Recursos de colección

DSpace at MIT (104.280 recursos)

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Operations Research - Master's degree

Mostrando recursos 1 - 20 de 127

  1. Revenue optimization for a hotel property with different market segments : demand prediction, price selection and capacity allocation

    Candela Garza, Eduardo
    We present our work with a hotel company as an example of how machine learning techniques can be used to improve the demand predictions of a hotel property, as well as its pricing and capacity allocation decisions. First, we build a price-sensitive random forest model to predict the number of daily bookings for each customer market segment. We feed these predictions into a mixed integer linear program (MILP) to optimize prices and capacity allocations at the same time. We prove that the MILP can be equivalently solved as a linear program, and then show that it produces upper and lower...

  2. A data-driven approach to mitigate risk in global food supply chains

    Anoun, Amine
    Economically motivated adulteration of imported food poses a serious threat to public health, and has contributed to several poisoning incidents in the past few years in the U.S. [1]. Prevention is achieved by sampling food shipments coming to the U.S. However, the sampling resources are limited: all shipments are electronically sampled [2], but only a small percentage of shipments are physically inspected. In an effort to mitigate risk in shipping supply chains, we develop a data-driven approach to identify risky shippers and manufacturers exporting food to the U.S., as well as U.S. based consignees and importers receiving imported products. We...

  3. Redesigning liver allocation regions through optimization

    Scully, Timothy (Timothy Edward)
    End-stage liver disease is one of the leading causes of death in the United States, and the only viable treatment is liver transplantation. Since the quality of a donor liver decreases with transportation time, United States organ policy prioritizes transplants within geographic regions. However, the boundaries of these regions were defined mostly by informal relationships between transplant centers many decades ago, which has created local imbalances in supply and demand. As a result, candidates on the waiting list for donor livers face drastically different odds of receiving a transplant. Policy makers have noticed this geographic inequity and are considering proposals...

  4. Inferring user location from time series of social media activity

    Webb, Matthew Robert
    Combining social media posts with known user locations can lead to unique insights with applications ranging from tracking diffusion of sentiment to earthquake detection. One approach used to determine a user's home location is to examine the timing of their posts, but the precision of existing time-based location predictors is limited to discrimination among time zones. In this thesis, we formulate a general time-based geolocation algorithm that has greater precision, using knowledge of a social media user's real world activities derived from his or her membership in a particular class. Our activity-based model discriminates among locations within a time zone,...

  5. Relative performance transparency : effects on sustainable purchase and consumption behavior

    Mariadassou, Shwetha Paramananda
    We build on existing operations and marketing research focusing on the effect of information transparency on consumers by studying how transparency into the levels and changes of relative sustainability performance affects consumer behavior. Our work considers two forms of transparency: process transparency and customer transparency. We operationalize process transparency, in which information about the company's sustainability performance relative to competitors is revealed to the customer, in the product purchase domain. We operationalize customer transparency, in which the customer receives information about their own sustainability performance relative to other customers, in the energy consumption domain. In a series of online consumer...

  6. Persistent cascades and the structure of influence in a communication network

    Morse, Steven T
    We present work in identifying, modeling, and predicting the structure of influence in a communication network. We focus on cellular phone data, which provides a near-global population sample (in contrast to the relatively limited scope of social media and other internet-based datasets) at the expense of losing any knowledge of the content of the communications themselves. First, using inexact tree matching and hierarchical clustering, we propose a novel method for extracting persistent patterns of communication among individuals, which we term persistent cascades. We find the cascades are short in duration ('bursty'), exhibit habitual hierarchy and long-term persistence, and reveal new...

  7. Predicting performance using galvanic skin response

    Mundell, Lee Carter
    The rapid growth of the availability of wearable biosensors has created the opportunity for using physiological signals to measure worker performance. An important question is how to use such signals to not just measure, but actually predict worker performance on a task under stressful and potentially high risk conditions. Here we show that the biological signal known as galvanic skin response (GSR) allows such a prediction. We conduct an experiment where subjects answer arithmetic questions under low and high stress conditions while having their GSR monitored. Using only the GSR measured under low stress conditions, we are able to predict...

