Kwong Meng Teo

Massachusetts Institute of Technology (MIT), Operations Research Center, Alumnus

National University of Singapore, Industrial and Systems Engineering, Faculty Member

Followers

Following

Co-authors

Public Views

Huawei Supply Chain Laboratory
SF Express Strategic Resource Planning
SF Express Network Planning (2017: 50+ planes, 10k trucks)
Expertise: Algorithms, Analytics, Applied Operations Research, Applied Optimization, Heuristics, Network Anaysis, Network Flows
Supervisors: Dimitris Bertsimas
Address: www.linkedin.com/in/kwongmeng

less

Andrej Dujella

University of Zagreb

Hemin Koyi

Uppsala University

Jana Javornik

University of East London

Graham Martin

University of Leicester

Gwen Robbins Schug

University of North Carolina at Greensboro

Gabriel Gutierrez-Alonso

University of Salamanca

John Sutton

Macquarie University

Eros Carvalho

Universidade Federal do Rio Grande do Sul

Kevin Arbuckle

Swansea University

Jesper Hoffmeyer

University of Copenhagen

Uploads

Papers by Kwong Meng Teo

A Systems Perspective of Cycling and Bike-sharing Systems in Urban Mobility

Urban mobility is a prevalent problem in many cities around the world. Cycling offers a fast and ... more Urban mobility is a prevalent problem in many cities around the world. Cycling offers a fast and cheap transportation option for short-distance trips, with smaller carbon and physical footprint than driving a car. Cycling can also encourage a modal shift from private car to public transport by providing efficient last mile connections. This has led to a renewed interest to promote cycling in cities, manifesting in a growing number of bike-sharing projects with larger bicycle fleets. However, the economic sustainability of these bike-sharing systems has not been demonstrated. Moreover, city governments may invest resources in bike-sharing projects at the expense of developing policies or infrastructure to improve cycling safety and convenience. We take a systems perspective to study how bike-sharing and other policies can influence cycling as a transport mode in the urban mobility problem. We observe that while bike-sharing projects may increase cycling level and generate public dema...

System Identification of an Autonomous Underwater Vehicle Via InField Experiments

The dynamic characteristic of an autonomous underwater vehicle (AUV) is affected when it is recon... more The dynamic characteristic of an autonomous underwater vehicle (AUV) is affected when it is reconfigured with different payloads. It is desirable to have an updated model, such that the control and guidance law can be redesigned to obtain better performance. Hence, we develop amethod to enable online identification of AUV dynamics via in-field experiments, where the AUV is commanded to execute a compact set of maneuvers under doublet excitation. The identification process has two stages. In the training stage, state variable filter and recursive least square (SVF-RLS) estimator is used to estimate the unknown parameters. In the validation stage, the prediction capability of the model is checked using a fresh data set. The parameters converged within 12 s in the experiments using five different thrusts. Validation results show that the identified models are able to explain 78% to 92% of the output variation. Next, we compare the SVF-RLS estimator with the conventional offline identif...

Cooperative path planning for UAVs with UAV loss considerations

2013 IEEE Symposium on Computational Intelligence for Security and Defense Applications (CISDA), 2013

Considering the dynamic environments where mechanical failures and/or ground-based threats take p... more Considering the dynamic environments where mechanical failures and/or ground-based threats take place, unmanned aerial vehicles (UAVs) may be lost when performing tasks. As such, designing path planning algorithms in such dynamic scenarios poses significant challenges. In this paper, we propose a cooperative path planning algorithm that is decentralized and adapts to the dynamic environments. This algorithm consists of two stages: in the static stage (i.e., before starting from the base station), the path planning is formulated as a mixed-integer linear program (MILP) problem that the optimal solutions can be obtained by specific solvers; in the dynamic stages (i.e., during UAVs' flight), task reassignment is adaptively conducted among surviving UAVs' cooperations once a UAV is lost. To evaluate the effectiveness of the proposed algorithm, we demonstrate its superior performance through simulations compared to centralized ones in terms of the ratio of mission completion and the total completion time.

Discrete Optimization Vehicle routing problem with time windows and a limited number of vehicles

This paper introduces a variant of the vehicle routing problem with time windows where a limited ... more This paper introduces a variant of the vehicle routing problem with time windows where a limited number of vehicles is given (m-VRPTW). Under this scenario, a feasible solution is one that may contain either unserved customers and/or relaxed time windows. We provide a computable upper bound to the problem. To solve the problem, we propose a tabu search approach characterized by a holding list and a mechanism to force dense packing within a route. We also allow time windows to be relaxed by introducing the notion of penalty for lateness. In our approach, customer jobs are inserted based on a hierarchical objective function that captures multiple objectives. Computational results on benchmark problems show that our approach yields solutions that are competitive to best- published results on VRPTW. On m-VRPTW instances, experiments show that our approach produces solutions that are very close to computed upper bounds. Moreover, as the number of vehicles decreases, the routes become mor...

