Operations Research, Systems Engineering and Industrial Engineering Commons^™

Lagrangian Relaxation For Large-Scale Multi-Agent Planning, Geoffrey J. Gordon, Pradeep Varakantham, William Yeoh, Hoong Chuin Lau, Ajay S. Aravamudhan, Shih-Fen Cheng

Research Collection School Of Computing and Information Systems

Multi-agent planning is a well-studied problem with various applications including disaster rescue, urban transportation and logistics, both for autonomous agents and for decision support to humans. Due to computational constraints, existing research typically focuses on one of two scenarios: unstructured domains with many agents where we are content with heuristic solutions, or domains with small numbers of agents or special structure where we can provide provably near-optimal solutions. By contrast, in this paper, we focus on providing provably near-optimal solutions for domains with large numbers of agents, by exploiting a common domain-general property: if individual agents each have limited influence …

A Mechanism For Organizing Last-Mile Service Using Non-Dedicated Fleet, Shih-Fen Cheng, Duc Thien Nguyen, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Unprecedented pace of urbanization and rising income levels have fueled the growth of car ownership in almost all newly formed megacities. Such growth has congested the limited road space and significantly affected the quality of life in these megacities. Convincing residents to give up their cars and use public transport is the most effective way in reducing congestion; however, even with sufficient public transport capacity, the lack of last-mile (from the transport hub to the destination) travel services is the major deterrent for the adoption of public transport. Due to the dynamic nature of such travel demands, fixed-size fleets will …

Lagrangian Relaxation For Large-Scale Multi-Agent Planning, Geoff Gordon, Pradeep Varakantham, William Yeoh, Hoong Chuin Lau, Shih-Fen Cheng

Research Collection School Of Computing and Information Systems

Multi-agent planning is a well-studied problem with various applications including disaster rescue, urban transportation and logistics, both for autonomous agents and for decision support to humans. Due to computational constraints, existing research typically focuses on one of two scenarios: unstructured domains with many agents where we are content with heuristic solutions, or domains with small numbers of agents or special structure where we can provide provably near-optimal solutions. By contrast, in this paper, we focus on providing provably near-optimal solutions for domains with large numbers of agents, by exploiting a common domain-general property: if individual agents each have limited influence …

Knowledge-Driven Autonomous Commodity Trading Advisor, Yee Pin Lim, Shih-Fen Cheng

Research Collection School Of Computing and Information Systems

The myth that financial trading is an art has been mostly destroyed in the recent decade due to the proliferation of algorithmic trading. In equity markets, algorithmic trading has already bypass human traders in terms of traded volume. This trend seems to be irreversible, and other asset classes are also quickly becoming dominated by the machine traders. However, for asset that requires deeper understanding of physicality, like the trading of commodities, human traders still have significant edge over machines. The primary advantage of human traders in such market is the qualitative expert knowledge that requires traders to consider not just …

A Flexible Mixed Integer Programming Framework For Nurse Scheduling, Murphy Choy, Michelle L. F. Cheong

Research Collection School Of Computing and Information Systems

In this paper, a nurse-scheduling model is developed using mixed integer programming model. It is deployed to a general care ward to replace and automate the current manual approach for scheduling. The developed model differs from other similar studies in that it optimizes both hospitals requirement as well as nurse preferences by allowing flexibility in the transfer of nurses from different duties. The model also incorporated additional policies which are part of the hospitals requirement but not part of the legislations. Hospitals key primary mission is to ensure continuous ward care service with appropriate number of nursing staffs and the …

The Factors Behind A Successful Implementation Of Electronic Health Records Systems, Anjee Gorkhali

Engineering Management & Systems Engineering Theses & Dissertations

This research explores the role that budget for Information System (IS) and technical expertise of healthcare service provider staff play on the successful leap from a partial to exhaustive implementation of Electronic Health Records (EHR) Systems. Technical expertise in Information Systems might not be easily measurable directly, but there are a number of indicators that could be used as a proxy, such as: Information System (IS) Department Budget, number of IS staff and the extent of technical trainings provided by the IS department to the clinical staff. This research study hypothesizes that quality technical trainings conducted by an IS department …

