IORA gave out seed grants for Faculty Research Projects
The Institute of Operations Research and Analytics (IORA) gave out seed grants in 2018 to fund 8 research projects lead by our affiliated faculty members. The projects received funding from IORA over 2 to 3-year period.
The IORA grants aimed to provide funding and infrastructure for NUS researchers to study, develop, and test novel OR and Analytics methodologies. It’s objective is also to bring the academic community together, disseminate knowledge and encourage collaborations in order to address important decision problems in the business, economic and social sphere.
Faculty members studied and developed solutions to challenges and problems faced by smart cities of the future. The IORA grants was awarded to the following projects:
Project List
Faculty Research Projects
Tugboat Scheduling for Large Container Ports
About Research Project This project aims to investigate two practical and important tugboat scheduling problems for a given tugging service network of a large container port, namely, the static Tug Boat Scheduling (TBS) and the dynamic TBS. For the static TBS, container ships are ready in anchorages and their berthing ...
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Faculty Research Projects
Randomized algorithms for large-scale constrained optimization
About Research Project In particular, recent randomized algorithms such as stochastic gradient descent (SGD), stochastic variancereduced gradient descent (SVRG), and stochastic average gradient (SAG) were motivated by the need to solve unconstrained optimization problems where the objective is the sum of a large number of terms (making it expensive to ...
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Faculty Research Projects
Data Driven Inventory Modeling for Spare Parts in the MRO Industry
About Research Project In the MRO industry, a very challenging problem faced by many companies is how to efficiently manage spare parts inventory due to the difficulty in accurately forecasting their demands for spare parts. The demand pattern of spare parts usually shows high irregularity. With years of consulting experiences ...
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Faculty Research Projects
Realtime Matching for Shared Mobility Systems
About Research Project The objective of this proposal is to design effective models and systems for shared mobility systems,with the eventual goal to provide viable solutions, from both operational and technological perspectives, to sustainable transportation and logistics in smart cities. The scope of this research plan encompasses: 1) real-time matching ...
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Faculty Research Projects
3D Point Cloud Classification for Virtual NUS
About Research Project Singapore government is highly ambitious to build a smart nation to improve the well-beings of its residents. A key component toward this vision is Virtual Singapore, a virtual city model for smart planning, organization, and management of the public resource. As a trial to the more ambitious ...
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Faculty Research Projects
Simulation based Real-Time Decision Tools for Smart Warehousing
About Research Project As a critical node in any supply chain systems, warehousing is a common yet complex industrial practice that involves a variety of planning and operation problems, such as layout design, equipment configuration, inventory allocations and picking policies. Different strategies and operation rules need to be developed according ...
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Faculty Research Projects
Integrating Optimization into Constraint Solvers
About Research Project Combinatorial optimization problems lie at the heart of many real world problems. The current state of art for dealing with combinatorial problems has three different approaches: Linear and Integer Programming (LP/IP), boolean satisfiability (SAT), and Constraint Programming (CP). Each approach has its strengths and weaknesses. As combinatorial ...
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Faculty Research Projects
Models and algorithms for risk-aware stochastic games
About Research Project A central problem in building resilient systems, be those urban transport networks, asset allocation algorithms, or bank regulation frameworks, is the optimal control of risk-benefit trade-offs. Emerging literature on risk-aware and robust optimization has made significant headway in developing theory that rigorously accounts for decision makers ’risk-preferences, ...
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