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Full-Text Articles in Engineering

Optimization Models And Algorithms For Demand Response In Smart Grid., Guangyang Xu Dec 2016

Optimization Models And Algorithms For Demand Response In Smart Grid., Guangyang Xu

Electronic Theses and Dissertations

For demand response in smart grid, a utility company wants to minimize total electricity cost and end users want to maximize their own utility. The latter is considered to consist of two parts in this research: electricity cost and convenience/comfort. We first develop a system optimal (SO) model and a user equilibrium (UE) model for the utility company and end users, respectively and compare the difference of the two. We consider users' possible preference on convenience over cost-saving under the real-time pricing in smart grid, and each user is assumed to have a preferred time window for using a particular …


Traffic Simulation Model For Port Planning And Congestion Prevention, Baoxiang Li, Kar Way Tan, Trong Khiem Tran Dec 2016

Traffic Simulation Model For Port Planning And Congestion Prevention, Baoxiang Li, Kar Way Tan, Trong Khiem Tran

Research Collection School Of Computing and Information Systems

Effective management of land-side transportation provides the competitive advantage to port terminal operators in improving services and efficient use of limited space in an urban port. We present a hybrid simulation model that combines traffic-flow modeling and discrete-event simulation for land-side port planning and evaluation of traffic conditions for a number of what-if scenarios. We design our model based on a real-world case of a bulk cargo port. The problem is interesting due to complexity of heterogeneous closed-looped internal vehicles and external vehicles traveling in spaces with very limited traffic regulation (no traffic lights, no traffic wardens) and the traffic …


Order Picking Strategies For Healthcare Warehouses., Ehsan Khodabandeh Dec 2016

Order Picking Strategies For Healthcare Warehouses., Ehsan Khodabandeh

Electronic Theses and Dissertations

Order picking is the process of collecting goods and items in specified quantities from storage locations, in response to customer orders. Since many labor resources are involved in this process, finding ways to make it more efficient have been a primary goal for researchers and practitioners. Determining a better allocation of products to the storage areas, finding the best route and sequence to pick multiple products, and choosing the best picking policies to minimize congestion in the aisles are just a few of many objectives regarding order picking process. Due to regulatory compliances and the chance of product spoilage, additional …


Improving Carbon Efficiency Through Container Size Optimization And Shipment Consolidation, Nang Laik Ma, Kar Way Tan, Edwin Lik Ming Chong Sep 2016

Improving Carbon Efficiency Through Container Size Optimization And Shipment Consolidation, Nang Laik Ma, Kar Way Tan, Edwin Lik Ming Chong

Research Collection School Of Computing and Information Systems

Purpose: Many manufacturing companies that ship goods through full container loads found themselves under-utilizing the containers and resulting in higher carbon footprint per volume shipment. One of the reasons is the choice of non-ideal container sizes for their shipments. Consolidation fills up the containers more efficiently that reduces the overall carbon footprint. The objective of this paper is to support decisions on selection of appropriate combination of container sizes and shipment consolidation for a manufacturing company. We develop two-steps model which first takes the volumes to be shipped as an input and provide the combination of container sizes required; then …


Efficient Employment Of Large Format Sensor Data Transfer Architectures, Jeffrey R. Oltmanns Jun 2016

Efficient Employment Of Large Format Sensor Data Transfer Architectures, Jeffrey R. Oltmanns

Theses and Dissertations

Due to the increasing quantity of data collected by Air Force intelligence, surveillance and reconnaissance (ISR) assets and the focus on timely access to the data collected by these systems, operational data transfer network architectures have become a critical component of their employment in the intelligence production process. Efficient utilization of the provided long-haul communications component of the ISR system improves the value of the single asset to the warfighter and enables connectivity of additional assets via the data transfer network architecture. This research effort focused on the creation and implementation of a structured test design methodology based on the …


Soto's True Earth Market Optimization, Hironari Fujita, Wei Lin Luong, Sean Macwilliams Jun 2016

Soto's True Earth Market Optimization, Hironari Fujita, Wei Lin Luong, Sean Macwilliams

