Operations Research, Systems Engineering and Industrial Engineering Commons^™

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 …

Half-Life Learning Curves In The Defense Acquisition Life Cycle, Adedeji B. Badiru

Faculty Publications

Learning curves are useful for assessing performance improvement due to the positive impact of learning. In recent years, the deleterious effects of forgetting have also been recognized. Workers experience forgetting or decline in performance over time. Consequently, contemporary learning curves have attempted to incorporate forgetting components into learning curves. An area of increasing interest is the study of how fast and how far the forgetting impact can influence overall performance. This article introduces the concept of half-life analysis of learning curves using the concept of growth and decay, with particular emphasis on applications in the defense acquisition process. The computational …

Meta-Heuristics Analysis For Technologically Complex Programs: Understanding The Impact Of Total Constraints For Schedule, Quality And Cost, Henry Darrel Webb

EMSE Doctoral Projects

Program management data associated with a technically complex radio frequency electronics base communication system has been collected and analyzed to identify heuristics which may be utilized in addition to existing processes and procedures to provide indicators that a program is trending to failure. Analysis of the collected data includes detailed schedule analysis, detailed earned value management analysis and defect analysis within the framework of a Firm Fixed Price (FFP) incentive fee contract.

This project develops heuristics and provides recommendations for analysis of complex project management efforts such as those discussed herein. The analysis of the effects of the constraints on …

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.

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 …

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 …

Blunt Impact Performance Evaluation Of Helmet Lining Systems For Military And Recreational Use, Jaclyn Siniora, Ryan Taylor, Darren Suey

Industrial Technology and Packaging

With the increasing problem in collegiate athletes experiencing injuries to the brain, different helmet liners where put to the test to see which liner provided athletes the greatest protection under specific conditions.

This senior project evaluates five different liners in football helmets. Each of the helmet liners were tested at three different temperatures: hot, cold, and ambient. Each helmet had seven different impact locations which were put to the test. The project was designed to be used to test ACH military combat liners as well. Due to shipping bottle necks the ACH combat liners have been left to future Cal …

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 …

Colonel Blotto Games And Lancaster's Equations: A Novel Military Modeling Combination, Andrew Collins, Patrick T. Hester

VMASC Publications

Military strategists face a difficult task when engaged in a battle against an adversarial force. They have to predict both what tactics their opponent will employ and the outcomes of any resultant conflicts in order to make the best decision about their actions. Game theory has been the dominant technique used by analysts to investigate the possible actions that an enemy will employ. Traditional game theory can be augmented by use of Lanchester equations, a set of differential equations used to determine the outcome of a conflict. This paper demonstrates a novel combination of game theory and Lanchester equations using …

Neutrosophic Masses & Indeterminate Models Applications To Information Fusion, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

In this paper we introduce the indeterminate models in information fusion, which are due either to the existence of some indeterminate elements in the fusion space or to some indeterminate masses. The best approach for dealing with such models is the neutrosophic logic.

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 …

Go Niche Or Go Home: Influence Maximization In The Presence Of Strong Opponent, Long Foong Liow

Dissertations and Theses Collection (Open Access)

In hotly contested product categories dominated by a few powerful firms, it is quite common for weaker or late entrants to focus only on particular segments of the whole market. The rationale for such strategy is intuitive: to avoid direct confrontation with heavy-weight firms, and to concentrate in segments where these weaker firms have comparative advantages. In marketing, this is what people called “go niche or go home”. The niche-building strategy may rely on “homophily”, which implies that consumers in a particular market segment might possess certain set of attributes that cause them to appreciate certain products better (in other …

Multi-Party Multi-Period Supply Chain Coordination, Thin Yin Leong, Michelle Lee Fong Cheong

Research Collection School Of Computing and Information Systems

We apply combinatorial auction as a coordination mechanism to smooth demands placed on suppliers' limited production capacities, allowing several manufacturers to share common suppliers effectively. Products are bidders bidding for parts from suppliers, consuming their capacities in different time periods. The fourth party logistic (4PL) provider acts as the auctioneer to coordinate bids and perform price iterations. We leverage on the strong links between the Lagrangian relaxation method and combinatorial auction, where the Lagrange multipliers serve as the supply capacity reserve prices, to balance the demand and supply of capacities. To prevent cyclic behaviour and to increase convergence speed, we …

A Sentiment Analysis Of Singapore Presidential Election 2011 Using Twitter Data With Census Correction, Murphy Junyu Choy, Michelle Lee Fong Cheong, Nang Laik Ma, Ping Shung Koo

Research Collection School Of Computing and Information Systems

Sentiment analysis is a new area in text analytics where it focuses on the analysis and understanding of the human emotions from the text patterns. This new form of analysis has been widely adopted in customer relationship management especially in the context of complaint management. However, sentiment analysis using Twitter data has remained extremely difficult to manage due to sampling biasness. In this paper, we will discuss about the application of reweighting techniques in conjunction with online sentiment divisions to predict the vote percentage that individual presidential candidate in Singapore will receive in the Presidential Election 2011. There will be …

Robust Local Search For Solving Rcpsp/Max With Durational Uncertainty, Na Fu, Hoong Chuin Lau, Pradeep Varakantham, Fei Xiao

Research Collection School Of Computing and Information Systems

Scheduling problems in manufacturing, logistics and project management have frequently been modeled using the framework of Resource Constrained Project Scheduling Problems with minimum and maximum time lags (RCPSP/max). Due to the importance of these problems, providing scalable solution schedules for RCPSP/max problems is a topic of extensive research. However, all existing methods for solving RCPSP/max assume that durations of activities are known with certainty, an assumption that does not hold in real world scheduling problems where unexpected external events such as manpower availability, weather changes, etc. lead to delays or advances in completion of activities. Thus, in this paper, our …

Robust Distributed Scheduling Via Time Period Aggregation, Shih-Fen Cheng, John Tajan, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

In this paper, we evaluate whether the robustness of a market mechanism that allocates complementary resources could be improved through the aggregation of time periods in which resources are consumed. In particular, we study a multi-round combinatorial auction that is built on a general equilibrium framework. We adopt the general equilibrium framework and the particular combinatorial auction design from the literature, and we investigate the benefits and the limitation of time-period aggregation when demand-side uncertainties are introduced. By using simulation experiments on a real-life resource allocation problem from a container port, we show that, under stochastic conditions, the performance variation …