mixedinteger

Convert ideas into mathematical expressions to solve operations research problemsPhoto by Aaron Lefler on UnsplashNumerical optimization is at the core of quantitative techniques in decision science. It encompasses a set of frameworks to optimize one or more objectives under some prescribed set of circumstances.Two major categories of optimization problems are Linear and Nonlinear Programming. These categories are distinguished by how the mathematical relationships between the decision variables are established in the…

Mathematical modeling and Python implementation of the classical sequencing problem using PyomoPhoto by Guillaume Bolduc on UnsplashThe job-shop scheduling problem (JSSP) is a widely studied optimization problem with several industrial applications. The goal is to define how to minimize the makespan required to allocate shared resources (machines) over time to complete competing activities (jobs). As for other optimization problems, mixed-integer programming can be an effective tool to provide good solutions, although for…

The classical inventory management optimization problem solved in Python using PyomoPhoto by CHUTTERSNAP on UnsplashLot sizing problems are production planning problems with setups between production lots. By reason of these setups, it is often too costly to produce a given product in every period (Suwondo & Yuliando, 2012). In contrast, fewer setups are associated with higher holding inventory costs. Therefore, to obtain optimal costs, one should balance these operational aspects.Throughout this article, the problem…

This side project creates an experiment that generates simulated data, creates mixed integer solutions, and trains a reinforcement learning network to approximate optimal allocationshttps://upload.wikimedia.org/wikipedia/commons/d/de/Distribution_centre_%28J_Sainsbury%27s%29.jpgNote: This project is not affiliated with any organization in terms of source code or data. This is a personal project that I developed from scratch.This post summarizes some business outcomes and goals that are considered while building mixed…

Learn how to solve optimization problems in Python using scipy and pyomoPhoto by Denisse Leon on UnsplashThe knapsack problem is probably one of the first problems one faces when studying integer programming, optimization, or operations research. In this problem, from a given set of items, one must choose the most valuable combination to fit in a knapsack of a certain capacity (weight, volume, or both).Throughout this article, we will implement the knapsack problem in a relaxed form using scipy and in an integer form…