Thanks to the evolution of Python and its applications to solve linear programs and their variations supply chain and operations research analysts now have access to numerous packages and tools that support decision making. In this article I will use…
As a result of the emergence and progress of open-source languages SCM and OR analysts have access to a growing number of constantly improving tools and solvers. Julia, for example, is a flexible dynamic open-source programming language that is appropriate…
In previous posts, we have discussed using PuLP in python for the implementation of multi-objective linear optimization methods such as maximizing for one objective, then adding it as a constraint, and solving for the other objective (or applying a scalar…
I already introduced various coding examples implementing multi-objective optimization. In these examples I implemented different strategies for searching a multi-objective optimum. One of these strategies was based on scalarizing multiple objectives into a single objective function using weights for each…
In this post, I explain how supervised learning models in machine learning use single or multiple neurons in a single layer (shallow learning) or multiple neurons in multiple layers (deep learning) to generate a real, binary, or integer value beneficial…