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Articles 1  17 of 17
FullText Articles in Operations Research, Systems Engineering and Industrial Engineering
A Pomdp Model For Guiding Taxi Cruising In A Congested Urban City, Lucas Agussurja, Hoong Chuin Lau
A Pomdp Model For Guiding Taxi Cruising In A Congested Urban City, Lucas Agussurja, Hoong Chuin Lau
Research Collection School Of Information Systems
We consider a partially observable Markov decision process (POMDP) model for improving a taxi agent cruising decision in a congested urban city. Using realworld data provided by a large taxi company in Singapore as a guide, we derive the state transition function of the POMDP. Specifically, we model the cruising behavior of the drivers as continuoustime Markov chains. We then apply dynamic programming algorithm for finding the optimal policy of the driver agent. Using a simulation, we show that this policy is significantly better than a greedy policy in congested road network.
Allocating Resources In Multiagent Flowshops With Adaptive Auctions, Hoong Chuin Lau, Zhengyi Zhao, Sam Shuzhi Ge, Thong Heng Lee
Allocating Resources In Multiagent Flowshops With Adaptive Auctions, Hoong Chuin Lau, Zhengyi Zhao, Sam Shuzhi Ge, Thong Heng Lee
Research Collection School Of Information Systems
In this paper, we consider the problem of allocating machine resources among multiple agents, each of which is responsible to solve a flowshop scheduling problem. We present an iterated combinatorial auction mechanism in which bid generation is performed within each agent, while a price adjustment procedure is performed by a centralized auctioneer. While this approach is fairly wellstudied in the literature, our primary innovation is in an adaptive price adjustment procedure, utilizing variable stepsize inspired by adaptive PIDcontrol theory coupled with utility pricing inspired by classical microeconomics. We compare with the conventional price adjustment scheme proposed in Fisher (1985), and ...
Taxisim: A Multiagent Simulation Platform For Evaluating Taxi Fleet Operations, ShihFen Cheng, Thi Duong Nguyen
Taxisim: A Multiagent Simulation Platform For Evaluating Taxi Fleet Operations, ShihFen Cheng, Thi Duong Nguyen
Research Collection School Of Information Systems
Taxi service is an important mode of public transportation in most metropolitan areas since it provides doortodoor convenience in the public domain. Unfortunately, despite all the convenience taxis bring, taxi ﬂeets are also extremely inefficient to the point that over 50% of its operation time could be spent in idling state. Improving taxi ﬂeet operation is an extremely challenging problem, not just because of its scale, but also due to fact that taxi drivers are selfinterested agents that cannot be controlled centrally. To facilitate the study of such complex and decentralized system, we propose to construct a multiagent simulation platform ...
A Study On Facility Planning Using Discrete Event Simulation: Case Study Of A Grain Delivery Terminal., Sarah M. Asio
A Study On Facility Planning Using Discrete Event Simulation: Case Study Of A Grain Delivery Terminal., Sarah M. Asio
Industrial and Management Systems Engineering  Dissertations and Student Research
The application of traditional approaches to the design of efficient facilities can be tedious and time consuming when uncertainty and a number of constraints exist. Queuing models and mathematical programming techniques are not able to capture the complex interaction between resources, the environment and space constraints for dynamic stochastic processes. In the following study discrete event simulation is applied to the facility planning process for a grain delivery terminal. The discrete event simulation approach has been applied to studies such as capacity planning and facility layout for a gasoline station and evaluating the resource requirements for a manufacturing facility. To ...
Finding RobustUnderRisk Solutions For Flowshop Scheduling, Steven O. Kimbrough, Ann Kuo, Hoong Chuin Lau
Finding RobustUnderRisk Solutions For Flowshop Scheduling, Steven O. Kimbrough, Ann Kuo, Hoong Chuin Lau
Research Collection School Of Information Systems
We propose and explore, in the context of benchmark problems for flowshop scheduling, a riskbased concept of robustness for optimization problems. This riskbased concept is in distinction to, and complements, the uncertaintybased concept employed in the field known as robust optimization. Implementation of our concept requires problem solution methods that sample the solution space intelligently and that produce large numbers of distinct sample points. With these solutions to hand, their robustness scores are easily obtained and heuristically robust solutions found. We find evolutionary computation to be effective for this purpose on these problems.
Scalable Multiagent Planning Using Probabilistic Inference, Akshat Kumar, Shlomo Zilberstein, Marc Toussaint
Scalable Multiagent Planning Using Probabilistic Inference, Akshat Kumar, Shlomo Zilberstein, Marc Toussaint
Research Collection School Of Information Systems
Multiagent planning has seen much progress with the development of formal models such as DecPOMDPs. However, the complexity of these models  NEXPComplete even for two agents  has limited scalability. We identify certain mild conditions that are sufficient to make multiagent planning amenable to a scalable approximation w.r.t. the number of agents. This is achieved by constructing a graphical model in which likelihood maximization is equivalent to plan optimization. Using the ExpectationMaximization framework for likelihood maximization, we show that the necessary inference can be decomposed into processes that often involve a small subset of agents, thereby facilitating scalability. We ...