Locating And Protecting Facilities Subject To Random Disruptions And Attacks, Hugh Medal

Graduate Theses and Dissertations

Recent events such as the 2011 Tohoku earthquake and tsunami in Japan have revealed the vulnerability of networks such as supply chains to disruptive events. In particular, it has become apparent that the failure of a few elements of an infrastructure system can cause a system-wide disruption. Thus, it is important to learn more about which elements of infrastructure systems are most critical and how to protect an infrastructure system from the effects of a disruption. This dissertation seeks to enhance the understanding of how to design and protect networked infrastructure systems from disruptions by developing new mathematical models and …

Bidder Behaviors In Repeated B2b Procurement Auctions, Jong Han Park, Jae Kyu Lee, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

B2B auctions play a key role in a firm's procurement process. Even though it is known that repetition is a key characteristic of procurement auctions, traditional auctioneers typically have not put in place a suitable mechanism that supports repetitive auctions effectively. In this paper, we empirically investigate what has taken place in repeated procurement auctions based on real world data from a major outsourcing company of MRO (Maintenance, Repair and Operations) items in Korea. From this empirical study, we discovered the followings. First, we discovered that the repeated bidders contribute majority of all bids, and that the number of new …

Toward Large-Scale Agent Guidance In An Urban Taxi Service, Agussurja Lucas, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Empty taxi cruising represents a wastage of resources in the context of urban taxi services. In this work, we seek to minimize such wastage. An analysis of a large trace of taxi operations reveals that the services’ inefficiency is caused by drivers’ greedy cruising behavior. We model the existing system as a continuous time Markov chain. To address the problem, we propose that each taxi be equipped with an intelligent agent that will guide the driver when cruising for passengers. Then, drawing from AI literature on multiagent planning, we explore two possible ways to compute such guidance. The first formulation …

Dynamic Stochastic Orienteering Problems For Risk-Aware Applications, Hoong Chuin Lau, William Yeoh, Pradeep Varakantham, Duc Thien Nguyen

Research Collection School Of Computing and Information Systems

Orienteering problems (OPs) are a variant of the well-known prize-collecting traveling salesman problem, where the salesman needs to choose a subset of cities to visit within a given deadline. OPs and their extensions with stochastic travel times (SOPs) have been used to model vehicle routing problems and tourist trip design problems. However, they suffer from two limitations travel times between cities are assumed to be time independent and the route provided is independent of the risk preference (with respect to violating the deadline) of the user. To address these issues, we make the following contributions: We introduce (1) a dynamic …

Uncertain Congestion Games With Assorted Human Agent Populations, Asrar Ahmed, Pradeep Reddy Varakantham, Shih-Fen Cheng

Research Collection School Of Computing and Information Systems

Congestion games model a wide variety of real-world resource congestion problems, such as selfish network routing, traffic route guidance in congested areas, taxi fleet optimization and crowd movement in busy areas. However, existing research in congestion games assumes: (a) deterministic movement of agents between resources; and (b) perfect rationality (i.e. maximizing their own expected value) of all agents. Such assumptions are not reasonable in dynamic domains where decision support has to be provided to humans. For instance, in optimizing the performance of a taxi fleet serving a city, movement of taxis can be involuntary or nondeterministic (decided by the specific …

The Patrol Scheduling Problem, Hoong Chuin Lau, Aldy Gunawan

Research Collection School Of Computing and Information Systems

This paper presents the problem of scheduling security teams to patrol a mass rapid transit rail network of a large urban city. The main objective of patrol scheduling is to deploy security teams to stations at varying time periods of the network subject to rostering as well as security-related constraints. We present a mathematical programming model for this problem. We then discuss the aspect of injecting randomness by varying the start times, the break times for each team as well as the number of visits required for each station according to their reported vulnerability. Finally, we present results for the …

Generating Minimal T-Wise Test Suites, Luis C. Gutierrez, Carlos Nieto, Francisco Zapata, Martine Ceberio

