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 Argonne Model for Universal Solvent Extraction (AMUSE); Computer programming; Radioactive wastes – Purification; Reactor fuel reprocessing; Separation (Technology); Software engineering; System analysis; Systems engineering; Transmutation (Chemistry) (2)
 Neural Network (2)
 Access Protocols (2)
 Lyapunov Methods (2)
 Energy Consumption (1)

 , Neural networks (NNs) (1)
 MIMO systems (1)
 DPC (1)
 AdaptiveCritic NN Controller (1)
 Atomic Force Microscope (AFM) (1)
 Artificial intelligence (1)
 Discretetime sysems (1)
 Distributed Control (1)
 Heuristics (1)
 Energy Conservation (1)
 Combinatorial optimization (1)
 Drift (1)
 Manipulator Dynamics (1)
 Channel Estimation (1)
 Adaptive Neural Network (NN) Controller (1)
 Distributed Power Control Algorithm (1)
 Ad Hoc Wireless Network (1)
 Alphabearing wastes; Argonne Model for Universal Solvent Extraction (AMUSE); Computer programming; Separation (Technology); Software engineering; System analysis; Systems engineering; Transuranium elements – Separation; Uranium Recovery by Extraction (UREX) (1)
 Lyapunov functions (1)
 Backpressure Mechanism (1)
 Closed Loop Systems (1)
 BackOff Scheme (1)
 Ad Hoc Networks (1)
 Congestion Control (1)
 Adaptive Control (1)
Articles 1  20 of 20
FullText Articles in Operations Research, Systems Engineering and Industrial Engineering
A Generic ObjectOriented Tabu Search Framework, Hoong Chuin Lau, Xiaomin Jia, Wee Chong Wan
A Generic ObjectOriented Tabu Search Framework, Hoong Chuin Lau, Xiaomin Jia, Wee Chong Wan
Research Collection School Of Information Systems
Presently, most tabu search designers devise their applications without considering the potential of design and code reuse, which consequently prolong the development of subsequent applications. In this paper, we propose a software solution known as Tabu Search Framework (TSF), which is a generic C++ software framework for tabu search implementation. The framework excels in code recycling through the use of a well designed set of generic abstract classes that clearly define their collaborative roles in the algorithm. Additionally, the framework incorporates a centralized process and control mechanism that enhances the search with intelligence. This results in a generic framework that ...
Partial Adjustable Autonomy In Multi Agent Environment And Its Application To Military Logistics, Hoong Chuin Lau, Lucas Agussurja, R. Thagarajoo
Partial Adjustable Autonomy In Multi Agent Environment And Its Application To Military Logistics, Hoong Chuin Lau, Lucas Agussurja, R. Thagarajoo
Research Collection School Of Information Systems
In a rapidly changing environment, the behavior and decisionmaking power of agents may have to be adaptive with respect to a fluctuating autonomy. In this paper, a centralized fuzzy approach is proposed to sense changes in environmental conditions and translate them to changes in agent autonomy. A distributed coalition formation scheme is then applied to allow agents in the new autonomy to renegotiate to establish schedule consistency. The proposed framework is applied to a realtime logistics control of a military hazardous material storage facility under peacetowar transition.
Solving Generalized Open Constraint Optimization Problem Using TwoLevel MultiAgent Framework, Hoong Chuin Lau, Lei Zhang, Chang Liu
Solving Generalized Open Constraint Optimization Problem Using TwoLevel MultiAgent Framework, Hoong Chuin Lau, Lei Zhang, Chang Liu
Research Collection School Of Information Systems
The Open Constraint Optimization Problem (OCOP) refers to the COP where constraints and variable domains can change over time and agents' opinions have to be sought over a distributed network to form a solution. The openness of the problem has caused conventional approaches to COP such as branchandbound to fail to find optimal solutions. OCOP is a new problem and the approach to find an optimal solution (minimum total cost) introduced in [1] is based on an unrealistic assumption that agents are willing to report their options in nondecreasing order of cost. In this paper, we study a generalized OCOP ...
Evaluation Of TimeVarying Availability In MultiEchelon Inventory System With Combat Damage, Hoong Chuin Lau, Huawei Song
Evaluation Of TimeVarying Availability In MultiEchelon Inventory System With Combat Damage, Hoong Chuin Lau, Huawei Song
Research Collection School Of Information Systems
No abstract provided.
