A

ACARS units (aircraft communication system), 364

Acronyms, 308-309 AdaptedMoore 1 procedure, 427-428 AdaptedMoore 2 procedure, 429 Ad Opt Technologies, 241 Advanced Traffic Management System

(ATMS), FAA, 297 Aeronomics Inc., 69 AGIFORS (Airline Oroup, International

Federation of Operational Research Societies),314

Airborne ATC System Interface, 211 Aircraft. see also Routing, aircraft

characteristics, OMS, 195 costs, 163 critical arrival/departure times, 415 diversion, 101,261 OMS display, 221 ground movement simulation. see

Oround Motion Simulator(OMS) icon data, OMS, 195 maintenance, 340, 385-386 motion, OMS. see Aircraft motion, OMS

Host older, 163, 166,170 schedule of rotations, deviations in,

331-332,340-341 scheduling, 319, 385-386 spare,328,334,340, 348 substitution, 5, 6,175-178,261,333,409 weight, 325

Aircraft automatic guidance, OMS, 203-207 Aircraft balance, 5, 261 Aircraft handoffs, OMS, 214, 216-218 Aircraft motion, OMS Host, 196-210

aircraft automatic guidance, 203-207 aircraft interactive control, 208--210 automatic stops, 206 automatic yield, 206 basic aircraft motion, 198-203 ground translation, 198--202 landing, 206-207 phases of, 196-198 platooning, 205

rolIing takeoff, 207 turns, 202-203

INDEX

Aircraft Routers, 315, 317, 328, 340-341 Aircraft routing. see Routing, aircraft Aircraft Situation Display (ASD) data, 326 Air France, 241 Airline Group, International Federation of

Operational Research Societies (AGIFORS),314

Airline Marketing Assistant (AMA), 47, 48 Airline Operations Controllers. see

Operations controllers/coordinators Airline regulation, history of, 313 Airline Reservation System (OARUDA)

(ARGA), 358, 360, 366 Airline Resource Planner (ARP), 358, 359,

362,367 Airline(s). see also specific airlines

competition between, xiii-xiv cost structure of, 158-159, 183-184,232 decision support systems, xv-xvi demand economics, 161-163 marketing group, 315 offtime/vacation policies, 266 pairing rules, 245 product offered by, xiii resource planning, 229-230 scheduling group, 315 seniority rules, 266 system operations control. see

Operational control timetables, 232

Airline schedule planning. see Scheduling operations

Airport acceptance rates (AARs), 351 Airport Operations (KO) group, Garuda

Indonesia Airlines, 364 Airport(s). see also Hub stations; Spoke

stations accessibility, 430 congestion at, 337-338 delays at, 335, 336, 342-350 geometry data, OMS, 194 links data, OMS, 194 nodes data, OMS, 194 staffing, 180-181, 186

462

Air Route Traffic Control Centers (ARTCCs)

Boston, 315 organization, 102, 289 Traffic Management Unit (TMU) in, 338

Airspace capacity, 104, 105-106,290-291 design, 102 itineraries, 291

Air traffic control (ATC). see also Traffic flow management (TFM)

aircraft handoffs, 214, 216-218 deviations due to, 103,260-261,338 FAA responsibility, 103,407 models, 106-121 simulation facilities, 190

Air traffic control flow managers, 338, 348-350

Air Traffic Control System Command Centers (ATCSCCs)

responsibilities, 287, 307 strategies, 289-290

Air Traffic Management and Operations Simulation (A TMOS) facility, 190

Air Transat, 241 Air Transport World, 166 Alitalia, 253, 255-256 ALLPS system, pair generation, 240 ALTITUDE system, 241 AMEGA. see Automated Maintenance

Engineering Garuda (AMEGA) American Airlines

cancellations by, 406 crew pairing by, 240, 241 expenses, 230 flight plans, 327 overbooking, 52 revenue management, 46, 69 schedule perturbation management,

410-411,419,425,451 scheduling, 348 spare aircraft, 328 traffic management, 354

Approach, GMS aircraft motion, 196 Arcs

all-type arcs, 134-135 Complex Configuration model, 376-377 crew pairing-repair model, 269 duty, multicommodity flow model, 392 flight, time-line network, 388 ground, multicommodity flow model, 392

ground, time-line network, 389 k-type arcs, 134, 135 multicommodity flow model, 11 STN model, 110-112 Time-Line Network, 388-389

