2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
115
2 - Customized Offers In Airline Revenue Management
Michael Witmann, Massachusetts Institute of Technology,
Cambridge, MA, United States,
I propose an approach for decoupling the customized offer generation problem
from the well-studied airline revenue management (RM) problem. After
generating a baseline assortment of fare products and observing a passenger’s
characteristics, an airline can choose to customize that passenger’s offer by either
adjusting the products in the assortment or changing the offered prices for those
products. For implementation, heuristics are developed that are compatible with
the airline RM methods and systems currently in use at large airlines.
3 - Optimization Models For Speed Control In Air Traffic Management
James Jones, University of Maryland, College Park, MD,
United States,
We propose four sets of models that use speed control to enhance the level of
coordination by FAA managers at the tactical and pre-tactical level to account for
the uncertainty at the time of planning. The first approach, assumes control of all
airborne flights 500 nm from the destination airport while assuming no control
over flights originating less than 500 nm. The second assumes control over all
flights. In the third and fourth approach we propose enhancements for equitably
rationing airport access to carriers and new GDP control procedures and flight
operator planning models.
4 - Modeling In Air Transportation: Cargo Loading And
Itinerary Choice
Virginie Lurkin, University of Liege, Liege, Belgium,
We examine two problems as part of this presentation. The first is a cargo loading
problem. The aim is to load a set of containers and pallets into a cargo aircraft that
serves multiple airports. Our work is the first to model cargo transport as a series
of trips consisting of several legs at the end of which pickup and delivery
operations might occur. The second problem we examine involves the estimation
of itinerary choice models that include price variables and correct for price
endogeneity using a control function that uses several types of instrumental
variables.
SD63
Cumberland 5- Omni
Dynamic Routing and Logistics
Sponsored: TSL, Freight Transportation & Logistics
Sponsored Session
Chair: Nicholas Kullman, University of Washington, Seattle, WA,
United States,
1 - Dynamic Pickup And Delivery Problem With Transfers
Afonso H. Sampaio, Eindhoven University of Technology,
Eindhoven, Netherlands,
Lucas Petrus Veelenturf, Tom Van Woensel
We consider the Dynamic Pickup and Delivery Problem with Transfers (d-PDP-T)
in which a set of transportation requests arrive in real-time and must be assigned
to a fleet of vehicles. Unlike most variants of the PDP, the pairing constraint is not
hard in the d-PDP-T and requests can be transferred from one vehicle to another
at transfer locations. Our research focus is to address the operational issues and to
evaluate costs/benefits when such transfers are introduced in a dynamic
environment. It is especially relevant for transportation companies that provide
on-demand services and that need to plan several service requests per day. We
discuss some preliminary modelling and solution approaches.
2 - Anticipatory Preemptive Depot Revisits For A Dynamic Same-day
Delivery Problem
Dirk Mattfeld, TU Braunschweig, Braunschweig, Germany,
Marlin Wolf Ulmer, Barrett Thomas
We consider a single-vehicle stochastic and dynamic one-to-many pickup and
delivery problem (SDPD) motivated by a same-day delivery application. An
uncapacitated vehicle delivers goods from a depot to customers during a shift.
Dynamic customer orders occur stochastically within the shift. Before serving
these orders, the vehicle revisits the depot to pick up the according goods. Since
the shift is limited, not every order can be assigned to the vehicle. Objective is to
maximize the number of assigned orders. For the SDPD, we present an
anticipatory preemptive depot revisit policy (APDR) based on approximate value
iteration. We show how APDR significantly increases the number of assignments.
3 - Electric Vehicle Routing With Mid-route Recharging And
Uncertain Charging Station Availability
Nicholas Kullman, University of Washington,
Justin Goodson, Jorge E Mendoza
We consider the problem of routing a single electric vehicle (EV) and allow for
mid-route recharging at stations with uncertain availability. The uncertainty in
charging station availability complicates the planning of mid-route recharging,
which is necessitated by EVs’ restricted driving ranges; longer recharging times for
EVs compound this difficulty. We present a stochastic dynamic programming
approach to route planning that hedges against these uncertainties.
4 - Joint Capacity Logistics And Inventory Control Of Mobile Modular
Production Systems
Satya Sarvani Malladi, Georgia Institute of Technology,
Alan Erera, Chelsea C White III
Mobile modular production systems enable better response to spatial and
temporal variations in demand. How should the logistics of such systems be
planned taking into account uncertainty of demand? We try to evaluate value
added by mobile modular production through several approaches.
SD64
Cumberland 6- Omni
Evolutionary Bilevel Multi-criterion Optimization
Methods and Applications
Sponsored: Multiple Criteria Decision Making
Sponsored Session
Chair: Kalyanmoy Deb, Professor, Michigan State University, 428 S.
Shaw Lane, 2120 EB, Michigan State University, East Lansing, MI,
48824, United States,
1 - Impacts Of Climate Uncertainty On A Bilevel Optimization
Framework For Targeting Agricultural Conservation Policy
Moriah Bostian, Lewis and Clark College,
We characterize the problem of spatially targeting agricultural conservation
practices to improve water quality as a multiobjective bilevel optimization
problem, integrating a biophysical model of the watershed with an economic
production model to estimate policy costs. Weather is an important driver of
water quality and agricultural production. We solve for the Pareto frontier for
water and production objectives under changing climate conditions, based on a
range of leading climate projections. We use the solution values to assess the
robustness of policy targets to climate uncertainty.
2 - Solving Optimistic Bilevel Programs By Iteratively Approximating
Lower Level Optimal Value Function
Pekka Malo, Aalto University School of Buisness,
, Kalyanmoy Deb, Ankur Sinha
The difficulties in bilevel programming arise primarily from the nested structure
of the problem. In this paper, we propose a metamodeling based solution strategy
that attempts to iteratively approximate the optimal lower level value function.
3 - Optimal Allocation Of Restoration Practices Using Indexes For
Stream Health
Brad Barnhart, U.S. EPA ORD/NHEERL/WED/EEB,
The optimal placement of agricultural and urban (i.e., green infrastructure)
management practices in order to achieve both economic and environmental
objectives is a commonly posed problem. However, the majority of studies seek to
optimize objectives related to intermediary environmental outputs (e.g., N and P
nutrient loadings, stream temperature, sediment concentrations) and do not
address impacts on overall indexes of stream health. Therefore, we investigate on
how best to include indexes within a bi-level optimization framework to better
characterize objectives when targeting management practices.
4 - Robust And Reliability-based Bi-level Multi-criterion Optimization
Zhichao Lu, Michigan State University,
Practical optimization and decision making problems involve uncertainties in
decision variables and parameters. In this talk, we shall suggest robust and
reliability based methods for bilevel problems using evolutionary methods.
Results on two practical methods will be presented.
SD64