12 research outputs found
Statistical Decisions in Aircraft Service = Statistiskie risinājumi lidaparātu apkalpes procesā
No full textEstimation of warranty period for structural components of aircraft
No full textOne of the most important problems in fatigue analysis and design of aircraft structures is the prediction of fatigue crack growth in service. Available in‐service inspection data for various types of aircraft indicate that the fatigue crack damage accumulation in service involves considerable statistical variability. In this paper, we consider the problem of estimating the minimum time to crack initiation (or warranty period) for a number of aircraft structural components, before which no cracks (that may be detected) in materials occur, based on the results of previous warranty period tests on the structural components in question. This problem is a special case of a general class of problems concerned with the analysis of fatigue crack damage accumulation in aircraft service. The technique proposed here for solving this problem emphasizes pivotal quantities relevant for obtaining ancillary statistics. Attention is restricted to invariant families of distributions. Numerical examples are given.
First Published Online: 14 Oct 201
Optimizing Inventory Control from the Past Data via Statistical Decision Equivalence Principle = Uz pagātnes datiem balstīta krājumu vadības optimizācija ar statistisko lēmumu ekvivalences principu izmantošanu
No full textLower and Upper Prediction Limits for Future Samples from a Weibull Distribution with Some Applications = Apakšējā un augšējā prognozēšanas robeža nākamajām Veibulu sadalījuma izlasēm ar vairākiem pielikumiem
No full textClassification of Radar Target via Data Samples = Radiolokāciju mērķu klasifikācija pamatojoties uz pamatizvēles datiem
No full textOptimal allocation of airplanes to routes
No full textIn this paper, we introduce a model that can assist airline planners in deploying their fleets as efficiently as possible. Specifically, we outline an optimization model that assigns a fleet of aircraft of different types to routes to maximize profits. An algorithm for solving nonlinear transportation problem is suggested. It is based on the use of Lagrange multipliers. We define and illustrate the use of the loss function, the cost structure of which is piecewise linear. The necessary and sufficient conditions for optimality are given. To illustrate the proposed approach, a numerical example is given.
First Published Online: 14 Oct 201
Optimal airline seat inventory control for multi‐leg flights
No full textAirline seat inventory control is about “selling the right seats to the right people at the right time”. In this paper, the problem of determining optimal booking policy for multiple fare classes in a pool of identical seats for multi‐leg flights is considered. During the time prior to departure of a multi‐leg flight, decisions must be made concerning the allocation of reserved seats to passengers requesting space on the full or partial spans of the flight. It will be noted that in the case of multi‐leg flights the long‐haul passengers are often unable to obtain seats because the shorter‐haul passengers block them. For large commercial airlines, efficiently setting and updating seat allocation targets for each passenger category on each multi‐leg flight is an extremely difficult problem. This paper presents static and dynamic models of airline seat inventory control for multi‐leg flights with multiple fare classes, which allow one to maximize the expected contribution to profit. The dynamic model uses the most recent demand and capacity information and allows one to allocate seats dynamically and anticipatorily over time.
First Published Online: 14 Oct 201