INDEX

ARGA. see Airline Reservation System (GARUDA) (ARGA)

ARINC data link, 326 ARMA (autoregression moving average)

model,49 ARP. see Airline Resource Planner (ARP) Arrival dependability statistics (ADS), 412 Arrival metering, 338, 339 Arrivals, delayed, 343-344, 346-347 ARTCCs. see Air Route Traffic Control

Centers (ARTCCs) ARTEMIS, 358, 361,362 ATCSCCs. see Air Traffic Control System

Command Centers (ATCSCCs) ATMOS (Air Traffic Management and

Operations Simulation) facility, 190 Automated demand resolution (ADR). see

Traffic Flow Management (TFM) Automated Maintenance Engineering

Garuda (AMEGA), 358, 361, 362 Automatic stops, GMS aircraft motion,

204,206 Automatic yield, GMS aircraft motion,

204,206 Autoregression moving average (ARMA)

model,49

B

Baggage handling, 336 BANKET, 48, 51

advantages, 64-65 architecture/dynamic configuration,

55-58 implementation, 63-64 input variables, 54 knowledge representation, 53-55 models compared, 6 1-63 overview, 52-55 parameters, 60-61 preprocessing variables, 54-55 training/testing, 59-60

Base cities, 125 Basic Fleet Assignment (Basic F AM)

model, 389-391, 393

INDEX

Batch mode, 272 BehavHeuristics, Inc. (BHI), 46, 47, 64 Belobaba, Peter, 69 Bidline procedures, 127,319,386 Bid prices, 79, 89-91 Block times, 332-333, 376 Booking classes, 47, 72, 76 Bounding-box, OMS, 191,218 Branch-and-bound algorithms, 132, 139,

242,243 Bumping procedures, 79-80

c

Cancellations, flight, 406 effects of, 340, 347 inODP,409 in irregular operations, 261, 334 statistical representation, 437 zero booking flights, 164-166

Capacity airspace, 102 PARM, 71-72, 74

Cargo manifests, 326 Carmen pairing construction system, 240,

244-252 automatic scheduling module, 245-250 deadheading, 255-256 experience with, 253-256 generation control rules, 254-255 optimizer, 248-250 pairing generator, 247-248 rule definitions, 253 rule language, 251-252 rule programming difficulties, 254 rule system, 250-252 subproblem selection, 245-247 users, 253

Causal models, forecasting, 49 Cengkereng Airport, 357 Central Flow Control Facility, 339,350-352 Chalmers University of Technology,

Sweden, 256 Column generation method

pairing, 392 rostering, 124, 144-147

COMFORT system, 363 Complex Configuration model, 375-383

introduction, 370-371 model implementation, 379-382

problem description, 371-375 problem formulation, 375-379 purpose, 375 summary, 383

Complexes, scheduling cancellation, 350 constraints on, 374-375 definition, 370, 374 development, 370-371 directionality of, 374 thinning out, 350

Complex time, 406

463

Computerized Terminal Area Simulation (CTAS) facility, 190

Computer reservation systems (CRS), xiiiCxiv, 374

Continental Airlines, 240 Controlled Times of Arrival (etAs), 351,

408 Controller interface, 211, 213-214

apron control, 213 ground control, 213 tower control, 213

CONVEX model C-220, 243 Credit hours, 232 Crew. see also Crew scheduling

categories, 231 costs, 167,230,232 fleet requirements, 231, 386 stand-by, 229

Crew balance, 261 Crew coordinators, 262, 272 CREWLINK. see Crew Management

System (CMS) Crew management, 259-285, 327-328

FAR requirements, 264-265 irregular operations, STN model,

266-285 off time policies, 266 planning, Oaruda Indonesia Airlines, 363 seniority policies, 266 vacation policies, 266

Crew Management System (CMS), 358, 363, 366-367

Crew Operations group, 317, 319, 321, 327-328

Crew Planning (OB) group, Oaruda Indonesia Airlines, 363

Crew Schedulers, 327 Crew schedules, 327, 331

deviations in, 339-340

464

in JIT scheduling, 179-180 responsibility for, 320

Crew scheduling. see also Pairing; Rostering contract legalities, 232, 266 critical arrival/departure times, 415 FAA rules, 232, 264-265 irregular operations, 259-285, 328 J1T,186 preferences. see Desiderata stages, 386