Dispatching Vehicles In A Mega Container Terminal, Ebru K. Bish, Frank Y. Chen, Thin Yin Leong, Barry L. Nelson, Jonathan W. C. Ng, David SimchiLevi
Dispatching Vehicles In A Mega Container Terminal, Ebru K. Bish, Frank Y. Chen, Thin Yin Leong, Barry L. Nelson, Jonathan W. C. Ng, David SimchiLevi
Research Collection School Of Information Systems
We consider a container terminal discharging and uploading containers to and from ships. The discharged containers are stored at prespecified storage locations in the terminal yard. Containers are moved between the ship area and the yard using a fleet of vehicles, each of which can carry one container at a time. The problem is to dispatch vehicles to the containers so as to minimize the total time it takes to serve a ship, which is the total time it takes to discharge all containers from the ship and upload new containers onto the ship. We develop easily implementable heuristic algorithms ...
Tuning Tabu Search Strategies Via Visual Diagnosis, Steven Halim, Wee Chong Wan, Hoong Chuin Lau
Tuning Tabu Search Strategies Via Visual Diagnosis, Steven Halim, Wee Chong Wan, Hoong Chuin Lau
Research Collection School Of Information Systems
While designing working metaheuristics can be straightforward, tuning them to solve the underlying combinatorial optimization problem well can be tricky. Several tuning methods have been proposed but they do not address the new aspect of our proposed classification of the metaheuristic tuning problem: tuning search strategies. We propose a tuning methodology based on Visual Diagnosis and a generic tool called Visualizer for Metaheuristics Development Framework(VMDF) to address specifically the problem of tuning search (particularly Tabu Search) strategies. Under VMDF, we propose the use of a Distance Radar visualizer where the human and computer can collaborate to diagnose the occurrence ...
Exploiting Belief Bounds: Practical Pomdps For Personal Assistant Agents, Pradeep Varakantham, Rajiv Maheswaran, Milind Tambe
Exploiting Belief Bounds: Practical Pomdps For Personal Assistant Agents, Pradeep Varakantham, Rajiv Maheswaran, Milind Tambe
Research Collection School Of Information Systems
Agents or agent teams deployed to assist humans often face the challenges of monitoring the state of key processes in their environment (including the state of their human users themselves) and making periodic decisions based on such monitoring. POMDPs appear well suited to enable agents to address these challenges, given the uncertain environment and cost of actions, but optimal policy generation for POMDPs is computationally expensive. This paper introduces three key techniques to speedup POMDP policy generation that exploit the notion of progress or dynamics in personal assistant domains. Policy computation is restricted to the belief space polytope that remains ...
Approximate Strategic Reasoning Through Hierarchical Reduction Of Large Symmetric Games, Michael P. Wellman, Daniel M. Reeves, Kevin M. Lochner, ShihFen Cheng, Rahul Suri
Approximate Strategic Reasoning Through Hierarchical Reduction Of Large Symmetric Games, Michael P. Wellman, Daniel M. Reeves, Kevin M. Lochner, ShihFen Cheng, Rahul Suri
Research Collection School Of Information Systems
To deal with exponential growth in the size of a game with the number of agents, we propose an approximation based on a hierarchy of reduced games. The reduced game achieves savings by restricting the number of agents playing any strategy to fixed multiples. We validate the idea through experiments on randomly generated localeffect games. An extended application to strategic reasoning about a complex trading scenario motivates the approach, and demonstrates methods for gametheoretic reasoning over incompletelyspecified games at multiple levels of granularity.
Development Of Integrated Process Simulation System Model For Spent Fuel Treatment Facility (Sftf) Design: Quarterly Progress Report January 1March 31, 2005, Yitung Chen, Sean Hsieh
Development Of Integrated Process Simulation System Model For Spent Fuel Treatment Facility (Sftf) Design: Quarterly Progress Report January 1March 31, 2005, Yitung Chen, Sean Hsieh
Separations Campaign (TRP)
The Advanced Fuel Cycle Initiative (AFCI) and Transmutation Research ProgramUniversity Participation Program (TRPUPP) supported by Department of Energy of the United States have been developing many important technologies for the transmutation of nuclear waste to address longterm disposal issues. While successfully embedding AMUSE module into a dedicated System Engineering Model (TRPSEMPro), developed by the Nevada Center for Advanced Computational Methods (NCACM) at the University of NevadaLas Vegas collaborating with Argonne National Laboratory (ANL), ANL is interested in further simulating the Light Water Reactor (LWR) Spent Fuel Treatment Facility (SFTF) combining commercial process simulation and analysis packages and core calculation of ...
