The effect of maternal employment on adolescents' transition to young adulthood

The purpose of this study was to examine relationships between multiple characteristics of maternal employment, parenting practices, and adolescents’ transition outcomes to young adulthood. The research addressed four main research questions. First, are the characteristics of maternal work (i.e., hours worked, multiple jobs held, work schedules, earnings, and occupation) related to adolescents’ enrollment in post-secondary education, employment, or involvement in neither of these types of activities as young adults? Second, are the work characteristics related to parental involvement and monitoring, and are the parenting practices related to adolescents’ transition outcomes? Third, do parental involvement and monitoring mediate any relationships between the characteristics of maternal employment and adolescents’ transition outcomes? Finally, do any associations between characteristics of maternal employment and parenting practices and adolescents’ transition outcomes vary by poverty status, race/ethnicity, or gender? To address these research questions, secondary data analysis was conducted, using data from the National Longitudinal Survey of Youth (NLSY) from 1998 through 2004. The study sample consisted of 849 youths who were 15 through 17 years of age in either 1998 or 2000, and were 19 through 21 years of age when their transition outcomes in young adulthood were measured four years later. Multinomial logistic and ordinary least squares regression models were estimated to answer the research questions. Study findings indicated that of the maternal work characteristics, mothers’ multiple jobs held, occupation, and work schedule were significantly related to the youths’ transition outcomes. When mothers held multiple jobs for 1 to 25 weeks per year, and when mothers held jobs involving lower levels of occupational complexity, their youths were more likely to experience employment rather than post-secondary education. Adolescents whose mothers worked a standard work schedule were less likely to experience other types of transitions than post-secondary education. With regard to the effects of maternal employment on parenting practices, none of the maternal work variables were related to parental involvement, and only one variable, mothers working less than 40 hours per week, was negatively related to parental monitoring. In addition, when parents were more involved with their youths’ education, the youths were less likely to transition into employment and other types of transitions rather than post-secondary education. The parenting practices did not mediate the relation between the significant work variables (holding multiple jobs, work schedule, and occupation) and youths’ transition outcomes. Finally, none of the interactions between maternal work characteristics and poverty status, race/ethnicity, and gender met the criteria for determining significance; but in a series of sub-group analyses, some differences according to poverty status and gender were found. Despite the lack of mediation and moderation, the findings of this study have important implications for social policy and social work intervention. Based on the findings, suggestions are made in these areas to improve working mothers’ lives and their adolescents’ development and successful transition to adulthood. Finally, directions for future research are discussed.

Scheduling of track inspection and maintenance activities in railroad networks

The U.S. railroad companies spend billions of dollars every year on railroad track maintenance in order to ensure safety and operational efficiency of their railroad networks. Besides maintenance costs, other costs such as train accident costs, train and shipment delay costs and rolling stock maintenance costs are also closely related to track maintenance activities. Optimizing the track maintenance process on the extensive railroad networks is a very complex problem with major cost implications. Currently, the decision making process for track maintenance planning is largely manual and primarily relies on the knowledge and judgment of experts. There is considerable potential to improve the process by using operations research techniques to develop solutions to the optimization problems on track maintenance. In this dissertation study, we propose a range of mathematical models and solution algorithms for three network-level scheduling problems on track maintenance: track inspection scheduling problem (TISP), production team scheduling problem (PTSP) and job-to-project clustering problem (JTPCP). TISP involves a set of inspection teams which travel over the railroad network to identify track defects. It is a large-scale routing and scheduling problem where thousands of tasks are to be scheduled subject to many difficult side constraints such as periodicity constraints and discrete working time constraints. A vehicle routing problem formulation was proposed for TISP, and a customized heuristic algorithm was developed to solve the model. The algorithm iteratively applies a constructive heuristic and a local search algorithm in an incremental scheduling horizon framework. The proposed model and algorithm have been adopted by a Class I railroad in its decision making process. Real-world case studies show the proposed approach outperforms the manual approach in short-term scheduling and can be used to conduct long-term what-if analyses to yield managerial insights. PTSP schedules capital track maintenance projects, which are the largest track maintenance activities and account for the majority of railroad capital spending. A time-space network model was proposed to formulate PTSP. More than ten types of side constraints were considered in the model, including very complex constraints such as mutual exclusion constraints and consecution constraints. A multiple neighborhood search algorithm, including a decomposition and restriction search and a block-interchange search, was developed to solve the model. Various performance enhancement techniques, such as data reduction, augmented cost function and subproblem prioritization, were developed to improve the algorithm. The proposed approach has been adopted by a Class I railroad for two years. Our numerical results show the model solutions are able to satisfy all hard constraints and most soft constraints. Compared with the existing manual procedure, the proposed approach is able to bring significant cost savings and operational efficiency improvement. JTPCP is an intermediate problem between TISP and PTSP. It focuses on clustering thousands of capital track maintenance jobs (based on the defects identified in track inspection) into projects so that the projects can be scheduled in PTSP. A vehicle routing problem based model and a multiple-step heuristic algorithm were developed to solve this problem. Various side constraints such as mutual exclusion constraints and rounding constraints were considered. The proposed approach has been applied in practice and has shown good performance in both solution quality and efficiency.