MessagePassing Algorithms For Quadratic Programming Formulations Of Map Estimation, Akshat Kumar, Shlomo Zilberstein
MessagePassing Algorithms For Quadratic Programming Formulations Of Map Estimation, Akshat Kumar, Shlomo Zilberstein
Research Collection School Of Information Systems
Computing maximum a posteriori (MAP) estimation in graphical models is an important inference problem with many applications. We present messagepassing algorithms for quadratic programming (QP) formulations of MAP estimation for pairwise Markov random fields. In particular, we use the concaveconvex procedure (CCCP) to obtain a locally optimal algorithm for the nonconvex QP formulation. A similar technique is used to derive a globally convergent algorithm for the convex QP relaxation of MAP. We also show that a recently developed expectationmaximization (EM) algorithm for the QP formulation of MAP can be derived from the CCCP perspective. Experiments on synthetic and realworld problems ...
RealWorld Parameter Tuning Using Factorial Design With Parameter Decomposition, Aldy Gunawan, Hoong Chuin Lau, Elaine Wong
RealWorld Parameter Tuning Using Factorial Design With Parameter Decomposition, Aldy Gunawan, Hoong Chuin Lau, Elaine Wong
Research Collection School Of Information Systems
In this paper, we explore the idea of improving the efficiency of factorial design for parameter tuning of metaheuristics. In a standard full factorial design, the number of runs increases exponentially as the number of parameters. To reduce the parameter search space, one option is to first partition parameters into disjoint categories. While this may be done manually based on user guidance, an automated approach proposed in this paper is to apply a fractional factorial design to partition parameters based on their main effects where each partition is then tuned independently. With a careful choice of fractional design, our approach ...
MessagePassing Algorithms For Large Structured Decentralized Pomdps, Akshat Kumar, Shlomo Zilberstein
MessagePassing Algorithms For Large Structured Decentralized Pomdps, Akshat Kumar, Shlomo Zilberstein
Research Collection School Of Information Systems
Decentralized POMDPs provide a rigorous framework for multiagent decisiontheoretic planning. However, their high complexity has limited scalability. In this work, we present a promising new class of algorithms based on probabilistic inference for infinitehorizon NDPOMDPsa restricted DecPOMDP model. We first transform the policy optimization problem to that of likelihood maximization in a mixture of dynamic Bayes nets (DBNs). We then develop the ExpectationMaximization (EM) algorithm for maximizing the likelihood in this representation. The EM algorithm for NDPOMDPs lends itself naturally to a simple messagepassing paradigm guided by the agent interaction graph. It is thus highly scalable w.r.t. the ...
Incremental Dcop Search Algorithms For Solving Dynamic Dcop Problems, William Yeoh, Pradeep Varakantham, Xiaoxun Sun, Sven Koenig
Incremental Dcop Search Algorithms For Solving Dynamic Dcop Problems, William Yeoh, Pradeep Varakantham, Xiaoxun Sun, Sven Koenig
Research Collection School Of Information Systems
Distributed constraint optimization problems (DCOPs) are wellsuited for modeling multiagent coordination problems. However, most research has focused on developing algorithms for solving static DCOPs. In this paper, we model dynamic DCOPs as sequences of (static) DCOPs with changes from one DCOP to the next one in the sequence. We introduce the ReuseBounds procedure, which can be used by anyspace ADOPT and anyspace BnBADOPT to find costminimal solutions for all DCOPs in the sequence faster than by solving each DCOP individually. This procedure allows those agents that are guaranteed to remain unaffected by a change to reuse their lower and upper ...
Decentralized Decision Support For An Agent Population In Dynamic And Uncertain Domains, Pradeep Reddy Varakantham, ShihFen Cheng, Thi Duong Nguyen
Decentralized Decision Support For An Agent Population In Dynamic And Uncertain Domains, Pradeep Reddy Varakantham, ShihFen Cheng, Thi Duong Nguyen
Research Collection School Of Information Systems
This research is motivated by problems in urban transportation and labor mobility, where the agent ﬂow is dynamic, nondeterministic and on a large scale. In such domains, even though the individual agents do not have an identity of their own and do not explicitly impact other agents, they have implicit interactions with other agents. While there has been much research in handling such implicit effects, it has primarily assumed controlled movements of agents in static environments. We address the issue of decision support for individual agents having involuntary movements in dynamic environments . For instance, in a taxi ﬂeet serving a ...