Crew Scheduling group, 179,315 Crew Trackers, 317 Critical arrival times, 415-418, 438 Critical departure times, 415-418 Cross, Bob, 69 CROSS RUNWAY command, OMS, 210,

216 CTAS (Computerized Terminal Area

Simulation) facility, 190 Customer diversion, 68, 78, 86-87

n fare classes, 87 two fare classes, 86-87

Customers. see Passenger(s) Cycle periods, scheduling, 317 Cycle-related expenses, 167 Cycles, STN model, 114

feasible, 114 improving, 114 multicommodity improving, 118, 119 types, 116-118

D

Daily training phase, BANKET, 59 Database manager, OMS Host, 194-195 DeS. see Departure Control System (DeS) Deadheading crew, 230, 247, 255-256 Delay management, ground delay program,

408-409,429-430,434-435,454-459 aircraft, models for, 3-4 computational experiments, 449-454 critical arrival/departure times, 415-418 current practices/opportunities, 410-412 delayed flights, minimizing number of,

424,426-429,437-445 improvement areas, 352-356 landing assignment in, 418-425 landing/takeoff as single resource,

425-429 literature review, 412-413

INDEX

maximum delay, minimizing, 424-425, 426,435-437

model simplification/valid inequalities/heuristic, 446-449

objectives in managing, 414-415, 426-429

options available, 409 restrictions, 409-410 total delay cost, minimizing, 424

Delays. see also Operational deviations average daily, 313-314 categories, 434 causes, 260-261, 405, 406, 408 cost, 103,288,407 degrees, 345-347 hub stations, 344-350 improving, 352-357 planned, 103-104,341-342 spoke stations, 342-344 unplanned, 103-104

Delay Spacing Programs (DSPs), 338 Delta Air Lines, 241 Demand

characteristics, 161-162 customer classes, 76 directionality of, 171 forecasting. see Forecasting demand

Denied boarding, 336 Department of Transportation (DOT)

delay, 437 Departure Control System (DCS), 360,

361,362,364,365,367 Departure( s)

delayed, 344, 347 OMS aircraft motion, 197 slots for. see Slot( s)

Deregulation, effect of, xiii Desiderata, 126

company respect for, 127 effect on solution time, 148-149 preassigned, 130, 149-154

Discount fare customers, 72, 74-76 in J1T scheduling, 165, 184 price-sensitivity, 162-163 show-ups, 76-77

Disjoint column method disjoint columns, defined, 124 method, 144-147

DISTINCT, 297 Distinct asset control mechanism, no

diversion model, 94-95

INDEX

general case, 95 two fare classes, 94-95

DLR Institute for Flight Guidance, Germany, 190

Duty network, 392 Duty period time, 230, 264-265 Dynamic data, GMS, 194 Dynamic programming models, TFM,

292-293

E

Enroute Spacing Programs (ESPs), 338 Estimated Departure Clearance Time

(EDCT)program,289-29O,306,338, 351

Execution rescheduling phase, 320 Execution scheduling phase, 315, 320,

341-342 Expected Marginal Seat Revenue (EMSR),

82,83-84 Experimenter interface, 211, 212-213

F

FAA. see Federal Aviation Administration (FAA)

FAA/MITRE National Airspace Simulation Capability facility, 190

Fare setting, 47 customer willingness to pay, 74-75 determination, 74 discount price classes, 76 optimization models, 94-97 price-sensitive customers, 72, 74-76,

162-163 Fare wars, 182 Federal Aviation Administration (FAA)

Advanced Traffic Management System (ATMS),297

ATC, responsibility for, 103,407 ATCSCC, 287, 289-290, 307 delays, impact of intervention, 406-407 GOP, responsibility for, 101,407,408,

434 MITRE National Airspace Simulation

Capability facility, 190 Operations Research Service. 288, 297 regulations, 232, 264-265

465

Research and Development Service, 288 TFM, responsibility for, 101,407

Federal Aviation Regulations (FAR), 232. 264-265

Feedforward networks, 52 Ferrying aircraft, 5, 261, 334 Fixes, spatial network, 109 Fleet, crew for, 231, 386 Fleet assignment, 5, 229-230, 385

case study, 396-399 existing models, 388-391 integrated with crew pairing, 386,

393-399 Fleet families, 386 Flight dispatch (EA) group, Garuda

Indonesia Airlines, 363, 364 Flight Dispatchers, 323-324, 325-326 Flight dispatch group

arrangement, 323 Load Control group, 326 Meteorology group, 326 responsibilities, 321, 322, 323-327