Reinforcement LearningBased Output Feedback Control Of Nonlinear Systems With Input Constraints, Pingan He, Jagannathan Sarangapani
Reinforcement LearningBased Output Feedback Control Of Nonlinear Systems With Input Constraints, Pingan He, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
A novel neural network (NN) based output feedback controller with magnitude constraints is designed to deliver a desired tracking performance for a class of multiinputmultioutput (MIMO) discretetime strict feedback nonlinear systems. Reinforcement learning in discrete time is proposed for the output feedback controller, which uses three NN: 1) a NN observer to estimate the system states with the inputoutput data; 2) a critic NN to approximate certain strategic utility function; and 3) an action NN to minimize both the strategic utility function and the unknown dynamics estimation errors. The magnitude constraints are manifested as saturation nonlinearities in the output feedback ...
Development Of A Systems Engineering Model Of The Chemical Separations Process, Yitung Chen, Darrell Pepper, Sean Hsieh
Development Of A Systems Engineering Model Of The Chemical Separations Process, Yitung Chen, Darrell Pepper, Sean Hsieh
Separations Campaign (TRP)
The chemical processing of used nuclear fuel is an integral component of any strategy for the transmutation of nuclear waste. Due to the large volume of material that must be handled in this first step of the transmutation process, the efficiency of the separations process is a key factor in the potential economic viability of transmutation strategies. The ability to optimize the chemical separation systems is vital to ensure the feasibility of the transmutation program.
Systems analysis, or total systems modeling, is one of the strongest tools available to researchers for understanding and optimizing complex systems such as chemical separations ...
Development Of Integrated Process Simulation System Model For Spent Fuel Treatment Facility (Sftf) Design, Yitung Chen, Sean Hsieh
Development Of Integrated Process Simulation System Model For Spent Fuel Treatment Facility (Sftf) Design, Yitung Chen, Sean Hsieh
Separations Campaign (TRP)
The major objective is to create a framework that combines all the strengths of AMUSE’s complicated calculations, well established commercial system process package such as ASPENPLUS, HYSYS and PRO/II and TRPSEMPro’s flexible parameter optimization modules. Development of the process simulation code can be done using the solvent extraction process experience at Argonne National Laboratory and in collaboration with the NCACM.
The major activities of the task are the following:
 Develop a framework for simulating the SFTF process using AMUSE code, commercial process package, such as ASPEN PLUS, and system engineering model.
 Develop a middleware package that can ...
Neural NetworkBased Control Of Nonlinear DiscreteTime Systems In NonStrict Form, Jagannathan Sarangapani, Zheng Chen, Pingan He
Neural NetworkBased Control Of Nonlinear DiscreteTime Systems In NonStrict Form, Jagannathan Sarangapani, Zheng Chen, Pingan He
Electrical and Computer Engineering Faculty Research & Creative Works
A novel reinforcement learningbased adaptive neural network (NN) controller, also referred as the adaptivecritic NN controller, is developed to deliver a desired tracking performance for a class of nonstrict feedback nonlinear discretetime systems in the presence of bounded and unknown disturbances. The adaptive critic NN controller architecture includes a critic NN and two action NNs. The critic NN approximates certain strategic utility function whereas the action neural networks are used to minimize both the strategic utility function and the unknown dynamics estimation errors. The NN weights are tuned online so as to minimize certain performance index. By using gradient descentbased ...
Predictive Congestion Control Mac Protocol For Wireless Sensor Networks, Maciej Jan Zawodniok, Jagannathan Sarangapani
Predictive Congestion Control Mac Protocol For Wireless Sensor Networks, Maciej Jan Zawodniok, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
Available congestion control schemes, for example transport control protocol (TCP), when applied to wireless networks results in a large number of packet drops, unfairness with a significant amount of wasted energy due to retransmissions. To fully utilize the hop by hop feedback information, a suite of novel, decentralized, predictive congestion control schemes are proposed for wireless sensor networks in concert with distributed power control (DPC). Besides providing energy efficient solution, embedded channel estimator in DPC predicts the channel quality. By using the channel quality and node queue utilizations, the onset of network congestion is predicted and congestion control is initiated ...