  8. Think global, act local when estimating a sparse precision matrix

    Lee, Peter Alexander
    Substantial progress has been made in the estimation of sparse high dimensional precision matrices from scant datasets. This is important because precision matrices underpin common tasks such as regression, discriminant analysis, and portfolio optimization. However, few good algorithms for this task exist outside the space of L1 penalized optimization approaches like GLASSO. This thesis introduces LGM, a new algorithm for the estimation of sparse high dimensional precision matrices. Using the framework of probabilistic graphical models, the algorithm performs robust covariance estimation to generate potentials for small cliques and fuses the local structures to form a sparse yet globally robust model...

  9. Interacting with users in social networks : the follow-back problem

    Rajagopalan, Krishnan, S.M. Sloan School of Management
    An agent wants to form a connection with a predetermined set of target users over social media. Because forming a connection is known as "following" in social networks such as Twitter, we refer to this as the follow-back problem. The targets and their friends form a directed graph which we refer to as the "friends graph." The agent's goal is to get the targets to follow it, and it is allowed to interact with the targets and their friends. To understand what features impact the probability of an interaction resulting in a follow-back, we conduct an empirical analysis of several...

  10. Internet of Things and anomaly detection for the iron ore mining industry

    Saroufim, Carl Elie
    In the context of a world flooded with data, the Internet of Things (IoT) is exploding. This thesis considers the problem of applying IoT technology to the reduction of costs in the iron ore mining industry, to compensate for the iron ore price slumping observed over the past years. More specifically, we focused on improving the quality of the output in a data-driven iron ore concentration factory. In this plant, mined iron ore goes through a series of complex physical and chemical transformations so as to increase the concentration in iron and reduce the concentration in impurities such as silica....

  11. Multi-target tracking via mixed integer optimization

    Saunders, Zachary Clayton
    Given a set of target detections over several time periods, this paper addresses the multi-target tracking problem (MTT) of optimally assigning detections to targets and estimating the trajectory of the targets over time. MTT has been studied in the literature via predominantly probabilistic methods. In contrast to these approaches, we propose the use of mixed integer optimization (MIO) models and local search algorithms that are (a) scalable, as they provide near optimal solutions for six targets and ten time periods in milliseconds to seconds, (b) general, as they make no assumptions on the data, (c) robust, as they can accommodate...

  12. Optimization of yard operations in maritime container terminals

    Borjian Boroujeni, Setareh
    With the continuous growth in international container shipping, many container terminals in maritime ports face congestion, particularly during peak hours of service, and when there is limited space in the storage area. Thus, there has been increasing interest in improving operations efficiency in container terminals. An efficient terminal, in general, is one that discharges containers from the ships in a timely manner and delivers containers to customers with a reasonable wait time. Moreover, a key performance measure in the storage area is the number of moves performed by yard cranes. Due to limited space in the storage area, containers are...

  13. Anomaly detection methods for unmanned underwater vehicle performance data

    Harris, William Ray
    This thesis considers the problem of detecting anomalies in performance data for unmanned underwater vehicles(UUVs). UUVs collect a tremendous amount of data, which operators are required to analyze between missions to determine if vehicle systems are functioning properly. Operators are typically under heavy time constraints when performing this data analysis. The goal of this research is to provide operators with a post-mission data analysis tool that automatically identifies anomalous features of performance data. Such anomalies are of interest because they are often the result of an abnormal condition that may prevent the vehicle from performing its programmed mission. In this...