Robust optimization in electromagnetic scattering problems

Journal of Applied Physics, 2007

In engineering design, the physical properties of a system can often only be described by numeric... more In engineering design, the physical properties of a system can often only be described by numerical simulation. Optimization of such systems is usually accomplished heuristically without taking into account that there are implementation errors that lead to very suboptimal, and often, infeasible solutions. We present a robust optimization method for electromagnetic scattering problems with large degrees of freedom and report on results when this technique is applied to optimization of aperiodic dielectric structures. The spatial configuration of 50 dielectric scattering cylinders is optimized to match a desired target function such that the optimal arrangement is robust against placement and prototype errors. Our optimization method inherently improves the robustness of the optimized solution with respect to relevant errors and is suitable for real-world design of materials with unconventional electromagnetic functionalities, as relevant to nanophotonics.

Download

Optimal producer well placement and production planning in an oil reservoir

Computers & Chemical Engineering, 2013

Most of the available literature on optimal well placement has employed numerical simulators in a... more Most of the available literature on optimal well placement has employed numerical simulators in a black box manner linked to an external search engine. In this work, we formulate the contents of that box inside a mixed integer nonlinear programming model for optimal well placement. We provide a unified model that integrates the subsurface, wells, and surface levels of an upstream production project. It links the production plan with the aforementioned elements, and economics and market. This results in a complex spatiotemporal mixed integer nonlinear model, for whose solution we modify and augment an existing outer approximation algorithm. The model solution provides the optimal number of new producers, their locations, and optimal production plan over a given planning horizon. To our knowledge, this is the first contribution that uses mathematical programming in a real dynamic sense by honoring the constituent partial differential equations.

Download

Nonconvex robust optimization

We propose a novel robust optimization technique, which is applicable to nonconvex and simulation... more We propose a novel robust optimization technique, which is applicable to nonconvex and simulation-based problems. Robust optimization finds decisions with the best worst-case performance under uncertainty. If constraints are present, decisions should also be feasible under perturbations. In the real-world, many problems are nonconvex and involve computer-based simulations. In these applications, the relationship between decision and outcome is not defined through algebraic functions. Instead, that relationship ...

Download

Nonconvex Robust Optimization for Problems with Constraints

INFORMS Journal on Computing, 2010

We propose a new robust optimization method for problems with objective functions that may be com... more We propose a new robust optimization method for problems with objective functions that may be computed via numerical simulations and incorporate constraints that need to be feasible under perturbations. The proposed method iteratively moves along descent directions for the robust problem with nonconvex constraints and terminates at a robust local minimum. We generalize the algorithm further to model parameter uncertainties. We demonstrate the practicability of the method in a test application on a nonconvex problem with a polynomial cost function as well as in a real-world application to the optimization problem of intensity-modulated radiation therapy for cancer treatment. The method significantly improves the robustness for both designs.

Download

Robust nonconvex optimization for simulation-based problems

Operations Research, Jun 1, 2007

Uncertainty is typically present in real-world applications. Information used to model a problem ... more Uncertainty is typically present in real-world applications. Information used to model a problem is often noisy, incomplete or even erroneous. In science and engineering, measurement errors are inevitable. In business applications, the cost and selling price as well as the demand of a product are, at best, expert opinions. Moreover, even if uncertainties in the model data can be ignored, solutions cannot be implemented to infinite precision, as assumed in continuous optimization. Therefore, an “optimal” solution can easily be sub- ...

Download

Vehicle routing problem with time windows and a limited number of vehicles

European Journal of Operational Research, Aug 1, 2003

Download

A lifecycle-based sustainability indicator framework for waste-to-energy systems and a proposed metric of sustainability

Renewable and Sustainable Energy Reviews, 2016

Dynamic Optimal Well Placement In Oil Reservoirs

by I Karimi and Kwong Meng Teo

Abstract OPEC predicts the oil industry to increase its production by almost 23% of the current l... more Abstract OPEC predicts the oil industry to increase its production by almost 23% of the current level to be able to fulfill the world oil demand in the next 20 years. However, the hydrocarbon resources are limited, and hence it is highly crucial to exploit the new, marginal and existing mature fields in an optimal way. In this situation, optimal well placement can play an important role with long-term financial impact. However, determining optimal well locations is inherently a complex nonlinear and combinatorial problem due to the spatial- ...

