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Publisher Summary This chapter discusses problems related to the management of air traffic and airline operations for minimizing the impact and cost of disruptions. Flight and crew schedules and passenger itineraries have become... more
Publisher Summary This chapter discusses problems related to the management of air traffic and airline operations for minimizing the impact and cost of disruptions. Flight and crew schedules and passenger itineraries have become increasingly fragile because of the growing complexity of the air transportation system and the tight coupling of its various elements. The resulting direct and indirect economic costs are very large, certainly amounting to several billion dollars annually. The airline industry has a vital stake in research aimed at mitigating the effects of severe weather and other disruptive events and at expediting recovery from irregular operations. A significant body of recent and ongoing work has led to major progress toward these objectives. Two breakthrough developments have been the primary drivers behind this progress. First, collaborative decision making has made it possible to apply the principles of information sharing and distributed decision making to air traffic flow management (ATFM) by expanding the databases available to airline and Federal Aviation Administration (FAA) traffic flow managers, by creating common situational awareness, and by introducing shared real-time tools and procedures. Second, there is growing recognition in the airline industry of the fact that planning for schedule robustness and reliability may be just as important as planning for minimizing costs in the complex, highly stochastic, and dynamic environment of air transportation.
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Abstract: Many of the existing methods for evaluating an airline's on-time performance are based on flight-centric measures of flight delay. However, recent research has demonstrated that as much as 50% of passenger delays are caused... more
Abstract: Many of the existing methods for evaluating an airline's on-time performance are based on flight-centric measures of flight delay. However, recent research has demonstrated that as much as 50% of passenger delays are caused by passenger travel disruptions, either flight cancelations or missed connections. The propensity for disruptions varies significantly across airports and carriers, based on key factors such as scheduling practices, network structures, and passenger connections. In this paper, we analyze the causes and costs of ...
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Logistics is the cost aware planning, design, and control of material flow and related information flow (persons, energy, money, information, ...) in production processes. The notion is often used as a synonym for transportation,... more
Logistics is the cost aware planning, design, and control of material flow and related information flow (persons, energy, money, information, ...) in production processes. The notion is often used as a synonym for transportation, distribution, or warehouse management. The topic is of a rich variety, has great practical importance , and attracts researchers from the computer science (CS), mathematical programming (MP), and the operations research (OR) communities alike. Today, problems from logistics are widely studied as parts of the disciplines of mathematical programming and operations research; algorithmics and theoretical computer science; and computer systems. The specific models and methods , as well as the objectives to be optimized, differ in the various disciplines; nevertheless, there are remarkable similarities (as well as significant differences) in the general framework adopted by researchers in logistics in these disparate disciplines. The primary objectives of the sem...
Developed and analyzed discrete choice models with latent variables/classes Clip-Air concept: Integrated schedule planning for a new generation of aircraft, 2010-2013 Project manager Bilge (Küçük) Atasoy 2 Developed airline schedule... more
Developed and analyzed discrete choice models with latent variables/classes Clip-Air concept: Integrated schedule planning for a new generation of aircraft, 2010-2013 Project manager Bilge (Küçük) Atasoy 2 Developed airline schedule planning and fleet assignment models for the new aircraft, compared its per-formance to standard aircraft. MyTosa: Simulation tool for the dimensioning, commercial promotion and case study set-up for ABB’s rev-
The Container Relocation Problem (CRP), also called Block Relocation Problem (BRP), is concerned with finding a sequence of moves of containers that minimizes the number of relocations needed to retrieve all containers, while respecting a... more
The Container Relocation Problem (CRP), also called Block Relocation Problem (BRP), is concerned with finding a sequence of moves of containers that minimizes the number of relocations needed to retrieve all containers, while respecting a given order of retrieval. The restricted CRP enforces that only containers blocking the target container can be relocated. We improve upon and enhance an existing binary encoding and using it, formulate the restricted CRP as a binary integer programming problem in which we exploit structural properties of the optimal solution. This integer programming formulation reduces significantly the number of variables and constraints compared to existing formulations. Its efficiency is shown through computational results on small and medium sized instances taken from the literature.
