2016 INFORMS Annual Meeting Program

SD64

INFORMS Nashville – 2016

2 - Customized Offers In Airline Revenue Management Michael Witmann, Massachusetts Institute of Technology, Cambridge, MA, United States, wittman@mit.edu 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, jonesjc1@umd.edu 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, vlurkin@ulg.ac.be 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, Nick.Kullman@gmail.com 1 - Dynamic Pickup And Delivery Problem With Transfers Afonso H. Sampaio, Eindhoven University of Technology, Eindhoven, Netherlands, A.H.Sampaio.Oliveira@tue.nl, 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 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. Dirk Mattfeld, TU Braunschweig, Braunschweig, Germany, d.mattfeld@tu-bs.de, Marlin Wolf Ulmer, Barrett Thomas

3 - Electric Vehicle Routing With Mid-route Recharging And Uncertain Charging Station Availability Nicholas Kullman, University of Washington, nkullman@uw.edu 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, mss@gatech.edu, 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, kdeb@egr.msu.edu 1 - Impacts Of Climate Uncertainty On A Bilevel Optimization Framework For Targeting Agricultural Conservation Policy Moriah Bostian, Lewis and Clark College, mbbostian@lclark.edu 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 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, bradleybarnhart@gmail.com 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, mikelzc1990@gmail.com 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. Pekka Malo, Aalto University School of Buisness, pekka.malo@aalto.fi, Kalyanmoy Deb, Ankur Sinha

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