Disruption Response Planning for an Urban Mass Rapid Transit Network

ABSTRACT Given many cities’ growing dependence on public rail transport, simple network disruptio... more ABSTRACT Given many cities’ growing dependence on public rail transport, simple network disruptions can lead to widespread confusion and significant productivity loss to the society. Therefore, a systematic approach to develop efficient disruption response and minimize the negative impacts is required. In this paper, we develop a planning procedure to supplement a degraded urban mass rapid transit network through intelligent introduction of shuttle bus services in the disrupted area. The proposed method includes two important mechanisms, namely (1) using column generation to identify all beneficial bus routes, including those which might not be intuitively found, and (2) using a path-based multi-commodity flow formulation to select the best among these candidate bus routes. Finally, the method is applied to two disruption case studies defined using real-world data; the corresponding results confirmed the practicality of the proposed approach: (1) the procedure can be carried out efficiently, (2) introducing bus routes to the naive bridging services can easily yield significant improvement on commuters’ travel delay, (3) the distribution of commuters’ travel delay is improved considerably with an optimized response, and (4) many realistic operating constraints can be handled in planning process.

Well Placement, Infrastructure Design, Facility Allocation, and Production Planning in Multireservoir Oil Fields with Surface Facility Networks

by Kwong Meng Teo and I Karimi

Industrial & Engineering Chemistry Research, 2014

ABSTRACT Managing oil fields with multiple reservoirs and shared surface networks optimally is a ... more ABSTRACT Managing oil fields with multiple reservoirs and shared surface networks optimally is a challenging practical problem. The majority of studies on optimal well placement have focused on either the interactions within the surface network facilities or the dynamic states of the subsurface environment. This work holistically integrates both surface and subsurface sections and addresses well placement, surface network design and allocation, and production/injection planning in a field with multiple irregular-shaped reservoirs. We consider the dynamic, economic, and operational interdependencies of the reservoirs, shared surface network, and common oil market through a complex, nonconvex, and deterministic mixed integer nonlinear programming model. Our approach determines the optimal number and locations of wells, design or retrofit of surface network, connections/allocations of wells with surface facilities, and optimal injection/production planning in water-drive reservoirs. We illustrate the complex interplay of well operations and throughputs using a literature example.

Minimum Speed Seeking Control for Nonhovering Autonomous Underwater Vehicles

by Kwong Meng Teo and YouHong Eng

Journal of Field Robotics, 2015

Optimizing Bus Bridging Services in Response to Disruptions of Urban Transit Rail Networks

Transportation Science, Feb 4, 2015

ABSTRACT With growing dependence of many cities on urban mass transit, even limited disruptions o... more ABSTRACT With growing dependence of many cities on urban mass transit, even limited disruptions of public transportation networks can lead to widespread confusion and significant productivity losses. A need exists for systematic approaches to developing efficient responses to minimize such negative impacts. We present an optimization-based approach that responds to degradations of urban transit rail networks by introducing smartly designed bus bridging services that take into consideration commuter travel demand at the time of the disruption. The approach consists of three fundamental steps, namely, (1) a column generation procedure to dynamically generate demand-responsive candidate bus routes, (2) a path-based multicommodity network flow model to identify the most effective combination of these candidate bus routes, and (3) another optimization-based procedure to determine simultaneously the optimal allocation of available vehicle resources among the selected routes and corresponding headways. The approach is applied to two case studies defined using actual data. The results show that the proposed approach can be carried out efficiently and that adding nonintuitive bus routes to the standard bus bridging services can significantly reduce the average travel delay. Moreover, the approach distributes delay more equitably. Many realistic operating constraints can also be handled.

Robust Optimization of Aperiodic Photonic Structures

8.4.1 A Systems Perspective to Commuter Cycling in Urban Mobility

INCOSE International Symposium, 2013

Reliability of surveillance mission with unmanned aerial vehicles

2011 IEEE International Conference on Industrial Engineering and Engineering Management, 2011

Abstract This paper has modeled the reliability of surveillance mission with unmanned aerial vehi... more Abstract This paper has modeled the reliability of surveillance mission with unmanned aerial vehicles (UAVs). In order to surveil a number of targets, some UAVs can be assigned to visit the targets. It is assumed that if a UAV is shot down during the mission all the targets assigned to the UAV cannot be surveilled. The mission is regarded as successful if all the targets are assigned and successfully surveilled. An optimization framework is presented to solve the UAV routing plan with the consideration of mission reliability.

Optimizing Bus Bridging Services in Response to Disruptions of Urban Transit Rail Networks

Transportation Science, 2015