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

(Please refe to this link for abstract of each talks)

Workshop on "Progressive Hedging Algorithms in Stochastic Optimization"

 Speakers           :        Prof Sun Jie (jsun@nus.edu.sg)

                                   Dr Min Zhang (min.zhang2@curtin.edu.au)

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 challenges in operations research and business analytics is to find a good approach to dealing with multi-stage stochastic optimization problems. 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 the progressive hedging algorithm, one of the long-standing methods for solving such optimization problems under convexity, to be used to solve multistage stochastic variational inequality problems under monotonicity. A code has been developed for stochastic linear variational inequality in a two-stage formulation.

 The first day of the workshop starts with a morning lecture on an introduction to stochastic optimization, stochastic variational inequality and the progressive hedging algorithm. In the afternoon, a MATLAB template will be demonstrated, followed by a group discussion of 1-2 hours. In the group discussion, the participants are expected to organize themselves into small groups of 4-6 people each on voluntary basis. The group discussion may begin with some group members’ research problems that involve stochastic optimization (come to the workshop with a problem!). They then study how to formulate these problems as two-stage stochastic programs and try to solve these problems by the MATLAB code placed in a dropbox. It is hoped that everyone in this class will have a hands-on experience on modelling stochastic optimization problems and solving them by the progressive hedging algorithm.

Prerequisites

 TThis workshop targets at PHD students and researchers in management and engineering, who have been working on various decision models under uncertainty and may need an effective way to solve convex stochastic optimization problems. A MATLAB programming capability is a plus. We encourage the participants to bring their own laptops with MATLAB.

Day 2

Series of Talks (Please refe to this link for abstract of each 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: Theory and Applications of Distributionally Robust Optimization.)

Speaker: Professor Melvyn Sim (NUS Business School)

Session 2- 9.40am to 10.20am  (Talk Title: Logistics and Supply Chain Analytics in China)

Speaker: Professor Yugang Yu (School of Management, USTC)

AM Tea-Break  - (10.20am to 10.40pm)

Session 3 – 10.40am to 11.20am (Talk Title: Making Lemonade from Lemons: Taxi Drivers’ Response to Cancellations and No-Shows)

Speaker: Professor Junhong Chu (NUS Business School)

Session 4 – 11:20am to 12pm (Talk Title: Some New Perspectives from High-tech and Fashion Industry in China:Ronds – A Pioneer in a Blue Ocean; and Goldfarm – Supply Chain Driven Fashion)

Speaker: Professor Bin Ding (School of Management, USTC) / Professor Liu Qizhang (NUS Business School)

Lunch  -  (12pm to 1.30pm)

Session 5 – 1.30pm to 2.10pm (Talk Title: Information Provision and Streamlined Medical Service: Evidence from a Mobile Appointment App )

Speaker: Professor Nan Yang (NUS Business School)

Session 6 – 2.10pm to 2.50pm (Talk Title: Optimal Stopping for Medical Treatment with Forecast Information )

Speaker: Professor Zhichao Zheng (Singapore Management University)

Session 7 – 2.50pm to 3.30pm (Talk Title: The Value of Buy-Online-and-Pickup-in-Store in Omni-Channel: Evidence from Customer Usage Data)

Speaker: Professor Hefen Liu  (School of Management, USTC)

PM Tea-Break  -  (3.30pm to 3.50pm)

Session 8 – 3.50pm to 4.30pm (Talk Title: Content Monetization and Preview Design)

Speaker: Professor Dai Yao (NUS Business School)

Last Session – 4.30pm to 5.10pm (Talk Title: Nonlinear Effects of Social Engagement on the Relation between Content Promotions and User’s Purchase Responses )

Speaker: Professor Yongjun Li (School of Management, USTC)

Q & A Session – 5.10pm to 5.30pm