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## Improving Revenue by System Integration and Cooperative Optimization

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**Improving Revenue bySystem Integration andCooperative**Optimization Reservations & Yield Management Study Group Annual Meeting Berlin 16 - 19 April 2002 Georg Kliewer Sven Grothklags Klaus Weber UNIVERSITY of PADERBORN**Motivation - Planning Processes**MarketModeling FleetAssignment Crew Pairing NetworkDesign OperationControl AircraftRotation RevenueManagement Crew Rostering**Agenda**• Fleet Assignment Problem • Business Process • Mathematical Model • Optimisation Algorithm • O&D Revenue Management • Current System Integration • System Integration Approaches • Conclusions**Fleet Assignment - Business Process**Development SchedulingActivity OperationsControl NetLineApplication NetLine/Plan NetLine/Sched NetLine/Ops weekly fully-dated • Find most Profitable Subfleet Assignment • Use a Subfleet that is Feasible for each Leg • Use the Existing Fleet and no extra Aircraft • Obey Blocktime and Groundtime Constraints Fleet Assignment**Strategic Profitability Evaluation Model**• Strategic-PEM is a forecasting model that measures the network profitability contribution of each schedule scenario • The Strategic PEM forecasts are developed on an O&D basis for a representative week for a schedule period • Input Data: • average revenue for the O&Ds • market demand for the O&Ds • cost model • fleeted schedule • Output Data: • overall schedule profitability • profit information for each leg-subfleet combination**Strategic Profitability Evaluation Model (cont)**Profitability Evaluation Model Fleet Assignment schedule av. revenues market demand Connection Builder itineraries Market Share Model assignment unconstrained demand prelim. capacity assignment Spill & Recapture Simulated Annealing constrained passenger flow Revenue & CostEstimation objective function for fleet assignment**Fleet Assignment - Mathematical Model**PAD leg l xl,f=1 leg l is assigned to subfleet f FRA yv,v+: aircraft flow on the ground xl,f yv,v+ MUC v- v v+ ground arc (v-,v) flight event**Fleet Assignment - Optimisation Algorithm**Profitability Evaluation Model Fleet Assignment finalassignment fleet schedule restrictions Update Solution GenerateNeighbor Solution Simulated Annealing Objective Function Accept/Reject**Fleet Assignment - Optimisation Algorithm**• Heuristic solution method based on local search S= initial solution T = warming_up do do Snew = neighbor solution (S) cost = cost(Snew) - cost(S) if (cost < 0 or accept(cost,T) ) S = Snew until equilibrium T = update(T) until frozen 1 Equilibrium P Frozen**Agenda**• Fleet Assignment Problem • O&D Revenue Management • Business Process • System Overview • O&D Control Parameters • Current System Integration • System Integration Approaches • Conclusions**O&D Revenue Management – Business Process**BusinessActivities Development Pricing Revenue Management OperationsControl Application NetLine/Plan NetLine/Sched NetLine/Price ProfitLine NetLine/Ops**GDS**GDS O&D Forecast Engine Forecast Building ForecastInterface DB GDS Inventory ... Demand Forecasts O&D Optimiser GDS Control Parameters OptimiserInterface DB O&D Revenue Management – System Overview Forecasts based on either • booking histories • e.g. ODIF POSbooking limits • or • market model and price elasticity model • e.g. fare buckets • or • both**Œ** O&D Revenue Management – O&D Control Parameters Parameters to beused by fleet assignment process O&D control parameters depend on type of optimizer • EMSR varieties • booking class limits per leg / compartment • on various granularity levels, e.g. ODIF POS • bid prices derived from EMSR curve or approximation • fare bucket limits per leg / compartment • revenue bucket limits per leg / compartment • Dynamic programming • bid prices per leg / compartment • booking class limits derived from bid prices Reflect • demand • demand variability • estimated fares**Agenda**• Fleet Assignment Problem • O&D Revenue Management • Current System Integration • Cooperative Approach • System Integration Approaches • Conclusions**Current System Integration - Cooperative Approach**Profitability Evaluation Model Fleet Assignment Connection Builder itineraries FinalAssignment Market Share Model 1 unconstrained demand 4 Update Solution Fleet Change on a Leg Sequence capacity assignment Simulated Annealing Spill & Recapture 5 3 constrained passenger flow Accept/Reject Revenue & CostEstimation 6 2 Objective Function**Current System Integration - Cooperative Approach (cont)**State • Strategic PEM + Fleet Assignment NetLine/Plan • Tactical PEM + Fleet Assignment NetLine/Sched • fully-dated