Flight following, 324 Flight Operations Officer (FOO), Garuda

Indonesia Airlines, 364 Flight plans, 323-324, 326-327 Flight route augmentation, 30-31 Flights

added,l86 cancelled. see Cancellations, flight diverted, 101,334-335 zero-booking, 164-166

Flight schedules, 384. see also Just-in-time (J1T) scheduling

definition, 2 European/North American compared,

232 grouping in, 168-170 planning, 102,229,385,405

Flight time, 264-265 Flow managers, ATC, 338, 348-350 FOLLOW command, GMS, 209,215 Forecasting demand, 46-65, 77

causal models, 49 in JlT scheduling, 186 model comparison, 61--63 model selection, 48-5 I neural network models, 48, 50-51, 52--64 problem statement, 51-52 time-series cross-sectional models, 50 time-series models, 49

466

Fuelcos~, 167,324-325,326-327

G

Garuda Indonesia Airlines, 312, 357-367 Airport Operations (KO) group, 364 Crew Planning (OB) group, 363 Flight Dispatch (EA) group, 363, 364 Infonnation Systems (OX) group,

366-367 Maintenance Control Center (MCC),

361-362 Maintenance Planning (MP) group,

362-363 Navigation (ON) group, 365-366 Operations Control Center (OCC), 361 Operations Movement Control (EM),

359-360 Operations Planning (EP), 358-359 Ramp Control (KR) group, 365

Garuda Maintenance Facility (GMF), 362 Gates

as complex constraint, 374 in JlT scheduling, 180 scheduling, 320, 329, 337

GDP-L1 problem, 420 GDP-L2 problem, 422-424 GDPL T model, 438-439, 445-447, 449-454 GDP-T model, 448-449 GDPTO model, 439-445 GENCOL column generation program, 140,

155 GMS. see Ground Motion Simulator (GMS) Go-shows, 51 Greedy randomized adaptive search

procedure (GRASP), routing, 1,29-35 flight route augmentation, 30-31 flow diagram, 34 partial route exchange, 31

Ground Delay Program Emulator (GDPE), 114-116

Ground Delay Program (GOP), 289 FAA responsibility, 101,407,408,434 improving, 352-356 internal, 352-353 landing assignment in, 418-419 levels, 351, 352-353 limitations of, 104-105 logic of, 351 models, 3-4

INDEX

as planned delay, 103-104 scheduling disturbed by, 348-350, 408 strategies for managing, 404-430,

433-459 Ground deviations, 335-338 Ground Motion Simulator (GMS), 189

background, 190-193 benefits, 190-191 commands, 208-210, 215-216 coinponents, 191-192 functions, 191-193 graphics display, 218-221 hardware/software necessary, 226 Host, 191, 193-212 human interfaces, 212-218 infonnation needed to run, 194-195 operation modes, 225-226 taxiway/runway networks, 221-225

Ground stops, 289, 290, 338-339 Ground support services, 329

deviations in, 335-338 in lIT scheduling, 173-175

H

Handoffs, aircraft, 214, 216-218 High-fare customers, 72,74-75, 162-163

in JlT scheduling, 165, 182-183, 184 show-ups, 76-77

High load factors, 181 Host, GMS, 191, 193-212

aircraft motion, 196-210 database manager, 194-195 interface drivers, 210-212 scheduler, 195-196

Hot spare aircraft, 328, 348 Hub and spoke networks, 370. see a/so

Hub stations; Spoke stations benefi~ of, 260, 313, 371-373 crew pairing in, 231-232, 260

Hub stations, 371 delays at, 335, 336, 344-350 directional, 347 omni-directional, 347 SOCC at, 329 spares at, 328, 348

Human interfaces, GMS, 212-218 aircraft handoffs, 216-218 controller, 213-214 experimenter, 212-213

INDEX

pseudo-pilot, 214-216

I

Information Systems (DX) group, Garuda Indonesia Airlines, 362, 366-367

INFORMS (International Federation of Operations Research and Management Science),314

Instrument flight rules (IFR), 327, 408 Instrument landing systems (ILS), 327 Integrated airline schedule planning,

384-401 advanced integrated solution approach,

395-396 case study, 396-399 conclusionslfuture research, 399-401 crew pairing, existing models/algorithms.