Industrial and Manufacturing Engineering

Soto’s True Earth Market is a new organic market startup which is located in a historical facility in the small town of Cambria. The new owner of Soto’s Andre Ponce has a vision to create a community revolved around local organic foods and sustainability. Since Soto’s is still in the initial startup phase there is a large amount of room for optimization and redesign in order to create a solid customer foundation. Andre presented several opportunities for improvement to the team. With a time constraint of solely two quarters the project team decided to provide the following:

● Old and …


Self-Organizing Neural Network For Adaptive Operator Selection In Evolutionary Search, Teck Hou Teng, Stephanus Daniel Handoko, Hoong Chuin Lau Jun 2016

Self-Organizing Neural Network For Adaptive Operator Selection In Evolutionary Search, Teck Hou Teng, Stephanus Daniel Handoko, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Evolutionary Algorithm is a well-known meta-heuristics paradigm capable of providing high-quality solutions to computationally hard problems. As with the other meta-heuristics, its performance is often attributed to appropriate design choices such as the choice of crossover operators and some other parameters. In this chapter, we propose a continuous state Markov Decision Process model to select crossover operators based on the states during evolutionary search. We propose to find the operator selection policy efficiently using a self-organizing neural network, which is trained offline using randomly selected training samples. The trained neural network is then verified on test instances not used for …


The Context Of Tool Control In An Aircraft Assembly Environment Related To Productivity, Taylor Jay Sisson May 2016

The Context Of Tool Control In An Aircraft Assembly Environment Related To Productivity, Taylor Jay Sisson

KSU Journey Honors College Capstones and Theses

The aircraft industry focuses a large portion of its resources on tool control during the assembly of aircraft. Tool control is a strict process that demands time from the assembly process. This time is removed from the value-added time spent actually assembling the aircraft. A study at Lockheed Martin conducted in the Spring of 2016 is discussed that examines the time spent on tool control. Tool control is necessary in aircraft assembly to prevent tools from entering compartments of the aircraft. If such an event occurs, the tool may damage the aircraft. All aircraft assembly processes must be tool controlled, …


Optimization Of Rfid System Coverage In A Manufacturing Environment, Scott D. Malatesta May 2016

Optimization Of Rfid System Coverage In A Manufacturing Environment, Scott D. Malatesta

Master's Theses

This paper compiles existing ideas, theories, and experiments across multiple disciplines to provide guidance for a company looking to implement an optimal RFID system in their production facility. The desire is to maximize the information received by the system while minimizing the cost. Four potential layouts of RFID antennas, two with overlapping antenna coverage and two with non-overlapping layouts, are first analyzed to understand the special coverage and the number of antennas required. The value of information is then quantified to determine whether higher coverage layouts are worth the additional costs associated with the higher number of antennas required. It …


Simultaneous Optimization And Sampling Of Agent Trajectories Over A Network, Hala Mostafa, Akshat Kumar, Hoong Chuin Lau May 2016

Simultaneous Optimization And Sampling Of Agent Trajectories Over A Network, Hala Mostafa, Akshat Kumar, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

We study the problem of optimizing the trajectories of agents moving over a network given their preferences over which nodes to visit subject to operational constraints on the network. In our running example, a theme park manager optimizes which attractions to include in a day-pass to maximize the pass’s appeal to visitors while keeping operational costs within budget. The first challenge in this combinatorial optimization problem is that it involves quantities (expected visit frequencies of each attraction) that cannot be expressed analytically, for which we use the Sample Average Approximation. The second challenge is that while sampling is typically done …


Robust Influence Maximization, Meghna Lowalekar, Pradeep Varakantham, Akshat Kumar May 2016

Robust Influence Maximization, Meghna Lowalekar, Pradeep Varakantham, Akshat Kumar

Research Collection School Of Computing and Information Systems

Influence Maximization is the problem of finding a fixed size set of nodes, which will maximize the expected number of influenced nodes in a social network. The number of influenced nodes is dependent on the influence strength of edges that can be very noisy. The noise in the influence strengths can be modeled using a random noise or adversarial noise model. It has been shown that all random processes that independently affect edges of the graph can be absorbed into the activation probabilities themselves and hence random noise can be captured within the independent cascade model. On the other hand, …


