Seed and vegetative propagation methods for the rare Florida native species Chionanthus pygmaeus (pygmy fringetree)

Chionanthus pygmaeus Small (pygmy fringetree) (Oleaceae) is an endemic and rare Florida species, which has an attractive, small habit giving it great potential for use in managed landscapes. Members of the genus Chionanthus are difficult to propagate via cuttings and possess complex seed dormancies that are not well understood. Conservation of pygmy fringetree and its potential for commercial propagation for use in managed landscapes is contingent on a better understanding of its complex seed dormancy and enhancement of its propagation. I conducted two experiments to assess sexual and asexual propagation methods for pygmy fringetree. The first experiment was conducted to determine what factors are involved in overcoming seed dormancy. Various scarification treatments, which mimicked conditions seeds are exposed to in the wild, were investigated to determine their effects on germination of 20-year-old seeds originally collected from the species’ native range. Treatments included endocarp removal, sulfuric acid, boiling-water, and smoke-water treatments. Prior to treatment initiation, seed viability was estimated to be 12%. Treated seeds went through two cold- and two warm-stratification periods of 4°C and 25°C, respectively, in a dark growth chamber. After 180 days, none of the treatments induced early germination. Seeds were then tested for viability, which was 11%. Seed dormancy of the species is apparently complex, allowing some of the seeds to retain some degree of viability, but without dormancy requirements satisfied. The second experiment was conducted to assess if pygmy fringetree could be successfully propagated via hardwood or root cuttings if the appropriate combination of environmental conditions and hormones were applied. Hardwood and root cuttings were treated with either 1000 ppm IBA talc, 8000 ppm IBA talc, or inert talc. All cuttings were placed on a mist bench in a greenhouse for 9 weeks. Hardwood cuttings were supplemented with bottom heat at 24 °C. No treatments were successful in inducing adventitious root formation. I conclude that pygmy fringetree seeds possess complex dormancy that was not able to be overcome by the treatments utilized. However, this result is confounded by the age of the seeds used in the experiment. I also conclude that vegetative propagation of pygmy fringetree is highly dependent on the time of year cuttings are harvested. Further research of both seed and asexual propagation methods need to be explored before pygmy fringetree can be propagated on a commercial scale.

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.