Institute for Systems Research Technical Reports

Permanent URI for this collectionhttp://hdl.handle.net/1903/4376

This archive contains a collection of reports generated by the faculty and students of the Institute for Systems Research (ISR), a permanent, interdisciplinary research unit in the A. James Clark School of Engineering at the University of Maryland. ISR-based projects are conducted through partnerships with industry and government, bringing together faculty and students from multiple academic departments and colleges across the university.

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Author: search.filters.author.Herrmann, Jeffrey W.Start date: 2000

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Now showing 1 - 10 of 25
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    Using Metareasoning on a Mobile Ground Robot to Recover from Path Planning Failures
    (2023-02) Molnar, Sidney; Mueller, Matt; Macpherson, Robert; Rhoads, Lawrence; Herrmann, Jeffrey W.
    Autonomous mobile ground robots use global and local path planners to determine the routes that they should follow to achieve mission goals while avoiding obstacles. Although many path planners have been developed, no single one is best for all situations. This paper describes metareasoning approaches that enable a robot to select a new path planning algorithm when the current planning algorithm cannot find a feasible solution. We implemented the approaches within a ROS-based autonomy stack and conducted simulation experiments to evaluate their performance in multiple scenarios. The results show that these metareasoning approaches reduce the frequency of failures and reduce the time required to complete the mission.
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    Separating the Inventory Slack Routing Problem
    (2012-07) Herrmann, Jeffrey W.
    In practice, when faced with a complex optimization problem, human decision-makers often separate it into subproblems and then solve each subproblem instead of tackling the complete problem. This paper describes a study in which different approaches for separating the Inventory Slack Routing Problem (a complex vehicle routing problem) were simulated. A random search was used to simulate how a bounded rational human decision-maker would solve each subproblem. The results show that the structure of the separation and the objectives used in each subproblem can significantly affect the quality of the solutions that are generated. This suggests that organizations should consider and assess how they separate complex optimization problems so that their limited decision-making resources can be employed efficiently and effectively.
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    Aggregating Alphabets to Construct Balanced Words
    (2009-09) Herrmann, Jeffrey W.
    Balanced words are useful for scheduling mixed-model, just-in-time assembly lines, planning preventive maintenance, managing inventory, and controlling asynchronous transfer mode (ATM) networks. This paper considers the challenging problem of finding a balanced word (a periodic sequence) for a finite set of letters, when the desired densities of the letters in the alphabet are given. We present an aggregation approach that combines letters with the same density, constructs a word for the aggregated alphabet, and then disaggregates this word into a feasible word for the original alphabet. We consider two different measures for evaluating solutions and use the aggregation approach with different heuristics. Computational experiments show that using aggregation not only finds more balanced words but also reduces computational effort.
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    Constructing Perfect Aggregations to Eliminate Response Time Variability in Cyclic Fair Sequences
    (2008-10) Herrmann, Jeffrey W.
    Fair sequences are useful in a variety of manufacturing and computer systems. This paper considers the generation of cyclic fair sequences for a given set of products, each of which must be produced multiple times in each cycle. The objective is to create a sequence so that, for each product, the variability of the time between consecutive completions is minimized. Previous work introduced an aggregation approach that can reduce response time variability (RTV) dramatically. However, in some cases, aggregating more carefully can generate sequences with zero RTV. We call this a perfect aggregation. This paper discusses properties of instances that have perfect aggregations. Moreover, we present techniques that can find a perfect aggregation if one exists.
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    Design Optimization with Imprecise Random Variables
    (2008-09) Herrmann, Jeffrey W.
    Design optimization is an important engineering design activity. Performing design optimization in the presence of uncertainty has been an active area of research. The approaches used require modeling the random variables using precise probability distributions or representing uncertain quantities as fuzzy sets. This work, however, considers problems in which the random variables are described with imprecise probability distributions, which are highly relevant when there is limited information about the distribution of a random variable. In particular, this paper formulates the imprecise probability design optimization problem and presents an approach for solving it. We present examples for illustrating the approach.
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    Routing and Scheduling for Medication Distribution Plans
    (2008-09-18) Herrmann, Jeffrey W.; Lu, Sara; Schalliol, Kristen
    This paper presents a two-stage approach for solving the medication distribution problem. The problem addresses a critical issue in emergency preparedness. Public health officials must plan the logistics for distributing medication to points of dispensing (PODs), which will give medication to the public in case of a bioterrorist attack such as anthrax. We consider the problem at the state and local levels. Our approach separates the problem into two subproblems: (1) the “routing problem” assigns PODs to vehicles and creates routes for each vehicle, and (2) the “scheduling problem” determines when the vehicles should start these routes and how much material should be delivered on each trip. This paper presents the results of using this approach to construct solutions for a realistic three-county scenario. The results show that the routing and scheduling decisions greatly affect the quality of the solution.
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    Using Aggregation to Reduce Response Time Variability in Cyclic Fair Sequences
    (2008-08-15) Herrmann, Jeffrey W.
    Fair sequences are useful in a variety of manufacturing and computer systems. This paper considers the generation of cyclic fair sequences for a given set of products, each of which must be produced multiple times in each cycle. The objective is to create a sequence so that, for each product, the variability of the time between consecutive completions is minimized. Because minimizing response time variability is known to be NP-hard and the performance of existing heuristics is poor for certain classes of problems, we present an aggregation approach that combines products with the same demand into groups, creates a sequence for those groups, and then disaggregates the sequence into a sequence for each product. Computational experiments show that using aggregation can reduce response time variability dramatically.
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    Queueing network approximations for mass dispensing and vaccination clinics
    (2008-01-10) Pilehvar, Ali; Herrmann, Jeffrey W.
    To respond to bioterrorism events or to curb outbreaks of contagious diseases, county health departments must set up and operate clinics to dispense medications or vaccines. Planning these clinics in advance of such an event requires determining clinic capacity and estimating the queueing that may occur in such facilities. We construct a queueing network model for mass dispensing and vaccination clinics and estimate the time that residents will spend at each workstation in such facilities. A key contribution is the development of useful approximations for queueing systems that have batch arrival, multiple-server batch processes and self-service stations. We compared the model’s estimates to those from simulation experiments of realistic clinics using data collected from emergency preparedness exercises. Although this research was motivated by this specific application, the model should be applicable to the design and analysis of other similar queueing networks, including manufacturing systems with batch processes.
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    Decision-Based Design Processes
    (2008-01-02) Herrmann, Jeffrey W.
    This paper studies engineering design decision-making. We show that the decision-based design framework, which seeks to find the most profitable design, can be separated into a sequence of subproblems. This separation is similar to decomposition but does not require a second-level coordination. We identify conditions under which this separation yields an exact solution and other conditions under which the error can be bounded. This separation provides a different way to solve the decision-based design framework and indicates a way to apply the principles of decision-based design to design processes.
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    The Legacy of Taylor, Gantt, and Johnson: How to Improve Production Scheduling
    (2007-12) Herrmann, Jeffrey W.
    The challenge of improving production scheduling has inspired many different approaches. This paper examines the key contributions of three individuals who improved production scheduling: Frederick Taylor, who defined the key planning functions and created a planning office; Henry Gantt, who provided useful charts to improve scheduling decision-making, and S.M. Johnson, who initiated the mathematical analysis of production scheduling problems. The paper presents an integrative strategy to improve production scheduling that synthesizes these complementary approaches. Finally, the paper discusses the soundness of this approach and its implications on OR research, education, and practice.