Distributed Model Shaping For Scaling To Decentralized Pomdps With Hundreds Of Agents, Prasanna Velagapudi, Pradeep Reddy Varakantham, Katia Sycara, Paul Scerri
Distributed Model Shaping For Scaling To Decentralized Pomdps With Hundreds Of Agents, Prasanna Velagapudi, Pradeep Reddy Varakantham, Katia Sycara, Paul Scerri
Research Collection School Of Information Systems
The use of distributed POMDPs for cooperative teams has been severely limited by the incredibly large joint policy space that results from combining the policyspaces of the individual agents. However, much of the computational cost of exploring the entire joint policy space can be avoided by observing that in many domains important interactions between agents occur in a relatively small set of scenarios, previously defined as coordination locales (CLs) [11]. Moreover, even when numerous interactions might occur, given a set of individual policies there are relatively few actual interactions. Exploiting this observation and building on an existing model shaping algorithm ...
Support Of Product Innovation With A Modular Framework For Knowledge Management: A Case Study, Douglas C. Eddy, Sundar Krishnamurty, Ian R. Grosse, Jack C. Wileden
Support Of Product Innovation With A Modular Framework For Knowledge Management: A Case Study, Douglas C. Eddy, Sundar Krishnamurty, Ian R. Grosse, Jack C. Wileden
Center for eDesign Proceedings
This paper presents an eDesign framework for knowledge management through its application in an engineering design case study. The eDesign framework enables the implementation of integrated design information throughout the entire design process. It facilitates the ease of sharing real time information across multiple individual designers, departments, or organizations as would be required in large scale design efforts. Similarly, it allows for the ease of use of technical tools integral to the design process that small design departments depend upon. Thus, regardless of the scale, the efficiency of engineering design can be improved with the use of the eDesign framework ...
Towards Industrial Implementation Of Emerging Semantic Technologies, Jay T. Brindel, Ian R. Grosse, Sundar Krishnamurty, John Altidor, Seth Trachtenberg, Paul Witherell
Towards Industrial Implementation Of Emerging Semantic Technologies, Jay T. Brindel, Ian R. Grosse, Sundar Krishnamurty, John Altidor, Seth Trachtenberg, Paul Witherell
Center for eDesign Proceedings
Every new design, project, or procedure within a company generates a considerable amount of new information and important knowledge. Furthermore, a tremendous amount of legacy knowledge already exists in companies in electronic and nonelectronic formats, and techniques are needed for representing, structuring and reusing this knowledge. Many researchers have spent considerable time and effort developing semantic knowledge management systems, which in theory are presumed to address these problems. Despite significant research investments, little has been done to implement these systems within an industrial setting. In this paper we identify five main requirements to the development of an industryready application of ...
Improving Service Through JustInTime Concept In A Dynamic Operational Environment, Kar Way Tan, Hoong Chuin Lau, Na Fu
Improving Service Through JustInTime Concept In A Dynamic Operational Environment, Kar Way Tan, Hoong Chuin Lau, Na Fu
Research Collection School Of Information Systems
This paper is concerned with the problem of JustInTime (JIT) job scheduling in a dynamic environment under uncertainty to attain timely service. We provide an approach, based on robust scheduling concepts, to analytically evaluate the expected cost of earliness and tardiness for each job and also the project. In addition, we search for a schedule execution policy with the minimum robust cost such that for a given risk level (epsilon), the actual realized schedule has (1  epsilon) probability of completing with less than or equal to this robust cost. Our method is quite generic, and can be applied to JIT ...
InstanceBased Parameter Tuning Via Search Trajectory Similarity Clustering, Linda Lindawati, Hoong Chuin Lau, David Lo
InstanceBased Parameter Tuning Via Search Trajectory Similarity Clustering, Linda Lindawati, Hoong Chuin Lau, David Lo
Research Collection School Of Information Systems
This paper is concerned with automated tuning of parameters in localsearch based metaheuristics. Several generic approaches have been introduced in the literature that returns a ”onesizefitsall” parameter configuration for all instances. This is unsatisfactory since different instances may require the algorithm to use very different parameter configurations in order to find good solutions. There have been approaches that perform instancebased automated tuning, but they are usually problemspecific. In this paper, we propose CluPaTra, a generic (problemindependent) approach to perform parameter tuning, based on CLUstering instances with similar PAtterns according to their search TRAjectories. We propose representing a search trajectory as ...
FineTuning Algorithm Parameters Using The Design Of Experiments Approach, Aldy Gunawan, Hoong Chuin Lau, Linda Lindawati
FineTuning Algorithm Parameters Using The Design Of Experiments Approach, Aldy Gunawan, Hoong Chuin Lau, Linda Lindawati
Research Collection School Of Information Systems
Optimizing parameter settings is an important task in algorithm design. Several automated parameter tuning procedures/configurators have been proposed in the literature, most of which work effectively when given a good initial range for the parameter values. In the Design of Experiments (DOE), a good initial range is known to lead to an optimum parameter setting. In this paper, we present a framework based on DOE to find a good initial range of parameter values for automated tuning. We use a factorial experiment design to first screen and rank all the parameters thereby allowing us to then focus on the ...