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Authors:听Divinus Oppong-Tawiah,听Jane Webster, Sandy Staples, Ann-Frances Cameron, Ana Ortiz de Guinea, Tam Y. Hung

Publication: Journal of Business Research, Forthcoming

Abstract:听

Authors:听Angelos Georghiou, Angelos Tsoukalas, Wolfram Wiesemann

Publication:听Operations Research, Forthcoming

础产蝉迟谤补肠迟:听

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.

Authors:听Senay Solak, Armagan Bayram, Mehmet Gumus,听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.

Professor Patricia Hewlin鈥檚 co-authored article entitled, 鈥淗ow do callings relate to job performance? The role of organizational commitment and ideological contract fulfillment,鈥� was nominated by the editors of Human Relations as one of the top papers published in 2018.

The article is co-authored in part by Desautels PhD alumni Sung Soo Kim and Donghoon Shin.

Human Relations is among the FT 50 journal list.

Angelos Georghiou,听Assistant Professor in Operations Management, was recently听appointed Associate Editor of Energy Systems - Optimization, Modeling, Simulation, and Economic Aspects.

The journal Energy Systems presents mathematical programming, control, and economic approaches towards energy systems related topics, and is especially relevant in light of the major worldwide challenges confronting humanity in this century.

Authors:听Wei Qi and Zuo-Jun Max Shen

Publication: Production and Operations Management, Forthcoming

Abstract:

We are entering an era of great expectations towards our cities. The vision of 鈥渟mart city鈥� has been pursued worldwide to transform urban habitats into superior efficiency, quality and sustainability. This phenomenon prompts us to ponder what role the scholars in operations management (OM) can assume. In this essay, we express our initial thoughts on expanding OM to the smart-city scope. We review smart-city initiatives of governments, industry, national laboratories and academia. We argue that the smart-city movement will transition from the tech-oriented stage to the decision-oriented stage. Hence, a smart city can be perceived as a system scope within which planning and operational decisions are orchestrated at the urban scale, reflective of multidimensional needs, and adaptive to massive data and innovation. The benefits of studying smart-city OM are manifold and significant: contributing to deeper understanding of smart cities by providing advanced analytical frameworks, pushing OM knowledge boundaries (such as data-driven decision making), and empowering the OM community to deliver much broader impacts than before. We discuss several research opportunities to embody these thoughts, in the interconnected contexts of smart buildings, smart grid, smart mobility and new retail. These opportunities arise from the increasing integration of systems and business models at the urban scale.