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Igniting the power of data analytics

Discover how Professor Juan Serpa and the 16 Desautels students comprising a new food analytics club are revolutionizing the operations of beloved NPO Santropol Roulant – and it’s all through the power of data analytics.

Read more in the McGill Reporter

Published: 12 Apr 2019

Low-complexity method for hybrid MPC with local optimality guarantees

Authors: Damian Frick, Angelos Georghiou, Juan L. Jerez, Alexander Domahidi, and Manfred Morari

Publication: SIAM Journal on Control and Optimization, Forthcoming

Abstract: 

Published: 10 Apr 2019

A Primal-Dual Lifting Scheme for Two-Stage Robust Optimization

Authors: Angelos Georghiou, Angelos Tsoukalas, Wolfram Wiesemann

Publication: Operations Research, Forthcoming

Abstract: 

Two-stage robust optimization problems, in which decisions are taken both in anticipation of and in response to the observation of an unknown parameter vector from within an uncertainty set, are notoriously challenging. In this paper, we develop convergent hierarchies of primal (conservative) and dual (progressive) bounds for these problems that trade off the competing goals of tractability and optimality: While the coarsest bounds recover a tractable but suboptimal affine decision rule approximation of the two-stage robust optimization problem, the refined bounds lift extreme points of the uncertainty set until an exact but intractable extreme point reformulation of the problem is obtained. Based on these bounds, we propose a primal-dual lifting scheme for the solution of two-stage robust optimization problems that accommodates for generic polyhedral uncertainty sets, infeasible problem instances as well as the absence of a relatively complete recourse. The incumbent solutions in each step of our algorithm afford rigorous error bounds, and they can be interpreted as piecewise affine decision rules. We illustrate the performance of our algorithm on illustrative examples and on an inventory management problem.

Published: 28 Mar 2019

Performance guarantees for model-based Approximate Dynamic Programming in continuous spaces

Authors: Paul N. Beuchat, Angelos Georghiou, and John Lygeros

Publication: IEEE Transactions on Automatic Control, Forthcoming

Abstract: 

Published: 11 Mar 2019

Evaluation of the allocation performance in a fashion retail chain using data envelopment analysis

Authors: He Huang, Shanling Li & Yu Yu

Publication: The Journal of The Textile Institute, Forthcoming

Abstract: 

Published: 4 Mar 2019

Grocery stores for a more ethical world

While most will agree with making ethical food choices in theory, it remains difficult to sway consumers to change their buying behaviors.

For Professor Saibal Ray, Academic Director of the Bensadoun School of Retail Management, the benefits must be apparent and immediate for the average shopper.

The key, he goes on to explain, is finding ways to save people time and money.

Published: 28 Feb 2019

Welcoming a new MMA advisory member

The Masters of Management in Analytics program is pleased to announce that Wemba Opota, National Technology Strategist at Microsoft, has joined the program’s Advisory Board.

Learn more

Published: 20 Feb 2019

Welcoming a new MMA advisory member

The Master’s of Management in Analytics program is pleased to announce that Richard Hines, Senior Director, Data and Digital Enablement at Air Canada, has joined the program’s Advisory Board.

 

Published: 12 Feb 2019

Shoppers hit the stores with sights set on bargains

Black Friday and Cyber Monday have become synonymous with frenzied shoppers looking to get the best deals on their favorite products.

In light of their growing appeal, Professor Saibal Ray charts the development of these major shopping events, particularly within the Canadian market.

Published: 27 Nov 2018

Insights into the changing face of retail

On one of the biggest shopping days of the year, Professor Saibal Ray, Academic Director of the Bensadoun School of Retail Management joins Global News Morning to explore the unique opportunities that the school will bring for students and researchers interested in the evolving retail sector.

Published: 23 Nov 2018

Open for Business: McGill University’s Bensadoun School of Retail Management dedicated to the future of retail

Interdisciplinary teaching and research hub equips next generation of leaders to promote sustainable retail practices

At a time of significant transformation in the retail industry worldwide, the newly opened Bensadoun School of Retail Management (BSRM) at McGill University will act as a hub in the heart of Montreal for students, researchers and practitioners to work collaboratively towards addressing the host o

Published: 16 Nov 2018

The Decision Rule Approach to Optimization under Uncertainty: Methodology and Applications

Authors: Angelos Georghiou, Daniel Kuhn, Wolfram Wiesemann

Publication: Computational Management Science, Forthcoming

Abstract: 

Published: 15 Nov 2018

Robust Dual Dynamic Programming

Authors: Angelos Georghiou, Angelos Tsoukalas, Wolfram Wiesemann

Publication: Operations Research, Forthcoming

Abstract: 

Multi-stage robust optimization problems, where the decision maker can dynamically react to consecutively observed realizations of the uncertain problem parameters, pose formidable theoretical and computational challenges. As a result, the existing solution approaches for this problem class typically determine suboptimal solutions under restrictive assumptions. In this paper, we propose a robust dual dynamic programming (RDDP) scheme for multi-stage robust optimization problems. The RDDP scheme takes advantage of the decomposable nature of these problems by bounding the costs arising in the future stages through lower and upper cost to-go functions. For problems with uncertain technology matrices and/or constraint right-hand sides, our RDDP scheme determines an optimal solution in finite time. If also the objective function and/or the recourse matrices are uncertain, our method converges asymptotically (but deterministically) to an optimal solution. Our RDDP scheme does not require a relatively complete recourse, and it offers deterministic upper and lower bounds throughout the execution of the algorithm. We demonstrate the promising performance of our algorithm in a stylized inventory management problem.

Published: 15 Nov 2018

MMA assembles accomplished advisory board

This fall, the Masters of Management in Analytics (MMA) kicked off its first Advisory Board meeting to discuss the future directions of the MMA curriculum, which will benefit its inaugural cohort.

The MMA Advisory Board comprises senior industry leaders from a wide variety of educational and skills backgrounds who have excelled in their given fields.

Published: 31 Oct 2018

Optimizing Foreclosed Housing Acquisitions in Societal Response to Foreclosures

Authors: Senay Solak, Armagan Bayram, Mehmet Gumus, Yueran Zhuo

Publication: Operations Research, Forthcoming

Abstract:

A dramatic increase in U.S. mortgage foreclosures during and after the great economic recession of 2007-2009 had devastating impacts on the society and the economy. In response to such negative impacts, non-profit community development corporations (CDCs) throughout the U.S. utilize various resources, such as grants and lines of credit, in acquiring and redeveloping foreclosed housing units to support neighborhood stabilization and revitalization. Given that the cost of all such acquisitions far exceeds the resources accessible by these non-profit organizations, we identify socially optimal policies for CDCs in dynamically selecting foreclosed properties to target for potential acquisition as they become available over time. We evaluate our analytical results in a numerical study involving a CDC serving a major city in the U.S, and specify social return based thresholds defining selection decisions at different funding levels. We also find that for most foreclosed properties CDCs should not offer more than the asking price, and should typically consider overbidding only when the total available budget is low. Overall, comparisons of optimal policies with historical acquisition data suggest a potential improvement of around 20% in expected total impacts of the acquisitions on nearby property values. Considering a CDC with annual fund availability of $4 million for investment, this corresponds to an estimated additional value of around $280,000 for the society.

Published: 15 Oct 2018

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