Block Phase CorrelationBased Automatic Drift Compensation For Atomic Force Microscopes, Qinmin Yang, Eric W. Bohannan, Jagannathan Sarangapani
Block Phase CorrelationBased Automatic Drift Compensation For Atomic Force Microscopes, Qinmin Yang, Eric W. Bohannan, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
Automatic nanomanipulation and nanofabrication with an Atomic Force Microscope (AFM) is a precursor for nanomanufacturing. In ambient conditions without stringent environmental controls, nanomanipulation tasks require extensive human intervention to compensate for the many spatial uncertainties of the AFM. Among these uncertainties, thermal drift is especially hard to solve because it tends to increase with time and cannot be compensated simultaneously by feedback. In this paper, an automatic compensation scheme is introduced to measure and estimate drift. This information can be subsequently utilized to compensate for the thermal drift so that a realtime controller for nanomanipulation can be designed as if ...
EnergyEfficient Rate Adaptation Mac Protocol For Ad Hoc Wireless Networks, Maciej Jan Zawodniok, Jagannathan Sarangapani
EnergyEfficient Rate Adaptation Mac Protocol For Ad Hoc Wireless Networks, Maciej Jan Zawodniok, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
Resource constraints in ad hoc wireless networks require that they are energy efficient during both transmission and rate adaptation. In this paper, we propose a novel energyefficient rate adaptation protocol that selects modulation schemes online to maximize throughput based on channel state while saving energy. This protocol uses the distributed power control (DPC) algorithm (M. Zawodniok et al., 2004) to accurately determine the necessary transmission power and to reduce the energy consumption. Additionally, the transmission rate is altered using energy efficiency as a constraint to meet the required throughput, which is estimated with queue fill ratio. Moreover, backoff scheme is ...
A Robust Controller For The Manipulation Of Micro Scale Objects, Qinmin Yang, Jagannathan Sarangapani
A Robust Controller For The Manipulation Of Micro Scale Objects, Qinmin Yang, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
A suite of novel robust controllers is presented for the manipulation and handling of microscale objects in a microelectromechanical system (MEMS) where adhesive, surface tension, friction and van der Waals forces are dominant. Moreover, these forces are typically unknown. The robust controller overcomes the unknown system dynamics and ensures the performance in the presence of actuator constraints by assuming that the upper bounds on these forces are known. On the other hand, for the robust adaptive controller, the unknown forces are estimated online. Using the Lyapunov approach, the uniformly ultimate boundedness (UUB) of the closedloop manipulation error is shown for ...
Decentralized DiscreteTime Neural Network Controller For A Class Of Nonlinear Systems With Unknown Interconnections, Jagannathan Sarangapani
Decentralized DiscreteTime Neural Network Controller For A Class Of Nonlinear Systems With Unknown Interconnections, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
A novel decentralized neural network (NN) controller in discretetime is designed for a class of uncertain nonlinear discretetime systems with unknown interconnections. Neural networks are used to approximate both the uncertain dynamics of the nonlinear systems and the unknown interconnections. Only local signals are needed for the decentralized controller design and the stability of the overall system can be guaranteed using the Lyapunov analysis. Further, controller redesign for the original subsystems is not required when additional subsystems are appended. Simulation results demonstrate the effectiveness of the proposed controller. The NN does not require an offline learning phase and the weights ...
A MultiAgent Approach For Solving Optimization Problems Involving Expensive Resources, Hoong Chuin Lau, H. Wang
A MultiAgent Approach For Solving Optimization Problems Involving Expensive Resources, Hoong Chuin Lau, H. Wang
Research Collection School Of Information Systems
In this paper, we propose a multiagent approach for solving a class of optimization problems involving expensive resources, where monolithic local search schemes perform miserably. More specifically, we study the class of binpacking problems. Under our proposed FineGrained Agent System scheme, rational agents work both collaboratively and selfishly based on local search and mimic physicsmotivated systems. We apply our approach to a generalization of binpacking  the Inventory Routing Problem with Time Windows  which is an important logistics problem, and demonstrate the efficiency and effectiveness of our approach.
Robust Temporal Constraint Networks, Hoong Chuin Lau, Thomas Ou, Melvyn Sim
Robust Temporal Constraint Networks, Hoong Chuin Lau, Thomas Ou, Melvyn Sim
Research Collection School Of Information Systems
In this paper, we propose the Robust Temporal Constraint Network (RTCN) model for simple temporal constraint networks where activity durations are bounded by random variables. The problem is to determine whether such temporal network can be executed with failure probability less than a given 0 ≤ E ≤ 1 for each possible instantiation of the random variables, and if so. how one might find a feasible schedule with each given instantiation. The advantage of our model is that one can vary the value of ∊ to control the level of conservativeness of the solution. We present a computationally tractable and efficient approach to ...