COURI Symposium Abstracts, Summer 2012

As the use of computing devices increases every day, users rely on the adequate functioning of software. When software is not tested properly, it can yield erroneous information or a complete failure of the system. The NIST estimates that defective software cost the United States economy close to $60 billion a year. Therefore, there is a need to develop software testing techniques that are time and cost effective. Fully testing software under all possible combinations of parameters values cannot be reduced. However, testing can focus on covering all combinations of subsets of parameters and empirical data shows that doing so …

Using Modeling And Simulation To Examine The Benefits Of A Network Tasking Order, Matthew D. Compton, Kenneth M. Hopkinson, Gilbert L. Peterson, James T. Moore

Faculty Publications

The Global Information Grid (GIG) is the military’s computer and communications network which supports the myriad of military missions. Military missions are highly planned, passing through many hands in the strategy-to-task methodology to ensure completeness, accuracy, coordination, cohesion, and appropriateness. A benefit of this planning is the possibility to collect knowledge of future conditions that could be of use to network designers whose goals include optimizing and protecting the GIG. This advanced knowledge includes which networked military equipment will be involved, what their capabilities are, where they will be, when they will be there, and particulars on the required data …

Design And Analysis Of A Dynamically Configured Log-Based Distributed Security Event Detection Methodology, Michael R. Grimaila, Justin M. Myers, Robert F. Mills, Gilbert L. Peterson

Faculty Publications

Military and defense organizations rely upon the security of data stored in, and communicated through, their cyber infrastructure to fulfill their mission objectives. It is essential to identify threats to the cyber infrastructure in a timely manner, so that mission risks can be recognized and mitigated. Centralized event logging and correlation is a proven method for identifying threats to cyber resources. However, centralized event logging is inflexible and does not scale well, because it consumes excessive network bandwidth and imposes significant storage and processing requirements on the central event log server. In this paper, we present a flexible, distributed event …

Incorporating Memory And Learning Mechanisms Into Meta-Raps, Arif Arin

Engineering Management & Systems Engineering Theses & Dissertations

Due to the rapid increase of dimensions and complexity of real life problems, it has become more difficult to find optimal solutions using only exact mathematical methods. The need to find near-optimal solutions in an acceptable amount of time is a challenge when developing more sophisticated approaches. A proper answer to this challenge can be through the implementation of metaheuristic approaches. However, a more powerful answer might be reached by incorporating intelligence into metaheuristics.

Meta-RaPS (Metaheuristic for Randomized Priority Search) is a metaheuristic that creates high quality solutions for discrete optimization problems. It is proposed that incorporating memory and learning …

Decision Support For Agent Populations In Uncertain And Congested Environments, Pradeep Reddy Varakantham, Shih-Fen Cheng, Geoff Gordon, Asrar Ahmed

Research Collection School Of Computing and Information Systems

This research is motivated by large scale problems in urban transportation and labor mobility where there is congestion for resources and uncertainty in movement. In such domains, even though the individual agents do not have an identity of their own and do not explicitly interact with other agents, they effect other agents. While there has been much research in handling such implicit effects, it has primarily assumed deterministic movements of agents. We address the issue of decision support for individual agents that are identical and have involuntary movements in dynamic environments. For instance, in a taxi fleet serving a city, …

Logistics Orchestration Modeling And Evaluation For Humanitarian Relief, Hoong Chuin Lau, Zhengping Li, Xin Du, Heng Jiang, Robert De Souza

Research Collection School Of Computing and Information Systems

This paper proposes an orchestration model for post-disaster response that is aimed at automating the coordination of scarce resources that minimizes the loss of human lives. In our setting, different teams are treated as agents and their activities are "orchestrated" to optimize rescue performance. Results from simulation are analysed to evaluate the performance of the optimization model.

