Cursos

Modelado de problemas típicos en su industria

Progrmación Entera Mixta (MLP) o Constranint Programing (COP)

Uso del lenguaje OPL o APIs programadas en (C. C++, Java, Python)

Técnicas avanzadas (generación de columnas, descomposición de Bender)

Manos a la Obra (entrenamiento usando los problemas que quiera resolver)

Gitbhub

Bienvenido a IBM® Decision Optimization Modeling con OPL y CPLEX en IBM® Decision Optimization on Cloud (DOcplexcloud)

Esta biblioteca contiene varios ejemplos de modelos con diferentes tipos de archivos. Breves descripciones de estos modelos se proporcionan más adelante en este archivo.

 

IBM Decision Optimization on Cloud (DOcplexcloud) enables you to solve optimization problems on the cloud without installing or configuring a solver. We handle the connection so that you can jump into coding faster.

This documentation describes the R API to access the service.

Welcome to IBM® Decision Optimization Modeling with OPL and CP Optimizer on DOcplexcloud.

This library contains various model examples with different file types. For each sample you can find here.

Welcome to the IBM® OPL connector for Python. Licensed under the Apache License v2.0.

With this library, you can quickly and easily add the power of optimization to your Python application. You can model your problems by using the OPL language and IDE, and integrate it in Python via Python/pandas/sql alchemy inputs/outputs.

IBM Decision Optimization on Cloud (DOcplexcloud) allows you to solve optimization problems on the cloud without installing or configuring a solver. We handle the connection so that you can jump into coding faster.

This documentation describes the IBM DOcplexcloud Python Client samples.

This sample shows how you can leverage the power of the DOcplexcloud service directly from your Microsoft Excel workbook.

This DO for DSX example introduces basic concepts of model builder and dashboard using a python CPLEX model.

It solves a simple Marketing Campaigns optimization example.

This DO for DSX example shows how to use optimization optimization position of SKUs on shelfs according to demand, availability and constraints. This example is migrated from an olde Decision Optimization Center demo.

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