391-393 fleet assignment, existing

models/algorithms, 388-391 integrated approximate model, 393-395 introduction, 385-388

Integrated Interactive Dynamic Flow Control (IIDFC), 357

Interface drivers, GMS Host, 210-212 Controller interface, 211 Experimenter interface, 211 external interfaces, 211-212 Pseudo-Pilot interface, 211

Internal ground delay programs, 338, 351, 352-353

IBM,241 International Federation of Operations

Research and Management Science (INFORMS),314

Interprocessormessages, 191, 196,210-211 Inventory management, 69 Irregular operations. see also Delay

management, ground delay program aircraft in, 1-43,261-262,340-341 crew in, 259-285, 339-340 definition, 260, 331 diverted flights in, 334-335 impact of, 261 models for, 1-43,259-285 planned deviations due to, 341-342 rescheduling operations. 320, 342-350

Itineraries, airframe, 290, 291

467

J

lust-in-time (JlT) scheduling, 158-188 aircraft substitution meeting demand,

175-178 airline demand economics. 161-163 benefits, 181-184 canceling zero booking flights, 164-166 conclusions, 187-188 cost reduction, 158-159, 166-168,

183-184 ground resources. rationalizing, 173-175 implementation, 178-181 need for, 159-160 old aircraft substituted on JlT flights,

166-168 rerouting for transient demand, 170-173 scaled for all high frequency routes,

168-170 setting up, 184-187 steps in, 164-178

K

KLM,253

L

Lagrangean Relaxation, 243 Landing

alternative objectives. 421-425 assignment, GDP,418-419 GDP-Ll problem, 420 GDP-L2 problem, 422-424 GMS aircraft motion, 196, 206-207 takeoff compared, 425

Landing fees, 167 Lay-overs. 230 Linear/interger/mixed integer programming

models. TFM, 293 Linear network flow models, TFM, 293 Links

GMS, 194,223,224-225 spatial network, 109, 110

Load Control group, 326 Lotus 1-2-3, 380 Lucas Management System (UK), 361 Lufthansa, 253, 256

468

M

Maintenance Control Center (MCC), Oaruda Indonesia Airlines, 361-362

Maintenance Operations Control (MOCC) centers, 315-317, 321, 328

Maintenance Planning (MP) group, Oaruda Indonesia Airlines, 362-363

Manned Vehicle Systems Research Facility (MVSRF), 190

Meteorology. see Weather Meteorology group, 326 METRON, 297 Miles in trail (MIT) restrictions, 101, 289,

290,338,356-357 Minimum turnaround time, 5 MITRE Corporation Center for Advanced

Aviation System Development (CAASD), 288, 293

MIT TFM model, 295--296, 298-302 MOCC. see Maintenance Operations

Control (MOCC) centers Multicommodity flow model, aircraft

routing, 10-16, 17 Multicommodity flow model, crew pairing,

392-393 Multicommodity Improving Cycle Refiner

(MICR), 114-116 Multicommodity network flow model,

ATC. see Space-Time Network (STN) model,ATC

Multicommodity networks. 107 Multiple Airport Scheduler (MAS), 297,

298-302 MVSRF (Manned Vehicle Systems

Research Facility), 190

N

NASA/Ames Research Center, 190 National Airspace System (NAS)

congestion, 104, 288 organization, 102

National ground delay programs. 103,351, 352-353

National Weather Service, 324 Navigation (ON) group, Oaruda Indonesia

Airlines. 365--366 Nested asset control mechanism, diversion

model, 96-97

Nested asset control mechanism, no diversion model, 95-96

NETSID,381-382 Network models

for crew pairing, 392-393 for crew pairing repair, 266-285 for fleet assignment, 388-389

INDEX

for forecasting demand, 48, 50-64 OMS, 221-225 multicommodity, for ATC, 101-102,

107-121,293,294-295 for route planning, 371, 375--383

Neural network model, forecasting demand,48,50-51, 52-64

Nodes, 52 Complex Configuration model, 375-376 crew pairing-repair model, 267 OMS, 194,222,224 multi commodity flow model, II spatial network, 109, 110 station-sink, 21 station-time, 21 Time-Line Network, 388

Nonlinear programming models. TFM, 293 Northwest Airlines. 230, 240 No-shows, 48, 5 I

o

OCC. see Operations Control Centers (OCCs)

Off time policies, 266 On-line simulation phase, BANKET, 59 Operational control, xivCxv, 260, 312-367.