Lagrangian Relaxation For Large-Scale Multi-Agent Planning, Geoff Gordon, Pradeep Reddy Varakantham, William Yeoh, Ajay Srinivasan, Hoong Chuin Lau, Shih-Fen Cheng

Research Collection School Of Computing and Information Systems

Multi-agent planning is a well-studied problem with applications in various areas. Due to computational constraints, existing research typically focuses either on unstructured domains with many agents, where we are content with heuristic solutions, or domains with small numbers of agents or special structure, where we can find provably near-optimal solutions. In contrast, here we focus on provably near-optimal solutions in domains with many agents, by exploiting influence limits. To that end, we make two key contributions: (a) an algorithm, based on Lagrangian relaxation and randomized rounding, for solving multi-agent planning problems represented as large mixed-integer programs; (b) a proof of …

Prioritized Shaping Of Models For Solving Dec-Pomdps, Pradeep Reddy Varakantham, William Yeoh, Prasanna Velagapudi, Paul Scerri

Research Collection School Of Computing and Information Systems

An interesting class of multi-agent POMDP planning problems can be solved by having agents iteratively solve individual POMDPs, find interactions with other individual plans, shape their transition and reward functions to encourage good interactions and discourage bad ones and then recompute a new plan. D-TREMOR showed that this approach can allow distributed planning for hundreds of agents. However, the quality and speed of the planning process depends on the prioritization scheme used. Lower priority agents shape their models with respect to the models of higher priority agents. In this paper, we introduce a new prioritization scheme that is guaranteed to …

Delayed Observation Planning In Partially Observable Domains, Pradeep Reddy Varakantham, Janusz Marecki

Research Collection School Of Computing and Information Systems

Traditional models for planning under uncertainty such as Markov Decision Processes (MDPs) or Partially Observable MDPs (POMDPs) assume that the observations about the results of agent actions are instantly available to the agent. In so doing, they are no longer applicable to domains where observations are received with delays caused by temporary unavailability of information (e.g. delayed response of the market to a new product). To that end, we make the following key contributions towards solving Delayed observation POMDPs (D-POMDPs): (i) We first provide an parameterized approximate algorithm for solving D-POMDPs efficiently, with desired accuracy; and (ii) We then propose …

Stochastic Dominance In Stochastic Dcops For Risk-Sensitive Applications, Nguyen Duc Thien, William Yeoh, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Distributed constraint optimization problems (DCOPs) are well-suited for modeling multi-agent coordination problems where the primary interactions are between local subsets of agents. However, one limitation of DCOPs is the assumption that the constraint rewards are without uncertainty. Researchers have thus extended DCOPs to Stochastic DCOPs (SDCOPs), where rewards are sampled from known probability distribution reward functions, and introduced algorithms to find solutions with the largest expected reward. Unfortunately, such a solution might be very risky, that is, very likely to result in a poor reward. Thus, in this paper, we make three contributions: (1) we propose a stricter objective for …

College Of Engineering Senior Design Competition Spring 2012, University Of Nevada, Las Vegas

Fred and Harriet Cox Senior Design Competition Projects

Senior Design Experience

Part of every UNLV engineering student’s academic experience, the Senior Design project stimulates engineering innovation and entrepreneurship. Each student in their senior year chooses, plans, designs and prototypes a product in this required element of the curriculum. Working in teams, the senior design project encourages students to use everything learned in the engineering and computer design programs to create a practical, real world solution to an engineering challenge.

Beyond the classroom...

Because of the requirement to work in teams, students also build good communication skills, presentation skills and even business writing skills. They also have to source …

Generating Minimal Pair-Wise Covering Test Suites, Luis C. Gutierrez ^, Martine Ceberio *

COURI Symposium Abstracts, Spring 2012

Software is ubiquitous and needs to be reliable. Software testing therefore plays an important role in software development. Proper testing a software system informs about its quality and reliability so as to prevent unexpected behavior during system execution. One of the methods to prevent failures consists in testing a system under different input values, but when all possible input values are tested, an impractical number of test cases might result. In software testing, pair-wise testing is a combinatorial technique which uses combination of pair input values to generate test cases. Using pair-wise testing dramatically reduces the number of test cases, …

