Optimization for Urban Mobility Systems

In the recent decades, new modes of transportation have been developed due to urbanization, highly dense population, and technological advancement. As a result, design and operation of urban transportation have become increasingly important to better utilize the resources and efficiently meet demand. This dissertation was motivated by two problems on optimizing design and control of urban transportation. In the first one, we consider a problem of dynamically matching heterogeneous market parcitipants so as to maximize the total number of matching, which was motivated by practices of ride-sharing platforms. In the other problem, we study efficient design of elevator zoning system in high-rises with uncertainty in customer batching.In Chapter 1, we consider a multiperiod stochastic optimization of a market that matches heterogeneous and impatient agents. The model was mainly motivated from carpooling products run by ride-sharing platforms such as Uber and Lyft, and kidney exchange market, where market participants are heterogeneous in terms of how likely they can be matched with others. In the case of a ride-sharing platform, one of the key operational decisions for carpooling is to efficiently match riders and clear the market in a timely manner. In doing so, the platform needs to take into account the heterogeneity of riders in terms of their trip types(e.g origin-destination pair) and different matching compatibility. For example, some customers may request rides within San Francisco, while others may request rides from San Francisco to outside the city. Since picking up and dropping off a customer within the city can be done within relatively short amount of time, those who want to travel within the city can be matched with any other riders for carpooling. However, the destinations of those who want to travel to outside the city may be very different, and in order to maintain customers' additional transit time due to carpooling, it is likely that they can be only matched with those who want to travel within the city. In the case of kidney exchange where market participants arrive in the form of patient-donor pair, pairs with donor who can donate her kidney to most of patients (for example, blood type O) and patient who can get kidney from most of donors (for example, blood type AB) can be easily matched to other pairs. The opposite case would be hard-to-match pair that is incompatible for matching with most of other pairs. Our model is an abstraction of these two motivating examples, and considers two types of agents: easy-to-match agents that can be matched with either type of agents, and hard-to-match agents that can be only matched with easy-to-match ones. We first formulate a dynamic program to solve for optimal matching decisions over infinite time horizon in a discrete time setting, and characterize structure of optimal stationary policies. Inspired by practices in kidney exchange where the market is cleared for every fixed time interval, we connect the discrete time model to a continuous time setting by investigating the effect of the length of matching intervals on the matching performance. Results from numerical experiments indicate certain patterns in the relationship between the length of matching intervals and the maximum number of matching achieved, and provides valuable insights for future direction of research. In Chapter 2, we consider a zoning problem for elevator dispatching systems in high-rises. In practice, zoning is frequently used to improve efficiency of elevator systems. The idea of zoning is to prevent different elevators from stopping at common floors, which may result in long service times of elevators and thus long waiting times of customers. Our goal is to provide a mathematical framework that can help a system planner decide optimal zoning design with some performance guarantee. To this end, we focus on uppeak traffic situation during morning rush hour, which is in general the heaviest traffic during the day. The performance in the uppeak traffic situation can be considered as the system's capacity, because if the system can handle uppeak traffic well, it can also serve other types of traffic with good performance. Thus, the performance measure in the uppeak traffic situation can be used as a metric to choose the optimal zoning configuration. One of the components that complicate the problem is customer batching, on which the system may not have a control. In view of this, we formulate an adversarial optimization problem that can measure the system performance of different zoning decisions. By considering the heaviest traffic situation of the day and using the adversarial framework, we provide a model that can be used for capacity planning of elevator systems. We formulate mixed-integer linear program(MILP)s to find the optimal zoning configuration. To solve the MILPs, we show that we can use simple greedy algorithms and solve smaller linear programs. We also provide a few illustrative examples as well as numerical experiments to verify the theoretical results and obtain insights for further analysis

Generation of spiral bevel gears with conjugate tooth surfaces and tooth contact analysis

A new method for generation of spiral bevel gears is proposed. The main features of this method are as follows: (1) the gear tooth surfaces are conjugated and can transform rotation with zero transmission errors; (2) the tooth bearing contact is localized; (3) the center of the instantaneous contact ellipse moves in a plane that has a fixed orientation; (4) the contact normal performs in the process of meshing a parallel motion; (5) the motion of the contact ellipse provides improved conditions of lubrication; and (6) the gears can be manufactured by use of Gleason's equipment

