CPLEX Learning Introduction
Traditionally businesses will focus on efficiency to differentiate themselves from competitors. This includes waste reduction, faster throughput time and better customer service. While efficiency is still important in today’s environment, it is no longer sufficient for differentiation.
Today’s buzzwords include Big Data and Analytics. Actions include installing huge IT infrastructure for data collection and storage, acquiring skills in processing structured and unstructured data and in advanced statistical software like SAS or R and implementing data visualization. Provided that data is available and usable, companies will have personnel and tools for reporting and prediction.
Today, businesses have to focus on efficiency, including waste reduction, faster throughput time and better customer service, to differentiate ourselves from competitors. We have huge IT infrastructure for data collection and storage, better skills in processing data with advanced statistical software and friendlier data visualization dashboard. However, we still has to make decisions based on gut feel.
Prescriptive analytics recommends one or more courses of action and showing the likely outcome of each decision so that the business decision-maker can take this information and act. There is no actionable recommendation provided by the systems and reports or what-if analyses to quantify what will happen if different course of actions are taken.
There are 3 types of analytics: descriptive (what has happened), predictive (what will happen), and prescriptive (what should happen). This training is about the third level analytics, prescriptive, which sits at the top of analytics evolution diagram above. It uses advanced analytical methods from Operations Research (OR) / Management Science (MS) / Decision Science for quantitative decision making to help make better decisions. No more gut feel or crystal ball in decision making.
OR/MS is not new as it started during World War II. Optimization problems need to be formulated as mathematical models and solved with the optimization engine to get the solutions/recommendations. Today’s computing capability has enabled very large and complex practical problems to be solved very quickly. Unfortunately OR/MS applications are not widespread in Malaysia compared to USA, Europe, South Korea, Taiwan, and Singapore.
IBM ILOG CPLEX Optimization Studio provides powerful advanced analytics to transform descriptive data and predictive solutions into optimized prescriptive courses of action – replacing intuition and heuristic thinking with fact-based decisions. The users are the operational research experts, academia, OEMs, modeling experts and business decision makers with the helps of internal IBM partners (GSB, Products, … etc.). They use Optimization Programming Language (OPL), which is specifically designed to express optimization models.
ILOG CPLEX OPL is a very niche skill but highly valued by the critical industry, like Oil and Gas, Supply Chain and Manufacturing. We have many training requests from individual operational scientists and planners, to improve their skills and increase their salaries. Here, we would like to compile all the CPLEX learning resources, free or paid:
IBM Official
Online Course
- CognativeClass.ai: Mathematical Optimization for Business Problems
- OptimiserSchool
Corporate Trainings
Video
- IBM Decision Optimization Dev Videos
- CPLEX Seminar – Getting started with CPLEX Studio (part 1) Video by Hernán Cáceres
- Linear Programming IBM CPLEX Video by Corey Messer
- ORLessons
- More…
Q&A
Reference
PS: Under development, please suggest your materials to learn CPLEX. Thanks.