Sarah G. Nurre

Integrated network design and scheduling problems with parallel identical machines: Complexity results and dispatching rules

We consider the class of integrated network design and scheduling INDS problems that focus on selecting and scheduling operations that will change the characteristics of a network, while being specifically concerned with the performance of the network over time. Motivating applications of INDS problems include infrastructure restoration after an extreme event and building humanitarian logistics networks. We examine INDS problems under a parallel identical machine scheduling environment where the performance of the network is evaluated by solving classic network optimization problems. We prove that all considered INDS problems are NP-hard. We propose a novel heuristic dispatching rule algorithm framework that selects and schedules sets of arcs based on their interactions in the network. These interactions are measured by examining network optimality conditions. Computational testing of these dispatching rules on realistic data sets representing infrastructure networks of lower Manhattan, New York demonstrates that they arrive at near-optimal solutions in real-time.Copyright

Identification and Classification of Restoration Interdependencies in the Wake of Hurricane Sandy

AbstractThis paper introduces the new concept of restoration interdependencies that exist among infrastructures during their restoration efforts after an extreme event. Restoration interdependencies occur whenever a restoration task in one infrastructure is impacted by a restoration task, or lack thereof, in another infrastructure. This work identifies examples of observed restoration interdependencies during the restoration efforts after Hurricane Sandy as reported by major newspapers in the affected areas. A classification scheme for the observed restoration interdependencies is provided that includes five distinct classes: traditional precedence, effectiveness precedence, options precedence, time-sensitive options, and competition for resources. This work provides an overview of these different classes by providing the frequency they were observed, the infrastructures involved with the restoration interdependency, and a discussion of their potential impact on interdependent infrastructure restoration. ...

Optimal Policies for the Management of an Electric Vehicle Battery Swap Station

Optimizing operations at electric vehicle (EV) battery swap stations is internally motivated by the movement to make transportation cleaner and more efficient. An EV battery swap station allows EV owners to quickly exchange their depleted battery for a fully charged battery. We introduce the EV Battery-Swap Station Management Problem (EVB-SSMP), which models battery charging and discharging operations at an EV battery swap station facing nonstationary, stochastic demand for battery swaps, nonstationary prices for charging depleted batteries, and nonstationary prices for discharging fully charged batteries. Discharging through vehicle-to-grid is beneficial for aiding power load balancing. The objective of the EVB-SSMP is to determine the optimal policy for charging and discharging batteries that maximizes expected total profit over a fixed time horizon. The EVB-SSMP is formulated as a finite-horizon, discrete-time Markov decision problem and an optimal policy is found using dynamic programming. We derive s...

Video Tutorials Within an Undergraduate Operations Research Course: Student Perception on Their Integration and Creating A Blended Learning Environment

In this paper, we discuss the impact of video tutorials on an undergraduate operations research (OR) course and analyze important aspects of student perception of their impact on the learning experience. Supplementary video tutorials offer additional examples of OR concepts; thus, class time can be more focused on letting students gain intuition about these concepts. We analyze students’ survey responses to help determine the perceived impact of the video tutorials on office hours and whether students’ familiarity with the creator of the tutorials impacted the tutorials’ effectiveness. Our results demonstrate that students saw significant advantages in using these supplementary video tutorials and that the creator of the tutorials did not impact the tutorials’ effectiveness as long as they were properly integrated into the course. Therefore, our results show that the overhead required to offer online video tutorials may be low (i.e., similar to selecting a course textbook) since their success relies more on proper integration into the course than having the professor of the course produce them. In addition, a preliminary assessment demonstrates that our blended learning environment has a positive impact on the learning experience.

Decomposition Methods for Restoring Infrastructure Systems

We consider a new class of integrated network design and scheduling problems, with important applications in the restoration of services provided by civil infrastructure systems after an extreme event. Critical services such as power, waste water, and transportation are provided by these infrastructure systems. The restoration of these services is necessary for the society to recover from the extreme event as quickly as possible. The class of integrated network design and scheduling problems considered by this work focuses on a set of selected arcs to install into an existing network (i.e., network design decisions) and then scheduling these arcs on a set of work groups. Unlike previous network design problems, the network must be operating at intermediate points in time so that the scheduling decisions associated with the design decisions have a significant impact on the objective of the problem. The operations of the network at intermediate points in time will be evaluated by determining the amount of satisfied demand in the network. We also discuss exact methods to solve this class of large scale optimization problems by employing decomposition techniques. Our methods are tested on a realistic data set representing the (disrupted) power infrastructure of New Hanover County, NC. These results indicate that our methods are capable of providing better computational performance to decision-makers.

Interactive Excel-Based Gantt Chart Schedule Builder

Many scheduling dispatching rules are intuitive processes used in every day life. For example, when faced with a variety of tasks due at different times one often implements the earliest due date scheduling rule: The next task worked on is the one with the earliest due date. Other common scheduling dispatching rules are easily understood, thereby enabling one to devise the rule when given the opportunity to experiment via trial and error. In this paper, we present an interactive Excel-based Gantt Chart Schedule builder that enables students to experiment with building schedules for different single and parallel machine problem examples. Instead of explicitly telling students these common scheduling rules, the schedule builder enables students to gain intuition about the rules on their own. Herein we describe the interactive schedule builder we created, explain how instructors and students can use this tool, perform a small preliminary assessment on the student perception metric, and provide supplemental teaching materials enabling use of the schedule builder in a variety of classroom environments.

Increasing the Resiliency of Local Supply Chain Distribution Networks against Multiple Hazards

We examine the resiliency of retail locations of a supply chain network to aid in the recovery of the local community after an extreme event. A two-stage stochastic programming model is used to determine the placement of permanent generators at the retail locations of Stewart’s Shops, which distributes both convenience items and fuel in Upstate New York and Vermont, to enhance the resiliency of the supply chain. Our measure of resiliency specifically considers the recovery process of each retail location after the extreme event and its interdependency on other external infrastructure systems. Our computational experiments consider the multiple distinct types of hazards that can affect the retail locations of Stewart’s Shops. We empirically explore different stochastic sampling procedures to solve the resiliency model. The results of computational tests indicate that we can converge to an approximate optimal solution quickly. We compare the resiliency efforts when planning for different types of hazards versus all hazards simultaneously as well as the impact of external infrastructure systems on the resiliency efforts. The empirical study identifies that the stores in rural, less densely populated areas, serving a large population should be selected to receive generators. ∗Department of Operational Sciences, Air Force Institute of Technology, 2950 Hobson Way, WPAFB, OH 45433. †Department of Industrial and Systems Engineering, Rensselaer Polytechnic Institute, 110 8th Street, Troy, NY, 12180. The work of this author was supported in part by the National Science Foundation under grant number 1254258. ‡Department of Mathematical Sciences, Rensselaer Polytechnic Institute, 110 8th St, Troy, NY 12180.