Role Of Low Carbon Energy Technologies In Near Term Energy Policy, Olaitan P. Olaleye Mar 2016

Role Of Low Carbon Energy Technologies In Near Term Energy Policy, Olaitan P. Olaleye

Doctoral Dissertations

In the first part of this thesis, we use a multi-model framework to examine a set of possible future energy scenarios resulting from R&D portfolios of Solar, Nuclear, Carbon Capture and Storage (CCS), Bio-Fuels, Bio-Electricity and Batteries for electric transportation. We show that CCS significantly complements Bio-Electricity, while most of the other energy technology pairs are substitutes. From the probabilistic analysis of future energy scenarios we observe that portfolios with CCS tend to stochastically dominate those without CCS; portfolios with only renewables tend to be stochastically dominated by others; and that there are clear decreasing marginal returns to scale. We …


Multi-Level Route-Optimization Computer Application, Ryan Sutardji, Frank Nguyen Mar 2016

Multi-Level Route-Optimization Computer Application, Ryan Sutardji, Frank Nguyen

Industrial and Manufacturing Engineering

This report provides a detailed analysis on how to optimize driving routes by creating a computer application. There are many different route-optimization issues that logistical companies consistently face, as well as many different solutions and algorithms. With technology on the rise, pick-up, delivery, and transportation services are become a huge part of our everyday lives. When optimizing routes, reducing transportation costs by minimizing travel distance is always ideal, but other factors must be considered such as arriving at a location before or after a certain time. Our objective is to optimize driving routes based on travel distance and priorities. We …


Shortest Path Based Decision Making Using Probabilistic Inference, Akshat Kumar Feb 2016

Shortest Path Based Decision Making Using Probabilistic Inference, Akshat Kumar

Research Collection School Of Computing and Information Systems

We present a new perspective on the classical shortest path routing (SPR) problem in graphs. We show that the SPR problem can be recast to that of probabilistic inference in a mixture of simple Bayesian networks. Maximizing the likelihood in this mixture becomes equivalent to solving the SPR problem. We develop the well known Expectation-Maximization (EM) algorithm for the SPR problem that maximizes the likelihood, and show that it does not get stuck in a locally optimal solution. Using the same probabilistic framework, we then address an NP-Hard network design problem where the goal is to repair a network of …


Applications Of Simulation And Optimization Techniques In Optimizing Room And Pillar Mining Systems, Angelina Konadu Anani Jan 2016

Applications Of Simulation And Optimization Techniques In Optimizing Room And Pillar Mining Systems, Angelina Konadu Anani

Doctoral Dissertations

"The goal of this research was to apply simulation and optimization techniques in solving mine design and production sequencing problems in room and pillar mines (R&P). The specific objectives were to: (1) apply Discrete Event Simulation (DES) to determine the optimal width of coal R&P panels under specific mining conditions; (2) investigate if the shuttle car fleet size used to mine a particular panel width is optimal in different segments of the panel; (3) test the hypothesis that binary integer linear programming (BILP) can be used to account for mining risk in R&P long range mine production sequencing; and (4) …


Approximation For Single-Channel Multi-Server Queues And Queuing Networks With Generally Distributed Inter-Arrival And Service Times, Carlos Roberto Chaves Jan 2016

Approximation For Single-Channel Multi-Server Queues And Queuing Networks With Generally Distributed Inter-Arrival And Service Times, Carlos Roberto Chaves

Doctoral Dissertations

"This dissertation is divided into two papers. The first paper is related to developing a closed-form approximation for single-channel multiple-server queues with generally distributed inter-arrival and service times, which are often found in numerous settings, e.g., airports and manufacturing systems. Unfortunately, exact models for such systems require distributions for the underlying random variables. Further, data for fitting distributions is sometimes not available, and one only has access to means and variances of the underlying input random variables. Under heavy traffic, excellent approximations already exist for this purpose. In the first paper, a new approximation method for medium traffic is presented. …