Physical Sciences and Mathematics Commons^™

Logistics Network Design With Differentiated Delivery Lead Time: A Chemical Industry Case Study, Michelle Lee Fong Cheong, Rohit Bhatnagar, Stephen C. Graves

Research Collection School Of Computing and Information Systems

Most logistics network design models assume exogenous customer demand that is independent of the service time or level. This paper examines the benefits of segmenting demand according to lead-time sensitivity of customers. To capture lead-time sensitivity in the network design model, we use a facility grouping method to ensure that the different demand classes are satisfied on time. In addition, we perform a series of computational experiments to develop a set of managerial insights for the network design decision making process.

A Two-Level Framework For Coalition Formation Via Optimization And Agent Negotiation, Hoong Chuin Lau, Lei Zhang

Research Collection School Of Computing and Information Systems

We present a two-level coalition formation approach based on a centralized optimization model on the upper level, and a distributed agent-negotiation model on the lower level. This approach allows us to balance agent self-interests against a high joint utility. Experimental results show that the two-level coalition formation mechanism will increase not only the overall utility of the coalition, but also the individual utility of most participating agents. The results also suggest it is better for the agents to be partially cooperative rather than either fully cooperative or self-interested in our setting.

Towards Personalised Web Intelligence, Ah-Hwee Tan, Hwee-Leng Ong, Hong Pan, Jamie Ng, Qiu-Xiang Li

Research Collection School Of Computing and Information Systems

The Flexible Organizer for Competitive Intelligence (FOCI) is a personalised web intelligence system that provides an integrated platform for gathering, organising, tracking, and disseminating competitive information on the web. FOCI builds personalised information portfolios through a novel method called User-Configurable Clustering, which allows a user to personalise his/her portfolios in terms of the content as well as the organisational structure. This paper outlines the key challenges we face in personalised information management and gives a detailed account of FOCI’s underlying personalisation mechanism. For a quantitative evaluation of the system’s performance, we propose a set of performance indices based on information …

A Development Framework For Rapid Metaheuristics Hybridization, Hoong Chuin Lau, M. K. Lim, W. C. Wan, S. Halim

Research Collection School Of Computing and Information Systems

While meta-heuristics are effective for solving large-scale combinatorial optimization problems, they result from time-consuming trial-and-error algorithm design tailored to specific problems. For this reason, a software tool for rapid prototyping of algorithms would save considerable resources. This work presents a generic software framework that reduces development time through abstract classes and software reuse, and more importantly, aids design with support of user-defined strategies and hybridization of meta-heuristics. Most interestingly, we propose a novel way of redefining hybridization with the use of the "request and response" metaphor, which form an abstract concept for hybridization. Different hybridization schemes can now be formed …

Probing The Posthuman: Richard Powers' Galatea 2.2 And The Mind-Body Problem, Miranda Campbell

Reconstruction: Studies in Contemporary Culture

[Editors' Introduction]

In this paper, Miranda Campbell discusses Richard Powers' novel Galatea 2.2 and argues that this work is situated at the intersection of the posthumanist and humanist discourses. Campbell examines Powers' approach to the mind-body problem, his interrogation of the limits and limitations of posthumanism, and its dissolution of the importance of the body, difference, and agency. In the posthuman setting of the Center for Advanced Science of this novel, scientists integrate the mind into the body through its designation as a mechanically functioning brain. At the Center, the binary of human and machine begins to erode with the …

Taking Dcop To The Real World: Efficient Complete Solutions For Distributed Event Scheduling, Rajiv Maheswaran, Milind Tambe, Emma Bowring, Jonathan Pearce, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

Distributed Constraint Optimization (DCOP) is an elegant formalism relevant to many areas in multiagent systems, yet complete algorithms have not been pursued for real world applications due to perceived complexity. To capably capture a rich class of complex problem domains, we introduce the Distributed Multi-Event Scheduling (DiMES) framework and design congruent DCOP formulations with binary constraints which are proven to yield the optimal solution. To approach real-world efficiency requirements, we obtain immense speedups by improving communication structure and precomputing best case bounds. Heuristics for generating better communication structures and calculating bound in a distributed manner are provided and tested on …

Notes On Equilibria In Symmetric Games, Shih-Fen Cheng, Daniel M. Reeves, Yevgeniy Vorobeychik, Michael P. Wellman

Research Collection School Of Computing and Information Systems

In a symmetric game, every player is identical with respect to the game rules. We show that a symmetric 2strategy game must have a pure-strategy Nash equilibrium. We also discuss Nash’s original paper and its generalized notion of symmetry in games. As a special case of Nash’s theorem, any finite symmetric game has a symmetric Nash equilibrium. Furthermore, symmetric infinite games with compact, convex strategy spaces and continuous, quasiconcave utility functions have symmetric pure-strategy Nash equilibria. Finally, we discuss how to exploit symmetry for more efficient methods of finding Nash equilibria.