See also Operations Control Centers (OCCs)

case study, 357-367 deviations in, 331-352 improvement areas, 352-357 introduction, 313-315 irregular. see Irregular operations maintenance, 328 schedule development phases, 315-320 station, 328-330 strategic, 320 tactical, 320

Operational deviations. see also Delays; Irregular operations

causes. 334-339 definition, 331-341

INDEX

ground,335-338 levels, 331, 341-342 OCC handling, 332-334 Passenger Schedule, 334-339 Schedule of Aircraft Rotations, 340-341 Schedule of Crew Trips, 339-340

Operational schedules, 323, 341 Operations Control Centers (OCCs)

groups of, 315, 321-328 irregular operations, 332-334 responsibilities, 320-321, 325

Operations Control Centre (OCC), Garuda Indonesia Airlines, 361, 363

Operations controllers/coordinators American Airlines, 419, 425 irregular operations, 405, 409-410 responsibilities, 321, 322-323, 342, 410

Operations Movement Control (EM) group, Garuda Indonesia Airlines, 359-360, 363

Operations planning, 260, 358-359 Operations Planning (EP) group, Garuda

Indonesia Airlines, 358-359 Operations Research Service, FAA, 288,

297 OPTIFLOW, 297-302 Optimum Booking Limits (OBL) rule, 82,

83,84-85 Overbooking, 52, 79, 336-337

one fare class, 85 two or more fare classes, 85-86

p

Pairing, 125,228-256,262,386 Carmen system, 244-256 daily problem, 234-235 definition, 230 EuropeanlNorth American compared,

230-233 fully dated problem, 233, 237 generation methods, 239-241 integrated with fleet assignment, 386,

393-399 in irregular operations. see Pairing repair multicommodity flow model, 392-393 planning, 230 rostering compared, 142 set partitioning/covering model,

237-239,241-244,391-392

469

substitution, 409 weekly problem, 235-237

Pairing repair, 259-285 computational experiences, 277-285 crew legalities/pairing repair, 264-266 introduction, 260-264 model/mathematical formulation,

266-271 solution methodology, 271-277

Paradox database management system, 359 Partial route exchange, 30, 31 Passenger delay, 331

causes, 334-339 hub station, 344-350 minimizing, 3, 414 spoke station, 342-344 total, 412

Passenger manifests, 326 Passenger(s)

airport handling, 329, 336-337 classes, 47, 72, 76 critical arrival/departure times, 415 demand forecasting, 48-65, 76, 77 diversion, 68, 78, 86-87 group reservations, 78 price sensitivity, 72, 74-76, 162-163,

184 show-ups, 76-77 turned-down reservations, 77

Passenger schedules cascading effect of, 332 importance of, 332 irregular operations in, 331, 334-339,

342 planned deviations, 342 production group, 315, 3 18-319 restoring, 332-334

Perishable-Asset Revenue Management (PARM), 68-97. see also Revenue management

components, 69 customer diversion/sell-up heuristics,

86-87 definition, 69-70 deterministic demand, heuristic methods,

91-94 deterministic demand, optimal methods,

89-91 industries for, 70-71 optimal pricing, 94-97 overbooking, 85-86

470

problem definition, 69--72 seat allocation decisions, 82-35 taxonomy, 72-32

Personalized schedules. see Rostering Perturbations. see Operational deviations Pfeifer, P.E., 69 Pilots

acceptance oftlight plan, 324-325 minimum rest time, 265 scheduling, 140

Planned delays/deviations, 103-104, 341-342

Planned deviations due to irregular operations, 341, 342

Platooning, OMS aircraft motion, 197, 204, 205

PLAYBACK operating mode, OMS, 225-226

Price setting. see Fare setting Pseudo-pilot interface, 211, 214-216 Pseudopilot stations, OMS, 191 Push back, OMS aircraft motion, 197 PUSH BACK command, OMS, 208, 215

Q

Q-CALC, 380 Queuing models, TFM, 292, 293

R

RALPH system, 241 Ramp Control (KR) group, Oaruda

Indonesia Airlines, 365 Randomized search heuristic, aircraft

routing, 29--35 neighboring solutions, 29, 31-32 operations, 30-32 phases, 29 sample data, 35-42 stopping criterion, 33