Message Passing Algorithms For Map Estimation Using Dc Programming, Akshat Kumar, Shlomo Zilberstein, Marc Toussaint

Research Collection School Of Computing and Information Systems

We address the problem of finding the most likely assignment or MAP estimation in a Markov random field. We analyze the linear programming formulation of MAP through the lens of difference of convex functions (DC) programming, and use the concave-convex procedure (CCCP) to develop efficient message-passing solvers. The resulting algorithms are guaranteed to converge to a global optimum of the well-studied local polytope, an outer bound on the MAP marginal polytope. To tighten the outer bound, we show how to combine it with the mean-field based inner bound and, again, solve it using CCCP. We also identify a useful relationship …

Analysis Of The Impact Of Data Normalization On Cyber Event Correlation Query Performance, Smile T. Ludovice

Theses and Dissertations

A critical capability required in the operation of cyberspace is the ability to maintain situational awareness of the status of the infrastructure elements that constitute cyberspace. Event logs from cyber devices can yield significant information, and when properly utilized they can provide timely situational awareness about the state of the cyber infrastructure. In addition, proper Information Assurance requires the validation and verification of the integrity of results generated by a commercial log analysis tool. Event log analysis can be performed using relational databases. To enhance database query performance, previous literatures affirm denormalization of databases. Yet database normalization can also increase …

Hierarchical Fuzzy Logic System For Implementing Maintenance Schedules Of Offshore Power Systems, C. S. Chang, Zhaoxia Wang, Fan Yang, W. W. Tan

Research Collection School Of Computing and Information Systems

Smart grid provides the technology for modernizing electricity delivery systems by using distributed and computer-based remote sensing, control and automation, and two-way communications. Potential benefits of the technology are that the smart grid's central control will now be able to control and operate many remote power plant, optimize the overall asset utilization and operational efficiently. In this paper, we propose an innovative approach for the smart grid to handle uncertainties arising from condition monitoring and maintenance of power plant. The approach uses an adaptive maintenance advisor and a system-maintenance optimizer for designing/implementing optimized condition-based maintenance activities, and collectively handles operational …

A Framework For Personalized Dynamic Cross-Selling In E-Commerce Retailing, Arun K. Timalsina

Wayne State University Dissertations

Cross-selling and product bundling are prevalent strategies in the retail sector. Instead of static bundling offers, i.e. giving the same offer to everyone, personalized dynamic cross-selling generates targeted bundle offers and can help maximize revenues and profits. In resolving the two basic problems of dynamic cross-selling, which involves selecting the right complementary products and optimizing the discount, the issue of computational complexity becomes central as the customer base and length of the product list grows. Traditional recommender systems are built upon simple collaborative filtering techniques, which exploit the informational cues gained from users in the form of product ratings and …

Decision Rule Induction For Service Sector Using Data Mining- A Rough Set Theory Approach, Zhonghua Hu

Open Access Theses & Dissertations

Nowadays, data mining is more widely used than ever before; not only by the academic area, but also in the industry and business area. Apart from execution of business processes, the creation of knowledge base and its utilization for the benefit of the organization is becoming a strategy tool to compete. Despite of having ever growing data bases, the problem is that the finance company fails to fully capitalize the true benefits which can be gained from this great wealth of information. The data mining technology instead of classic statistical analysis is developed to help the people to discover the …

Robust Execution Strategy For Scheduling Under Uncertainity, Na Fu

Dissertations and Theses Collection (Open Access)

Resource Constrained Project Scheduling Problems with minimum and maximum time lags (RCPSP/max) provides a general model for resource scheduling in many real-world problems (such as manufacturing and construction engineering). Due to its practical importance and generality, providing effective algorithms and scalable solutions for RCPSP/max is a topic of growing research. Traditional methods have addressed deterministic models with all parameters known with certainty. In this thesis, we are concerned with RCPSP/max problems in an uncertain environment where durations of activities are stochastic and resource availabilities are subject to unforeseen breakdowns. We propose methods for generating robust execution strategy to protect against …