Data Driven Prescriptive Analytics Workshop

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Innovation 4.0

3 Research Link


Singapore, 117602


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Event description


In a world where flood of data available to businesses regarding their operations these days. The need capabilities to analyze historical data, doing it right and becoming a data driven organization.

Many large organizations, especially those in traditional industry sectors such as telecommunications, financial services and manufacturing from Singapore or china companies and governments, are beginning to realize the importance of design thinking combined with big data for true customer centricity. By embedding design thinking into big data use cases, organizations can unlock new opportunities, build empathy for users and pave the way to experiences that are truly human-centered and create an emotional connection.

In this new paradigm shift across businesses, success lies in simplifying complex and using statistical methods, deterministic and stochastic optimization methods to solve them. These logics will help to utilize business data more effectively by deriving insights of trends and irregularities from data and applying them for forward-looking predictions which will help improve the user experience, business intelligence and analytics environment of their organizations. This is realized through building predictive models with appropriate analytical and design thinking techniques.

Day 1

Workshop on "Progressive Hedging Algorithms in Stochastic Optimization"

Lecturer : Prof Sun Jie (

Dr Min Zhang (

Time : Fri Sep 28, (Registration - 8.30am to 9am)

Morning Session 9am-11.30am

(Tea Break 10.10am-10.30am)

Lunch 11.45am-1.15pm

Afternoon Session: 1.30pm-4pm

(Tea break 2.40pm-3pm)

Place : Innovation 4.0, NUS, Level 1, Seminar Room (I4-01-03)

Workshop Objective

One of the central challenge in OR and Analytics is to find a good approach to deal with multi-stage stochastic optimization problem. The concept of a stochastic variational inequality has recently been articulated in a new way that is able to cover, in particular, the optimality conditions for multistage stochastic programming problems. This allows Progressive Hedging algorithm, one of the long-standing methods for solving such an optimization problem under convexity, to be used to solve multistage stochastic variational inequality problems under monotonicity constraints, with a code developed for stochastic complementarity problems in a linear two-stage formulation.

The workshop starts the participants presenting on their models in multistage stochastic optimization (come with a problem!). We then study how to convert the models into a stochastic variational inequality or a stochastic linear complementarity problem (SLCP). The basic progressive hedging algorithm (PHA) is then introduced. A MATLAB code of PHA for SLCP is demonstrated. The workshop will end with a discussion on how to design a PHA for the specific model of the participants.


This workshop targets at PHD students and researchers in management and engineering, who have been working on various operations research models under uncertainty and may need an effective way to solve convex stochastic optimization problems. Programming capability in MATLAB is a plus.

Day 2

Series of Talks

Lecturer : By different Professors from NUS and USTC

Time : Sat Sep 29, 9am to 5.10pm

Place : Innovation 4.0, NUS, Level 1, Seminar Room (I4-01-03)

Registration – 8.30am to 9am

Session 1 – 9am to 9.40am (Talk Title: TBC)

Session 2- 9.40am to 10.20am (Talk Title: TBC)

AM Tea-Break (10.20am to 10.40pm)

Session 3 – 10.40am to 11.20am (Talk Title: TBC)

Session 4 – 11:20am to 12pm (Talk Title: TBC)

Lunch (12pm to 1.30pm)

Session 5 – 1.30pm to 2.10pm (Talk Title: TBC)

Session 6 – 2.10pm to 2.50pm (Talk Title: TBC)

Session 7 – 2.50pm to 3.30pm (Talk Title: TBC)

PM Tea-Break (3.30pm to 3.50pm)

Session 8 – 3.50pm to 4.30pm (Talk Title: TBC)

Last Session – 4.30pm to 5.10pm (Talk Title: TBC)

Q & A Session – 5.10pm to 5.30pm

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Innovation 4.0

3 Research Link


Singapore, 117602


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