Problem definition: Physical distancing requirements during the COVID-19 pandemic have dramatically reduced the effective capacity of university campuses. Under these conditions, we examine how to make the most of newly scarce resources... more
Problem definition: Physical distancing requirements during the COVID-19 pandemic have dramatically reduced the effective capacity of university campuses. Under these conditions, we examine how to make the most of newly scarce resources in the related problems of curriculum planning and course timetabling. Academic/practical relevance: We propose a unified model for university course scheduling problems under a two-stage framework and draw parallels between component problems while showing how to accommodate individual specifics. During the pandemic, our models were critical to measuring the impact of several innovative proposals, including expanding the academic calendar, teaching across multiple rooms, and rotating student attendance through the week and school year. Methodology: We use integer optimization combined with enrollment data from thousands of past students. Our models scale to thousands of individual students enrolled in hundreds of courses. Results: We projected that ...
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The mission of The Journal of General Physiology is to publish articles that elucidate basic biological, chemical, and physical principles of broad physiological significance. Physiological significance usually means mechanistic insights,... more
The mission of The Journal of General Physiology is to publish articles that elucidate basic biological, chemical, and physical principles of broad physiological significance. Physiological significance usually means mechanistic insights, which often are obtained only after extensive analysis of the experimental results. The significance of the mechanistic insights therefore can be no better than the validity of the theoretical framework used for the analysis—and it is usually better to be vaguely right than precisely wrong. The uncertainties associated with data analysis are well illustrated in the Perspectives on Ion Permeation through membrane-spanning channels ( J . Gen . Physiol . 113:761– 794) and the related Letters-to-the-Editor in this issue. This exchange moreover identified a particular problem that can be resolved by a change in editorial policy. The problem is the graphic representation of the results of kinetic analyses of ion permeation based on discrete-state rate mo...
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The container relocation problem (CRP) is concerned with finding a sequence of moves of containers that minimizes the number of relocations needed to retrieve all containers, while respecting a given order of retrieval. However, the... more
The container relocation problem (CRP) is concerned with finding a sequence of moves of containers that minimizes the number of relocations needed to retrieve all containers, while respecting a given order of retrieval. However, the assumption of knowing the full retrieval order of containers is particularly unrealistic in real operations. This paper studies the stochastic CRP, which relaxes this assumption. A new multistage stochastic model, called the batch model, is introduced, motivated, and compared with an existing model (the online model). The two main contributions are an optimal algorithm called Pruning-Best-First-Search (PBFS) and a randomized approximate algorithm called PBFS-Approximate with a bounded average error. Both algorithms, applicable in the batch and online models, are based on a new family of lower bounds for which we show some theoretical properties. Moreover, we introduce two new heuristics outperforming the best existing heuristics. Algorithms, bounds, and ...
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Airlines and high speed rail are increasingly competing for passengers, especially in Europe and Asia. Competition between them affects the number of captured passengers and, therefore, revenues. We consider competition between airlines... more
Airlines and high speed rail are increasingly competing for passengers, especially in Europe and Asia. Competition between them affects the number of captured passengers and, therefore, revenues. We consider competition between airlines (legacy and low-cost) and high speed rail. We develop a new approach that generates airline schedules using an integrated mixed integer, nonlinear optimization model that captures the impacts of airlines’ decisions on passenger demand. We estimate the demand associated with a given schedule using a nested logit model. We report our computational results on realistic problem instances of the Spanish airline IBERIA and show that the actual airline schedules are found to be reasonably close to the schedules generated by our approach. Next, we use this optimization modeling approach under multimodal competition to evaluate multiple scenarios involving entry of high speed rail into new markets. We account for the possibility of demand stimulation as a res...