  14. Modeling and design of material recovery facilities : genetic algorithm approach

    Testa, Mariapaola
    In the Organisation for Economic Co-operation and Development (OECD) area, the production of numerical solid waste (MI\SW) increased by 32% between 1990 and 2011, exceeding 660 million tonnes in 2011; the world-wide production of waste is estimated to grow further due to increasing GDP in developing economies. Given this scenario, effective treatment and recovery of wastes becomes a priority. In developed countries, MSW is usually sent to materials recovery facilities (MRFs), which use mechanical and manual sorting units to extract valuable components. In this work, we define a network flow model to represent a MRF that sorts wastes using multi-output...

  15. Delay characterization and prediction in major U.S. airline networks

    Hanley, Zebulon James
    This thesis expands on models that predict delays within the National Airspace System (NAS) in the United States. We propose a new method to predict the expected behavior of the NAS throughout the course of an entire day after only a few flying hours have elapsed. We do so by using k-means clustering to classify the daily NAS behavior into a small set of most commonly seen snapshots. We then use random forests to map the delay behavior experienced early in a day to the most similar NAS snapshot, from which we make our type-of-day prediction for the NAS. By...

  16. Multi-objective optimization of next-generation aircraft collision avoidance software

    Lepird, John R
    Developed in the 1970's and 1980's, the Traffic Alert and Collision Avoidance System (TCAS) is the last safety net to prevent an aircraft mid-air collision. Although TCAS has been historically very effective, TCAS logic must adapt to meet the new challenges of our increasingly busy modern airspace. Numerous studies have shown that formulating collision avoidance as a partially-observable Markov decision process (POMDP) can dramatically increase system performance. However, the POMDP formulation relies on a number of design parameters modifying these parameters can dramatically alter system behavior. Prior work tunes these design parameters with respect to a single performance metric. This...

  17. Faster fully polynomial approximation schemes for Knapsack problems

    Rhee, Donguk
    A fully polynomial time approximation scheme (FPTAS) is an algorithm that returns ... -optimal solution to a maximization problem of size n, which runs in polynomial time in both ... We develop faster FPTASs for several classes of knapsack problems. In this thesis, we will first survey the relevant literature in FPTASs for knapsack problems. We propose the use of floating point arithmetic rather than the use of geometric rounding in order to simplify analysis. Given a knapsack problem that yield an ... -optimal solution for disjoint subsets S and T of decision variables, we show how to attain ......

  18. Price incentives for online retailers using social media

    Rizzo, Ludovica
    In the era of Big Data, online retailers have access to a large amount of data about their customers. This data can include demographic information, shopping carts, transactions and browsing history. In the last decade, online retailers have been leveraging this data to build a personalized shopping experience for their customers with targeted promotions, discounts and personalized item recommendations. More recently, some online retailers started having access to social media data: more accurate demographic and interests information, friends, social interactions, posts and comments on social networks, etc. Social media data allows to understand, not only what customers buy, but also...

  19. Optimized air asset scheduling within a Joint Aerospace Operations Center (JAOC)

    Rossillon, Kevin Joseph
    In this thesis, we introduce and analyze models for air asset scheduling within a military theater. Specifically, we seek to create models that generate aircraft-specific schedules for Air Tasking Orders (ATOs) within a Joint Aerospace Operations Center (JAOC). A JAOC provides command and control of all air and space assets tasked to a particular region/area of responsibility (AOR) or strategic command. Scheduling these assets requires a high level of unified effort whereby centralized planning must be handled in a decentralized fashion and is known as the Air Tasking Cycle. Given the complexity of this process, subject matter experts from diverse...

  20. Dynamic prediction of terminal-area severe convective weather penetration

    Schonfeld, Daniel (Daniel Ryan)
    Despite groundbreaking technology and revised operating procedures designed to improve the safety of air travel, numerous aviation accidents still occur every year. According to a recent report by the FAA's Aviation Weather Research Program, over 23% of these accidents are weather-related, typically taking place during the takeoff and landing phases. When pilots fly through severe convective weather, regardless of whether or not an accident occurs, they cause damage to the aircraft, increasing maintenance cost for airlines. These concerns, coupled with the growing demand for air transportation, put an enormous amount of pressure on the existing air traffic control system. Moreover,...

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