and applying its capabilities my whole career spanning five decades -- mostly in network design but branching out over time. For personal use, I developed tennis blocktime and matchplay scheduling apps about 20 years ago. Probabilistic programming, reinforcement learning, defeasible reasoning, and general planning/scheduling applications are recent interests.
My personal research in optimization is centered around the theory and implementation of my St*Mesh planning tool, motivated by an algorithm I conceived in the mid 90's. Since then, variations of this approach have been successfully applied to optical mesh restoration design and optical connection planning. Over the years I have developed a general technique that combines constraint satisfaction with optimization that enables me to find near-optimal solutions for a broad variety of such applications. Some of these applications, solved with simpler algorithms, will be described here.