Merken
How to improve your diet and save money with Python
Metadaten
Formale Metadaten
Titel  How to improve your diet and save money with Python 
Serientitel  EuroPython 2016 
Teil  35 
Anzahl der Teile  169 
Autor 
Bauer, Zuria

Lizenz 
CCNamensnennung  keine kommerzielle Nutzung  Weitergabe unter gleichen Bedingungen 3.0 Unported: Sie dürfen das Werk bzw. den Inhalt zu jedem legalen und nichtkommerziellen Zweck nutzen, verändern und in unveränderter oder veränderter Form vervielfältigen, verbreiten und öffentlich zugänglich machen, sofern Sie den Namen des Autors/Rechteinhabers in der von ihm festgelegten Weise nennen und das Werk bzw. diesen Inhalt auch in veränderter Form nur unter den Bedingungen dieser Lizenz weitergeben 
DOI  10.5446/21245 
Herausgeber  EuroPython 
Erscheinungsjahr  2016 
Sprache  Englisch 
Produktionsort  Bilbao, Euskadi, Spain 
Inhaltliche Metadaten
Fachgebiet  Informatik 
Abstract  Zuria Bauer/Daniel Domene López  How to improve your diet and save money with Python Optimization in Python (also known as mathematical programming) can be performed by minimization (or maximization) of an objective function within a model that can include discrete variables subject to a set of constrains. At this talk, chemical engineering students of the University of Alicante will introduce the audience to the possibilities of optimization, presenting Pyomo and showing real world examples such as how to improve your diet and save money at fast food restaurants.  Process optimization in industry has become essential in order to maximize the resources available and reduce energy consumption. Optimization problems become interesting when dealing with restrictions (linear or nonlinear) and integer variables (modeling the discrete decisions). Python ecosystem presents different libraries to solve optimization problems, some of them are CVXOpt, CVXPy, PulP, OpenOpt, or Pyomo. Among them, Pyomo results interesting because:  It can be used for Mathematical modeling in Python similarly to AMPL (and GAMS)  It communicates with the main solvers used in this field such as GLPK, Gurobi, CPLEX, CBC and PICO  It's free and open source Python library (BSD license), being developed by Sandia National Laboratories, USA.  It supports Python 3 and it is easy to install. The talk will be divided in three parts: 1. Introduction to Mathematical Programming/Optimization (15 min): visual introduction to optimization concepts including restrictions and non linearties (linear Programming, Nonlinear Programming, ILP, MIP, MINLP). 2. Introduction to the Pyomo sintax and a quick note for the installation (20 min): showing how to improve their diet and save money when ordering food in fast food restaurants. 3. Optimization problems in engineering (10 min): showing more advanced optimization examples that include decision variables. 
Schlagwörter 
EuroPython 2016 EP 2016 EuroPython Conference 