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Given a schedule of flight legs to be flown by an airline, the fleet assignment problem is to determine the minimum cost assignment of flights to aircraft types, called fleets, such that each scheduled flight is assigned to exactly one... more
Given a schedule of flight legs to be flown by an airline, the fleet assignment problem is to determine the minimum cost assignment of flights to aircraft types, called fleets, such that each scheduled flight is assigned to exactly one fleet, and the resulting assignment is feasible to fly given a limited number of aircraft in each fleet. Then the airline must determine a sequence of flights, or routes, to be flown by individual aircraft such that assigned flights are included in exactly one route, and all aircraft can be maintained as necessary. This is referred to as the aircraft routing problem. In this paper, we present a single model and solution approach to solve simultaneously the fleet assignment and aircraft routing problems. Our approach is robust in that it can capture costs associated with aircraft connections and complicating constraints such as maintenance requirements. By setting the number of fleets to one, our approach can be used to solve the aircraft routing probl...
Research Interests: Mathematics, Applied Mathematics, Computer Science, Routing, Scheduling, and 14 moreTransportation, Algorithm, Traffic Management, Simulation, Numerical Simulation, Stress analysis, Air Transportation, Concept, Cost Analysis, Schedule, Transportation Network, Transportation Science, Stress Analysis, and Air traffic
Airline crew scheduling is concerned with finding a minimum cost assignment of flight crews to a given flight schedule while satisfying restrictions dictated by collective bargaining agreements and the Federal Aviation Administration.... more
Airline crew scheduling is concerned with finding a minimum cost assignment of flight crews to a given flight schedule while satisfying restrictions dictated by collective bargaining agreements and the Federal Aviation Administration. Traditionally, the problem has been modeled as a set partitioning problem. In this paper, we present a new model based on breaking the decision process into two stages. In the first stage we select a set of duty periods that cover the flights in the schedule. Then, in the second stage, we attempt to build pairings using those duty periods. We suggest a decomposition approach for solving the model and present computational results for test problems provided by a major carrier. Our formulation provides a tighter linear programming bound than that of the conventional set partitioning formulation but is more difficult to solve.
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Executive Summary Flight delay is a serious and widespread problem in the United States. Increasing flight delays place a significant strain on the US air travel system and cost airlines, passengers, and society at many billions of... more
Executive Summary Flight delay is a serious and widespread problem in the United States. Increasing flight delays place a significant strain on the US air travel system and cost airlines, passengers, and society at many billions of dollars each year. While a number of previous studies have attempted to estimate the total economic impact of delays, scientific knowledge about the cost of delay is still limited. The Federal Aviation Administration sponsored the five NEXTOR universities and the Brattle Group to conduct a ...
Research Interests: Applied Mathematics, Mathematical Programming, Integer Programming, Mathematical, Mathematical Optimization, and 10 moreBranch and Bound, Large Scale Optimization, Degeneration, Numerical Analysis and Computational Mathematics, Assignment Problem, Large Scale, Integer Program, LINEAR PROGRAM, Interior Point Algorithm, and Set partitions
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The airline industry has a long history of developing and applying optimization approaches to their myriad of scheduling problems. These problems have several challenging characteristics, the two most challenging of which include: 1) they... more
The airline industry has a long history of developing and applying optimization approaches to their myriad of scheduling problems. These problems have several challenging characteristics, the two most challenging of which include: 1) they span long- and short-term horizons, from strategic planning of flight schedules operated several months into the future, to real-time operations in which strategies must be developed and implemented immediately to recover scheduled operations from disruptions; and 2) they include multiple resources that must be coordinated, such as aircraft, crews, and passengers. While optimization approaches have been essential to the airline industry and effective in developing aircraft and crew schedules, historical models and approaches often fail to capture the complexity of airline operations. For example, approaches, often by necessity, involve a sequential, rather than an integrated process to develop schedules for aircraft and crews, and moreover, the pro...
Abstract: A new passenger-centric metric is presented for both addressing the shortcomings of existing flight-based metrics and more accurately evaluating schedule reliability. A Passenger Delay Calculator (PDC) was developed using... more
Abstract: A new passenger-centric metric is presented for both addressing the shortcomings of existing flight-based metrics and more accurately evaluating schedule reliability. A Passenger Delay Calculator (PDC) was developed using passenger bookings and flight ...