schedule • Basic O&D Fleet Assignment • Approximative revenue estimation • Fast evaluation loop: essential for Simulated Annealing • even faster with internal feedback by passenger flow model**Agenda**• Fleet Assignment Problem • O&D Revenue Management • Current System Integration • System Integration Approaches • Internal Feedback • External Feedback by O&D Revenue Management System • System View • Conclusions**System Integration – Internal Feedback**Profitability Evaluation Model Fleet Assignment Connection Builder FinalAssignment itineraries Market Share Model 1 3 unconstrained demand Update Solution Fleet Change on a Leg Sequence 4 capacity assignment Simulated Annealing Spill & Recapture Passenger Flow LP-Model passenger flow Accept/Reject Revenue & CostEstimation Dual Variables for Legs 2 5 Objective Function**System Integration – External Feedback by O&D RMS**Profitability Evaluation Model Fleet Assignment O&D Revenue Management FinalAssignment Connection Builder itineraries O&DForecast Engine Market Share Model Update Solution O&D Forecasts unconstrained demand Fleet Change on a Leg Sequence Simulated Annealing Capacity Assignment capacity assignment O&D Optimiser Spill & Recapture O&D Control Parameters passenger flow RevenueEstimation Accept/Reject CostEstimation Objective Function**O&DForecast Engine**O&D Forecasts Capacity Assignment O&D Optimiser System Integration – System Details O&D Revenue Management Iterative Proration (ProBP) ODIF POS buckets O&D Control Parameters**System Integration – System Details (cont)**O&D Revenue Management O&DForecast Engine O&D Forecasts Capacity Assignment O&D Optimiser O&D Control Parameters RevenueEstimation Estimated revenue = sum of EMSR values**O&DForecast Engine**vacant seats x x-1 Rt-1(x) = fi + Rt(x-1) O&D Forecasts Rt-1(x) = Rt(x) Capacity Assignment O&D Optimiser time to departure t t-1 Rt-1(x) = max[fi + Rt(x-1), Rt(x)] = max [ufi + Rt(x-u)] uÎ{0, 1} System Integration – System Details (cont) Dynamic Bid Price (DynBP) models revenue management as multistage decision process O&D Revenue Management O&D Control Parameters Bid price matrix per compartment**time to deptarture**current optimization point next optimization point t t-1 t-2 C 147.3 146.5 145.8 Decrease 149.5 148.7 147.9 C-1 . C-2 151.8 150.8 150.1 . remaining capacity Increase . System Integration – System Details (cont) Bid price matrix per compartment O&D Revenue Management O&DForecast Engine O&D Forecasts Capacity Assignment O&D Optimiser O&D Control Parameters RevenueEstimation Estimated revenue = sum of bid prices**S =**J System Integration – Discussion State Challenges • forecast uncertainty and actual fares taken into account • simple interfaces between fleet assigner and revenue management system • more accurate revenue estimation • two loop system • revenue estimation loop • fleet assignment loop • significant runtime differences • coordination of loops • capacity dependency of revenue management optimization • runtime! Approximation? • partly overlapping system functions (market model, OD-Forecast) • redundancy, requires further integration**Agenda**• Fleet Assignment Problem • O&D Revenue Management System • Current System Integration • System Integration Approaches • Conclusions**Conclusions - Fleet Assignment in Practice**Simulated Annealing-based Fleet Assignment Optimization • substantial part of commercialFleet Assignment tool Cooperative Approach • applied in Fleet Assignment Systems of ... Integrated Approaches • prototype**Conclusions - Summary**• Integration of Fleet Assignment and Revenue Management can improve overall revenue • Facets of the fleet assignment problem introduced:business, mathematics, simulated annealing • Substantial part: Profitability Evaluation Model (PEM) • Revenue management system introduced:particularly important for integration: control parameters • Current state of integration: Cooperative Approach with PEM (without integration of RMS) - successfully used by three airlines • System integration prototype: • based on internal passenger flow model (deterministic LP) • based on external link to O&D RMS: EMSR-based, dynamic programming good better almost perfect**Conclusions - Ongoing Work, Outlook**• Ongoing tests of system integration prototype • Market Model used in FA is also used in Pricing • further Integration possible • Integration of the Passenger Flow Model in Fleet Assignment • optimization approach for enhanced O&D Fleet Assignment • Usage in short-term → pre-implementation phase: • booking dependent (demand driven) fleet assignment**Thank you for your attention!Any questions?**UNIVERSITY of PADERBORN sven@uni-paderborn.de georg.kliewer@upb.de klaus.weber@lhsystems.com