Review Of The Product Development Process And Information Flow In The Manufacturing Industry: Problems And A Possible Wav Forward, E Opiyo

Tanzania Journal of Engineering and Technology (TJET)

No abstract provided.

Tournament Versus Fitness Uniform Selection, Shane Legg, Marcus Hutter, Akshat Kumar

Research Collection School Of Computing and Information Systems

In evolutionary algorithms a critical parameter that must be tuned is that of selection pressure. If it is set too low then the rate of convergence towards the optimum is likely to be slow. Alternatively if the selection pressure is set too high the system is likely to become stuck in a local optimum due to a loss of diversity in the population. The recent Fitness Uniform Selection Scheme (FUSS) is a conceptually simple but somewhat radical approach to addressing this problem - rather than biasing the selection towards higher fitness, FUSS biases selection towards sparsely populated fitness levels. In …

Multi-Period Multi-Dimensional Knapsack Problem And Its Application To Available-To-Promise, Hoong Chuin Lau, M. K. Lim

Research Collection School Of Computing and Information Systems

This paper is motivated by a recent trend in logistics scheduling, called Available-to-Promise. We model this problem as the multi-period multi-dimensional knapsack problem. We provide some properties for a special case of a single-dimensional problem. Based on insights obtained from these properties, we propose a two-phase heuristics for solving the multi-dimensional problem. We also propose a novel time-based ant colony optimization algorithm. The quality of the solutions generated is verified through experiments, where we demonstrate that the computational time is superior compared with integer programming to achieve solutions that are within a small percentage of the upper bounds.

Cognitive Robot Mapping With Polylines And An Absolute Space Representation, Kennard R. Laviers, Gilbert L. Peterson

Faculty Publications

Robot mapping even today is one of the most challenging problems in robot programming. Most successful methods use some form of occupancy grid to represent a mapped region. This approach becomes problematic if the robot is mapping a large environment, the map quickly becomes too large for processing and storage. Rather than storing the map as an occupancy grid, our robot (equipped with sonars) sees the world as a series of connected spaces. These spaces are initially mapped as an occupancy grid in a room by room fashion. As the robot leaves a space, denoted by passing through a doorway, …

Development Approaches Coupled With Verification And Validation Methodologies For Agent-Based Mission-Level Analytical Combat Simulations, Lance E. Champagne

Theses and Dissertations

This research investigated the applicability of agent-based combat simulations to real-world combat operations. An agent-based simulation of the Allied offensive search for German U-Boats in the Bay of Biscay during World War II was constructed, extending the state-of-the-art in agent-based combat simulations, bridging the gap between the current level of agent-like combat simulations and the concept of agent-based simulations found in the broader literature. The proposed simulation advances agent-based combat simulations to “validateable” mission-level military operations. Simulation validation is a complex task with numerous, diverse techniques available and levels of validation differing significantly among simulations and applications. This research presents …

Concurrent Cognitive Mapping And Localization Using Expectation Maximization, Kennard R. Laviers

Theses and Dissertations

Robot mapping remains one of the most challenging problems in robot programming. Most successful methods use some form of occupancy grid for representing a mapped region. An occupancy grid is a two dimensional array in which the array cells represents (x,y) coordinates of a cartesian map. This approach becomes problematic in mapping large environments as the map quickly becomes too large for processing and storage. Rather than storing the map as an occupancy grid, our robot (equipped with ultrasonic sonars) views the world as a series of connected spaces. These spaces are initially mapped as an occupancy grid in a …

Integrating Perception, Language And Problem Solving In A Cognitive Agent For A Mobile Robot., Deryle W. Lonsdale, D. Paul Benjamin, Damian M. Lyons

Faculty Publications

We are implementing a unified cognitive architecture for a mobile robot. Our goal is to endow a robot agent with the full range of cognitive abilities, including perception, use of natural language, learning and the ability to solve complex problems. The perspective of this work is that an architecture based on a unified theory of robot cognition has the best chance of attaining human-level performance.

This agent architecture is an integration of three theories: a theory of cognition embodied in the Soar system, the RS formal model of sensorimotor activity and an algebraic theory of decomposition and reformulation.