Optimization for Urban Mobility Systems

In the recent decades, new modes of transportation have been developed due to urbanization, highly dense population, and technological advancement. As a result, design and operation of urban transportation have become increasingly important to better utilize the resources and efficiently meet demand. This dissertation was motivated by two problems on optimizing design and control of urban transportation. In the first one, we consider a problem of dynamically matching heterogeneous market parcitipants so as to maximize the total number of matching, which was motivated by practices of ride-sharing platforms. In the other problem, we study efficient design of elevator zoning system in high-rises with uncertainty in customer batching.In Chapter 1, we consider a multiperiod stochastic optimization of a market that matches heterogeneous and impatient agents. The model was mainly motivated from carpooling products run by ride-sharing platforms such as Uber and Lyft, and kidney exchange market, where market participants are heterogeneous in terms of how likely they can be matched with others. In the case of a ride-sharing platform, one of the key operational decisions for carpooling is to efficiently match riders and clear the market in a timely manner. In doing so, the platform needs to take into account the heterogeneity of riders in terms of their trip types(e.g origin-destination pair) and different matching compatibility. For example, some customers may request rides within San Francisco, while others may request rides from San Francisco to outside the city. Since picking up and dropping off a customer within the city can be done within relatively short amount of time, those who want to travel within the city can be matched with any other riders for carpooling. However, the destinations of those who want to travel to outside the city may be very different, and in order to maintain customers' additional transit time due to carpooling, it is likely that they can be only matched with those who want to travel within the city. In the case of kidney exchange where market participants arrive in the form of patient-donor pair, pairs with donor who can donate her kidney to most of patients (for example, blood type O) and patient who can get kidney from most of donors (for example, blood type AB) can be easily matched to other pairs. The opposite case would be hard-to-match pair that is incompatible for matching with most of other pairs. Our model is an abstraction of these two motivating examples, and considers two types of agents: easy-to-match agents that can be matched with either type of agents, and hard-to-match agents that can be only matched with easy-to-match ones. We first formulate a dynamic program to solve for optimal matching decisions over infinite time horizon in a discrete time setting, and characterize structure of optimal stationary policies. Inspired by practices in kidney exchange where the market is cleared for every fixed time interval, we connect the discrete time model to a continuous time setting by investigating the effect of the length of matching intervals on the matching performance. Results from numerical experiments indicate certain patterns in the relationship between the length of matching intervals and the maximum number of matching achieved, and provides valuable insights for future direction of research. In Chapter 2, we consider a zoning problem for elevator dispatching systems in high-rises. In practice, zoning is frequently used to improve efficiency of elevator systems. The idea of zoning is to prevent different elevators from stopping at common floors, which may result in long service times of elevators and thus long waiting times of customers. Our goal is to provide a mathematical framework that can help a system planner decide optimal zoning design with some performance guarantee. To this end, we focus on uppeak traffic situation during morning rush hour, which is in general the heaviest traffic during the day. The performance in the uppeak traffic situation can be considered as the system's capacity, because if the system can handle uppeak traffic well, it can also serve other types of traffic with good performance. Thus, the performance measure in the uppeak traffic situation can be used as a metric to choose the optimal zoning configuration. One of the components that complicate the problem is customer batching, on which the system may not have a control. In view of this, we formulate an adversarial optimization problem that can measure the system performance of different zoning decisions. By considering the heaviest traffic situation of the day and using the adversarial framework, we provide a model that can be used for capacity planning of elevator systems. We formulate mixed-integer linear program(MILP)s to find the optimal zoning configuration. To solve the MILPs, we show that we can use simple greedy algorithms and solve smaller linear programs. We also provide a few illustrative examples as well as numerical experiments to verify the theoretical results and obtain insights for further analysis

Unique electrochemical behavior of a silver–zinc secondary battery at high rates and low temperatures

This study investigates an unusual charging phenomenon observed in silver–zinc secondary batteries. In the case of general secondary batteries, the specific capacity and coulombic efficiency decrease with increasing battery charging rate because of a concomitant increase in overvoltage. However, this study reveals that, at room temperature and within a specific charging-rate range, the discharge capacity and coulombic efficiency of silver–zinc batteries increase with increasing charging rate. To elucidate this unusual behavior, the charge/discharge characteristics of silver–zinc batteries were systematically analyzed at different charging rates and operating temperatures. In addition, the structural and compositional evolution of the silver cathode with the state of charge of the battery were investigated. The experimental results demonstrated that the phase transformation kinetics of silver oxide to silver peroxide governs the electrochemical performance of silver–zinc batteries and the kinetically unfavorable formation of silver peroxide ironically enables fast-chargeable silver–zinc batteries with high capacity and efficiency. Furthermore, it was confirmed that the suppression of water hydrolysis at low temperatures promotes the silver peroxide formation, resulting in high capacity during low temperature operation. This study provides an effective charge strategy, which could help achieve high-capacity, high-efficiency silver–zinc secondary batteries. © 20211

