This document and trademark(s) contained herein are protected by law. This representation of RAND intellectual property is provided for noncommercial use only. Unauthorized posting of this publication online is prohibited. Permission is given to duplicate this document for personal use only, as long as it is unaltered and complete. Permission is required from RAND to reproduce, or reuse in another form, any of its research documents for commercial use. For information on reprint and linking permissions, please visit www.rand.org/pubs/permissions. The RAND Corporation is a research organization that develops solutions to public policy challenges to help make communities throughout the world safer and more secure, healthier and more prosperous. RAND is nonprofit, nonpartisan, and committed to the public interest.RAND's publications do not necessarily reflect the opinions of its research clients and sponsors. Support RANDMake a tax-deductible charitable contribution at www.rand.org/giving/contribute www.rand.org For more information on this publication, visit www.rand.org/t/RR2482Library of Congress Cataloging-in-Publication Data is available for this publication.

No abstract

No abstract

The research in this report is intended to inform implementation of the Puerto Rico recovery plan, Transformation and Innovation in the Wake of Devastation: An Economic and Disaster Recovery Plan for Puerto Rico. Under contract with the Federal Emergency Management Agency (FEMA), the Homeland Security Operational Analysis Center (HSOAC) provided substantial support in developing that recovery plan by soliciting and integrating input from a wide variety of stakeholders, contributing analysis where needed, and supporting drafting of the plan. The plan included an overview of damage and needs, courses of action (COAs) to meet those needs, costs of the COAs, and potential funding mechanisms for those costs.After completing the recovery plan, HSOAC was tasked to study whether the logistics capacity of Puerto Rico would support the anticipated increase in imports of materials for use in funded recovery projects. The research focused on available capacity to import the materials anticipated to stress the logistics system, large and heavy items. These items are imported to Puerto Rico via the seaborne logistics system. This report should be of interest to FEMA, the government of Puerto Rico, and individuals active in performing work as part of the Puerto Rico recovery plan.This research was sponsored by FEMA and conducted within the Strategy, Policy, and Operations Program of the HSOAC federally funded research and development center (FFRDC). More information about HSOAC's contribution to planning for recovery in Puerto Rico, along with links to other reports being published as part of this series, can be found at www.rand.org/hsoac/puerto-rico-recovery.Comments or questions on this draft report should be addressed to the project leaders,

This paper presents a search algorithm based framework to calibrate origin-destination (O-D) market specific airline ticket demands and prices for the Air Transportation System (ATS). This framework is used for calibrating an agent based model of the air ticket buy-sell process -Airline Evolutionary Simulation (Airline EVOS) -that has fidelity of detail that accounts for airline and consumer behaviors and the interdependencies they share between themselves and the NAS. More specificially, this algorithm simultaneous calibrates demand and airfares for each O-D market, to within specified threshold of a pre-specified target value. The proposed algorithm is illustrated with market data targets provided by the Transportation System Analysis Model (TSAM) and Airline Origin and Destination Survey (DB1B). Although we specify these models and datasources for this calibration exercise, the methods described in this paper are applicable to calibrating any low-level model of the ATS to some other demand forecast model-based data. We argue that using a calibration algorithm such as the one we present here to synchronize ATS models with specialized forecast demand models, is a powerful tool for establishing credible baseline conditions in experiments analyzing the effects of proposed policy changes to the ATS. Nomenclature α= price elasticity of demand λ = multiplier for airfare of non-stop itineraries A = advertised airfare B = basefare d = number of days to travel date l = load-factor (ratio of sold to total number of available seats)