Parithi Govindaraju

Profit Motivated Airline Fleet Allocation and Concurrent Aircraft Design for Multiple Airlines

A “System of Systems” (SoS) approach is particularly beneficial in analyzing complex large scale systems comprised of numerous independent systems – each capable of independent operations in their own right – that, when brought in conjunction, o↵er capabilities and performance beyond that of the individual systems. The variable resource allocation problem is a type of SoS problem, which includes the allocation of “yet-to-be-designed” systems along with existing resources and systems. The work here uses an airline as a type of system of systems and a new passenger aircraft, whose design requirements are not yet defined, as the variable resource. The methodology presented here expands upon earlier work that demonstrated a decomposition approach to simultaneously design a new aircraft and allocate this new aircraft along with existing aircraft in an e↵ort to meet passenger demand at minimum fleet level operating cost for a single airline. The result of this describes important characteristics of the new aircraft. The ticket price model developed and implemented here enables analysis of the system using profit maximization studies instead of cost minimization. A multi-objective problem formulation determines characteristics of a new aircraft that maximizes the profit of multiple airlines to recognize the fact that aircraft manufacturers sell their aircraft to multiple customers and seldom design aircraft customized to a single airline’s operations. The route network characteristics of two simple airlines serve as the example problem for the initial studies. The resulting problem formulation is a mixed–integer nonlinear programming problem, which is typically di cult to solve. A sequential decomposition strategy is applied as a solution methodology by segregating the allocation (integer programming) and aircraft design (nonlinear programming) subspaces. After solving a simple problem considering two airlines, the decomposition approach is then applied to two larger airline route networks representing actual airline operations in the year 2005. Results from the profit maximization studies with the ticket pricing model developed here favor a smaller aircraft in terms of passenger capacity due to its higher yield generation capability on shorter routes.

Platform Design for Fleet-Level Efficiency under Uncertain Demand: Application for Air Mobility Command (AMC)

The approach presented here combines approaches from multidisciplinary design optimization and operations research to improve energy efficiency-related defense acquisition decisions. The work focuses upon the acquisition of new aircraft for the US Air Force Air Mobility Command, which is the largest consumer of fuel in the Department of Defense. The approach here extends prior work in fleet-level acquisition decisions, in the context of Air Mobility Command, by explicitly considering uncertainty. The approach simultaneously selects requirements for a new cargo aircraft, predicts size, weight and performance of that new aircraft, and also allocates the new aircraft along with existing aircraft to meet cargo transportation demand. Fuel efficiency of the resulting fleet provides a metric for comparison. The approach, with the abstractions and assumptions used, successfully provides a description of a new cargo aircraft that impacts fleet-level metrics. The allocation problem incorporates scheduling-like features to account for time driven operational constraints. Results in this study demonstrate the approach for a simple three-route network and 22-base network, using the Air Mobility Command Global Air Transportation Execution System dataset.

Assessing Effects of Aircraft and Fuel Technology Advancement on Select Aviation Environmental Impacts

The ability to simultaneously assess airline operations, economics, and emissions would help evaluate the progress toward reduction of aviation’s environmental impact as outlined in the NASA Environmentally Responsible Aviation program. Furthermore, assessment of aircraft utilization by airlines would guide future policies and investment decisions on technologies most urgently required. This paper describes the development of the Fleet-Level Environmental Evaluation Tool, which is a computational simulation tool developed to assess the impact of new aircraft concepts and technologies on aviation’s impact on environmental emissions and noise. This tool uses an aircraft allocation model that represents the airlines’ profit-seeking operational decisions as a mixed-integer programming problem. The allocation model is embedded in a system-dynamics framework that mimics the economics of airline operations, models their decisions regarding retirement and acquisition of aircraft, and estimates market demand growt...

Optimized Military Transport Aircraft Design Through Multi-Objective Analysis of Fleet-Level Metrics Under Demand Uncertainty

Identifying optimal design requirements of new systems that operate along with existing systems to provide a set of overarching capabilities is challenging due to the tightly coupled effects that setting requirements on a system’s design (here, military transportation aircraft) can have on how the system is being used (here, how the aircraft is allocated to carry cargo on specified routes). This research builds on prior work to further develop a quantitative approach that generates optimum design requirements of new, yet-to-be-designed systems that, when serving alongside other systems, will optimize fleet-level objectives while considering the effect of demand uncertainties in the service network and specific payload capacity requirements for the new system. The approach is demonstrated for two example problems resembling missions of the USAF Air Mobility Command cargocarrying fleet. Solving the multi-objective formulation using the subspace decomposition framework provides a set of Pareto optimal solutions for different tradeoff opportunities between fleet-level cost and fleet-level productivity. The Pareto front enables the decisionmaker to select a desired balance of fleet-level cost and fleet-level productivity, and identify the corresponding optimized design of the new system.