ABSTRACT Building robust airline scheduling models involves constructing schedules and routes with reduced levels of both flight delays and passenger and crew disruptions. This might be achieved by building plans that require fewer... more
ABSTRACT Building robust airline scheduling models involves constructing schedules and routes with reduced levels of both flight delays and passenger and crew disruptions. This might be achieved by building plans that require fewer recovery actions, or that decrease the complexity or cost of recovery. In this paper, we study different classes of models to achieve robust airline scheduling solutions. We focus on the aircraft routing problem, a step of the airline scheduling process. In particular, we study two general classes of robust models and one tailored approach that uses domain knowledge to guide the solution process. The general classes of models are (i) extreme-value based, and (ii) chance-constrained or probability-based. We first show how the general models can be applied to the aircraft routing problem. Then, based on model structure and tractability considerations, we suggest extensions to the general models, capturing domain knowledge and reducing the need to iterate and re-solve the models. The extended models and insights gleaned in this work apply not only to the aircraft routing model but also to the broad class of large-scale, network-based, resource allocation. We provide extended formulations for our extended models in the appendices. We discuss how general and tailored models are similar or different with respect to modeling, complexity and tractability, and we compare solution performance with respect to the robustness metrics of interest.
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ABSTRACT We introduce a new model and mathematical formulation for planning crane moves in the storage yard of container terminals. Our objective is to develop a tool that captures customer centric elements, especially service time, and... more
ABSTRACT We introduce a new model and mathematical formulation for planning crane moves in the storage yard of container terminals. Our objective is to develop a tool that captures customer centric elements, especially service time, and helps operators to manage costly relocation moves. Our model incorporates several practical details and provides port operators with expanded capabilities including planning repositioning moves in off-peak hours, controlling wait times of each customer as well as total service time, optimizing the number of relocations and wait time jointly, and optimizing simultaneously the container stacking and retrieval process. We also study a class of flexible service policies which allow for out-of-order retrieval. We show that under such flexible policies, we can decrease the number of relocations and retrieval delays without creating inequities.
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The focus of this research is to model and solve a large-scale service network design problem involving express package delivery. The objective is to find the cost minimizing movement of packages from their origins to their destinations,... more
The focus of this research is to model and solve a large-scale service network design problem involving express package delivery. The objective is to find the cost minimizing movement of packages from their origins to their destinations, given very tight service windows, limited ...
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ABSTRACT From June 21 to June 26, 2009, the Dagstuhl Seminar 09261 on Models and Algorithms for Optimization in Logistics was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several... more
ABSTRACT From June 21 to June 26, 2009, the Dagstuhl Seminar 09261 on Models and Algorithms for Optimization in Logistics was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available. @InProceedings{barnhart_et_al:DSP:2009:2175, author = {Cynthia Barnhart and Uwe Clausen and Ulrich Lauther and Rolf H. M{"o}hring}, title = {09261 Executive Summary -- Models and Algorithms for Optimization in Logistics}, booktitle = {Models and Algorithms for Optimization in Logistics}, year = {2009}, editor = {Cynthia Barnhart and Uwe Clausen and Ulrich Lauther and Rolf H. M{"o}hring}, number = {09261}, series = {Dagstuhl Seminar Proceedings}, ISSN = {1862-4405}, publisher = {Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, Germany}, address = {Dagstuhl, Germany}, URL = {http://drops.dagstuhl.de/opus/volltexte/2009/2175}, annote = {Keywords: Logistics, optimization, transport} }
... PAMELA H. VANCE Goi-ueta Business School, Emory University, Atlanta, Georgia 30322, pamelawvance@bus.einory.edu (Received November 1997; revision received July 1998 ... Vk is the volume of commodity k. * (a is the incidence indicator... more
... PAMELA H. VANCE Goi-ueta Business School, Emory University, Atlanta, Georgia 30322, pamelawvance@bus.einory.edu (Received November 1997; revision received July 1998 ... Vk is the volume of commodity k. * (a is the incidence indicator that equals 1 if arc a is on path q ...