These three …

Investigation Of Implementation Techniques For Backpropagation Neural Networks, John Culloty

Theses

Artificial neural networks are biologically inspired computational methods that have the ability to approximate discrete, real and vector valued target functions. For some problem domains this ability makes neural networks a more appealing solution than traditional computational techniques. Such problem domains typically contain a large number of parameters that are interrelated in a complex and often unknown manner. This makes rule based solutions all but impossible. However another feature of such problem domains is the presence of large volumes of real world data that can be used to tram a neural network until it learns the solution.

One of the …

Logistics Outsourcing And 3pl Challenges, Michelle L. F. Cheong

Research Collection School Of Computing and Information Systems

Logistics has been an important part of every economy and every business entity. The worldwide trend in globalization has led to many companies outsourcing their logistics function to Third-Party Logistics (3PL) companies, so as to focus on their core competencies. This paper attempts to broadly identify and categorize the challenges faced by 3PL companies and discover potential gaps for future research. Some of the challenges will be related with the experience and information collected from interviews with two 3PL companies.

Pyro: A Python-Based Versatile Programming Environment For Teaching Robotics, D. Blank, D. Kumar, Lisa A. Meeden, H. Yanco

Computer Science Faculty Works

In this article we describe a programming framework called Pyro, which provides a set of abstractions that allows students to write platform-independent robot programs. This project is unique because of its focus on the pedagogical implications of teaching mobile robotics via a top-down approach. We describe the background of the project, its novel abstractions, its library of objects, and the many learning modules that have been created from which curricula for different types of courses can be drawn. Finally, we explore Pyro from the students' perspective in a case study.

Predicting Nonlinear Network Traffic Using Fuzzy Neural Network, Zhaoxia Wang, Tingzhu Hao, Zengqiang Chen, Zhuzhi Yuan

Research Collection School Of Computing and Information Systems

Network traffic is a complex and nonlinear process, which is significantly affected by immeasurable parameters and variables. This paper addresses the use of the five-layer fuzzy neural network (FNN) for predicting the nonlinear network traffic. The structure of this system is introduced in detail. Through training the FNN using back-propagation algorithm with inertia] terms the traffic series can be well predicted by this FNN system. We analyze the performance of the FNN in terms of prediction ability as compared with solely neural network. The simulation demonstrates that the proposed FNN is superior to the solely neural network systems. In addition, …

Task Allocation Via Multi-Agent Coalition Formation: Taxonomy, Algorithms And Complexity, Hoong Chuin Lau, L. Zhang

Research Collection School Of Computing and Information Systems

Coalition formation has become a key topic in multiagent research. In this paper, we propose a preliminary classification for the coalition formation problem based on three driving factors (demands, resources and profit objectives). We divide our analysis into 5 cases. For each case, we present algorithms and complexity results. We anticipate that with future research, this classification can be extended in similar fashion to the comprehensive classification for the job scheduling problem.

A Computer-Based Articulation Training Aid For Short Words (Cata), Mukund Devarajan

Electrical & Computer Engineering Theses & Dissertations

Several improvements in the vowel articulation training aid (VATA) are described, as well as the efforts to extend the visual feedback system to operate with short words in the form of consonant, vowel and consonant (CVC). The extended version of the visual feedback system is referred to as CATA (Computer-based Articulation Training Aid); the vowel version of the aid (VATA) only operates with ten American English monopthong vowels. Improvements in VATA include the use of a neural network (NN) recognizer method to prune a large database of vowel recordings to eliminate noisy and/or mispronounced tokens. The spectral jitter problem, previously …

Safe Robot Driving In Cluttered Environments, Chuck Thorpe, Justin Carlson, Dave Duggins, Jay Gowdy, Rob Maclachlan, Christoph Mertz, Arne Suppe, Bob Wang

Research Collection School Of Computing and Information Systems

The Navlab group at Carnegie Mellon University has a long history of development of automated vehicles and intelligent systems for driver assistance. The earlier work of the group concentrated on road following, cross-country driving, and obstacle detection. The new focus is on short-range sensing, to look all around the vehicle for safe driving. The current system uses video sensing, laser rangefinders, a novel light-stripe rangefinder, software to process each sensor individually, and a map-based fusion system. The complete system has been demonstrated on the Navlab 11 vehicle for monitoring the environment of a vehicle driving through a cluttered urban environment, …

Multi-Agent Coalition Via Autonomous Price Negotiation In A Real-Time Web Environment, Hoong Chuin Lau, Wei Sian Lim

Research Collection School Of Computing and Information Systems

In e-marketplaces, customers specify job requests in real-time and agents form coalitions to service them. This paper proposes a protocol for self-interested agents to negotiate prices in forming successful coalitions. We propose and experiment with two negotiation schemes: one allows information sharing while the other does not.