The Effects of Operational Efficiency and Environmental Risk on the Adoption of Environmental Management Practices

Given that prior research has provided inconsistent findings on the relationship between financial performance and the adoption of environmental management practices (EMPs), we aim to resolve the inconsistency by positing that the firm may consider different components of financial performance when making decisions. Specifically, we maintain that operational efficiency, measured based on net profit margin, is a key determinant of a firm’s decision to adopt EMPs. Additionally, we aim to examine environmental risk as one contingency that moderates the relationship between operational efficiency and EMP adoption. Employing a firm-fixed effect model to examine the effects of various measures of financial performance, including the net profit margin, return on asset (ROA), return on equity (ROE), and asset turnover, on the adoption rates of EMPs by firms, we find that firms with higher operational efficiency measured based on net profit margin are more inclined to adopt EMPs, while measures such as ROA, ROE, and asset turnover do not demonstrate any substantial effect. This study also finds that while environmental risk increases the possibility of adopting EMPs, it weakens the impact of operational efficiency on the adoption rates of EMPs

Examining Comparative Shopping Agents from Two Types of Search Results

When searching for products and information using search engines, Web consumers often see comparative shopping agents (CSAs) in search results. CSAs list companies that sell desired products and the prices they offer on one page, greatly reducing search costs. Using 168 digital camera models from seven major camera makers, we examine CSAs between organic and paid search results in terms of the number of CSAs, number of vendors, lowest and average prices, and price dispersion

Thin-Film Optical Devices Based on Transparent Conducting Oxides: Physical Mechanisms and Applications

This paper provides a review of optical devices based on a wide band-gap transparent conducting oxide (TCO) while discussing related physical mechanisms and potential applications. Intentionally using a light-induced metastability mechanism of oxygen defects in TCOs, it is allowed to detect even visible lights, eluding to a persistent photoconductivity (PPC) as an optical memory action. So, this PPC phenomenon is naturally useful for TCO-based optical memory applications, e.g., optical synaptic transistors, as well as photo-sensors along with an electrical controllability of a recovery speed with gate pulse or bias. Besides the role of TCO channel layer in thin-film transistor structure, a defective gate insulator can be another approach for a memory operation with assistance for gate bias and illuminations. In this respect, TCOs can be promising materials for a low-cost transparent optoelectronic application

Resistive Switching Characteristics of Alloyed AlSiOx Insulator for Neuromorphic Devices

Charge-based memories, such as NAND flash and dynamic random-access memory (DRAM), have reached scaling limits and various next-generation memories are being studied to overcome their issues. Resistive random-access memory (RRAM) has advantages in structural scalability and long retention characteristics, and thus has been studied as a next-generation memory application and neuromorphic system area. In this paper, AlSiOx, which was used as an alloyed insulator, was used to secure stable switching. We demonstrate synaptic characteristics, as well as the basic resistive switching characteristics with multi-level cells (MLC) by applying the DC sweep and pulses. Conduction mechanism analysis for resistive switching characteristics was conducted to understand the resistive switching properties of the device. MLC, retention, and endurance are evaluated and potentiation/depression curves are mimicked for a neuromorphic device

Achieving Mass Customization Through Trust-driven Information Sharing: A Supplier’s Perspective

Purpose – Trust is essential for business relationships within a supply chain, and information sharing provides a key means to improve the efficiency of a supply chain. The purpose of this paper is to test empirically the relationship between trust and manufacturer-supplier information sharing to determine its (positive) effect on mass customization. Design/methodology/approach – The data come from 208 firms in North America and China. Structural equation modeling supports the data analysis. Findings – The results suggest that high mutual trust can lead to free information sharing between suppliers and manufacturers, which in turn leads to improved mass customization capabilities. In addition, cultural differences have significant moderating effects on the relationship between trust and information sharing. Originality/value – The study described in this paper measures mutual trust between manufacturers and suppliers and regards information sharing as the free flow of information, both to and from the manufacturer and supplier