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Haya Shida, Subscribe (Full Service), Register (Limited Service, Free), Login. Search: The ACM Digital Library The Guide. ...
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... CYNTHIA BARNHART Massachusetts Institute of Technology, Cambridge, MassachusettsLEVENT HATAY American Airlines Decision Technologies, Dallas/Fort Worth Airport, Texas ... ate = at +y*inc, fory = minconnect, minconnect + 1, ...,... more
... CYNTHIA BARNHART Massachusetts Institute of Technology, Cambridge, MassachusettsLEVENT HATAY American Airlines Decision Technologies, Dallas/Fort Worth Airport, Texas ... ate = at +y*inc, fory = minconnect, minconnect + 1, ..., maxrest, where ...
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Airlines schedules are built such as to maximize expected profit. Such schedules turn out to be more sensitive to delay propagation and have lower on-time performance. Robust schedules are thus used instead. In this paper, we compare two... more
Airlines schedules are built such as to maximize expected profit. Such schedules turn out to be more sensitive to delay propagation and have lower on-time performance. Robust schedules are thus used instead. In this paper, we compare two different approaches to derive robust schedules, being either based on historical data or not. We show how the way historical data is considered affects the solutions quality.
ABSTRACT Airline scheduling is characterized by numerous complexities, including a network of flights, different aircraft types, limited numbers of gates, air traffic control restrictions, environmental regulations, strict safety... more
ABSTRACT Airline scheduling is characterized by numerous complexities, including a network of flights, different aircraft types, limited numbers of gates, air traffic control restrictions, environmental regulations, strict safety requirements, a myriad of crew work rules and complicated payment structures, and competitive, dynamic environments in which passenger demands are uncertain and pricing strategies are complex. This, layered with the airline industry’s endemic issues of low profitability, contentious labor issues, and outdated and inadequate infrastructure, poses daunting challenges that have intrigued operations researchers for at least a half-century, and have provided a fertile ground for the development and application of models and algorithms. In this talk, we first briefly summarize the optimization-based accomplishments in this area, highlighting the significant successes and impacts. While impressive, the problem is far from solved today. The focus of this talk, then, is on the many remaining opportunities and challenges, namely: a) Robust scheduling: A trend in airline scheduling is to generate schedules that are “robust” to the disruptions that plague airline operations. Because airlines have typically constructed schedules with the assumption that every flight departs and arrives as planned, plans are frequently disrupted and airlines often incur significant additional costs beyond those originally planned. A more robust plan can reduce the occurrence and impact of these disruptions. b) Dynamic scheduling: Stochasticity of passenger demands is a major challenge for the airlines in their quest to produce profit-maximizing schedules. Even using sophisticated optimization tools, many flights upon departure have empty seats, while others suffer a lack of seats to accommodate passengers who desire to travel. One approach to this challenge is to implement dynamic scheduling approaches that re-optimize elements of the flight schedule during the passenger booking process, recognizing that demand forecast quality for a particular date improves as the date approaches. c) Recovery from irregular operations: We describe approaches designed for use in near real-time mode to adjust operations in response to a variety of disruptions. We present briefly some of the market-based mechanisms being considered to address this problem, with a particular focus on minimizing disruption and delay to passengers.
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Abstract: Service network design is critical to the profitability of expressshipment carriers. In this paper, we consider the problem of designingthe integrated service network for premium and deferred expressshipment delivery. Related... more
Abstract: Service network design is critical to the profitability of expressshipment carriers. In this paper, we consider the problem of designingthe integrated service network for premium and deferred expressshipment delivery. Related existing models adapted to this problem areintractable for realistic problem instances, requiring excessive computermemory and solution times. We extend existing models and introducea new approach to solve the resulting