Solving Multi-Objective Multi-Constrained Optimization Problems Using Hybrid Ants System And Tabu Search, Hoong Chuin Lau, Min Kwang Lim, Wee Chong Wan, Hui Wang, Xiaotao Wu

Research Collection School Of Computing and Information Systems

Many real-world optimization problems today are multi-objective multi-constraint generalizations of NP-hard problems. A classic case we study in this paper is the Inventory Routing Problem with Time Windows (IRPTW). IRPTW considers inventory costs across multiple instances of Vehicle Routing Problem with Time Windows (VRPTW). The latter is in turn extended with time-windows constraints from the Vehicle Routing Problem (VRP), which is extended with optimal fleet size objective from the single-objective Traveling Salesman Problem (TSP). While single-objective problems like TSP are solved effectively using meta-heuristics, it is not obvious how to cope with the increasing complexity systematically as the problem is …

A Generic Object-Oriented Tabu Search Framework, Hoong Chuin Lau, Wee Chong Wan, Xiaomin Jia

Research Collection School Of Computing and 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 welldesigned 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 is …

A Generic Object-Oriented Tabu Search Framework, Hoong Chuin Lau

Research Collection School Of Computing and 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 welldesigned 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 is …

On Machine Learning Methods For Chinese Document Classification, Ji He, Ah-Hwee Tan, Chew-Lim Tan

Research Collection School Of Computing and Information Systems

This paper reports our comparative evaluation of three machine learning methods, namely k Nearest Neighbor (kNN), Support Vector Machines (SVM), and Adaptive Resonance Associative Map (ARAM) for Chinese document categorization. Based on two Chinese corpora, a series of controlled experiments evaluated their learning capabilities and efficiency in mining text classification knowledge. Benchmark experiments showed that their predictive performance were roughly comparable, especially on clean and well organized data sets. While kNN and ARAM yield better performances than SVM on small and clean data sets, SVM and ARAM significantly outperformed kNN on noisy data. Comparing efficiency, kNN was notably more costly …

Machine Learning Approaches For Determining Effective Seeds For K -Means Algorithm, Kaveephong Lertwachara

Doctoral Dissertations

In this study, I investigate and conduct an experiment on two-stage clustering procedures, hybrid models in simulated environments where conditions such as collinearity problems and cluster structures are controlled, and in real-life problems where conditions are not controlled. The first hybrid model (NK) is an integration between a neural network (NN) and the k-means algorithm (KM) where NN screens seeds and passes them to KM. The second hybrid (GK) uses a genetic algorithm (GA) instead of the neural network. Both NN and GA used in this study are in their simplest-possible forms.

In the simulated data sets, I investigate two …

Automatic Speaker Identification Using Reusable And Retrainable Binary-Pair Partitioned Neural Networks, Ashutosh Mishra

Electrical & Computer Engineering Theses & Dissertations

This thesis presents an extension of the work previously done on speaker identification using Binary Pair Partitioned (BPP) neural networks. In the previous work, a separate network was used for each pair of speakers in the speaker population. Although the basic BPP approach did perform well and had a simple underlying algorithm, it had the obvious disadvantage of requiring an extremely large number of networks for speaker identification with large speaker populations. It also requires training of networks proportional to the square of the number of speakers under consideration, leading to a very large number of networks to be trained …

Pid Stabilization Of A Position-Controlled Robot Manipulator Acting Independently Of In Collaboration With Human Arm, Anindo Roy, Kamran Iqbal

Journal of the Arkansas Academy of Science

In this paper we develop framework for PID stabilization of a robot manipulator when using an object independently or in collaboration with a human arm. In both applications, the manipulator is equipped with a wrist sensor represented by an impedance. A second order manipulator transfer function along each coordinate direction is assumed. The aim of the paper is to design a PID controller when measurement of contact force, available via wrist sensor, is used to command the position controlled manipulator to a desired position and/or force profile. Necessary and sufficient conditions for stability of the closed loop system are developed …

A Neural Network Method For Protein Classification, Arie D. Jones

All-Inclusive List of Electronic Theses and Dissertations

The investigation detailed in this paper attempts to utilize a Leaming Vector Quantization network in order to classify a set of mitochondrial proteins based upon their amino acid sequence. The Learning Vector Quantization network uses a nearest neighbor approach to classification. Input vectors are fed into the network, which produces output vectors. Those output vectors are then matched by means of a distance bias to a corresponding classification vector. The learning and test sets consisted of thirteen similar mitochodrial proteins from seventy-two different species. This provided a pool of over nine hundred proteins to use. Half of the species were …