RECORD operating mode, OMS, 225 Rescheduling operations, 320, 332, 342-350

delays at hub stations, 344-350 delays at spoke station, 342-344

Research and Development Service, FAA, 288

Reservation(s) demand,76

group, 78 show-ups, 76-77 turned down, 77

Reserve blocks, rostering, 127 Resource assignment model, aircraft

routing, 7-10,16-17

INDEX

Resource assignment phase, 315, 319--320 Resource batch sequencing (RBS), 458 Resource management Operations Control

system (ROC), 358, 359--360, 361,367 Rest time, 127, 149, 265 Revenue management, 46-65. see also

Perishable-Asset Revenue Management (PARM)

AMA system, 47, 48 characteristics needed, 71-72 displacement of resources, 78-79 forecasting models, 48-65 goals, 46-47 process, 47 shortcomings in, 159--160

RM Resource Management (Sweden), 359 ROC. see Resource management

Operations Control system (ROC) Rolling takeoff, OMS aircraft motion, 207 Rostering, 124-155. see also Set

partitioning model, crew rostering definition, 124, 127 desiderata effect, 126 literature review, 128-129 pairing compared, 142 planning, 230, 386 problem definition, 130-131 seniority in, 266

Rotations, crew. see Pairing Routes

ATC-preferred, 324 connectivity, 6

Routing, aircraft. see also Aircraft Routers different city pairs, 170-173 irregular operations, models for, 1-43,

340-341 in JIT scheduling, 170-173, 178-179,

186 maintenance, 385-386 model assessment, 16-17 multicommodity flow model, 10-16, 17 planning stages, 385-386 randomized search heuristic, 29-42 resource assignment model, 7-10, 16-17

INDEX

time-band approximation scheme, 17-28, 35-42

Routing, crew. see Pairing Runways, GMS, 195

s

Sabre Decision Technologies, 241 SAS, 253 Scenario data, GMS, 195 Schedule generation phase, 315, 318-319 Schedule perturbation problem, nonsplitable

resource, 404-430 causes/nature/severity of problem,

406-409 conclusions, 429-430 critical arrival/departure times, 415-418 current status/opportunities, 410-412 delay, minimizing maximum, 426 delayed outflights, minimizing number,

426-428 delayed outflights, minimizing total,

428-429 introduction, 405-406 landing assignment, 418-425 landing/takeoff as single resource,

425-429 literature review, 412-413 objectives, 414-415, 421-425 options available/restrictions, 409-410 preliminaries, 414-418

Schedule perturbation problem, splitable resources, 433-459

computational experiments, 449-454 conclusions, 454-459 delayed flights, minimizing number of,

437-445 experiment implications, 454 GDPTO, special case, 439-445 heuristic, 446-449 introduction, 434-435 model simplification, 446-449 NP-hardness of (GDPL T), 445 outflights, minimizing maximum delay,

435-437 realistic example, 451-454 valid inequalities, 446-449

Scheduler, GMS Host, 195-196 Schedules. see also specific schedules

Airline System, 331

definition, 127 effect of delays on, 434 perturbations in. see Delays

471

Schedules of Aircraft Rotations, 319, 320, 331-332,340-341

Schedules of Crew Trips. see Crew Schedules

Scheduling operations, 260, 314 complexes, 370-371 integrated fleet assignment/crew pairing,

388-401 irregular operations, 320, 341-350 phases of, 315-320 planning stages, 385-388

Seasonality training phase, BANKET, 59 Seat inventory control, 47, 69,80-82 Seats

allocation, 82-85 as perishable asset, 71, 73-74

Sectors, airspace, 102 Sell-ups, 68, 78, 86-87 Seniority policies, 266 Service planning phase, 315, 317-318 Service Scheduling group, 315 Set partitioning/covering model, crew

pairing, 237-239, 391-392 exact algorithms, 242-243 heuristic algorithms, 243-244 methods, 241-244

Set partitioning model, crew rostering, 131-139

baseline method, 142-144 branch and bound algorithm, 139 constraints in, 138-139 desiderata effect, 148-149 disjoint column method, 144-147 preliminary tests, 140-142 productivity/solution quality, 149-154 solution method, 132-133 subproblem modeling, 133-139

Severe Weather Avoidance Program (SWAP), 289, 290

SIMULATION operating mode, GMS, 226 Single Commodity Improving Cycle

Refiner (SCICR), 114-116 Slot( s), 348

assignment, 352,435 auctions, 355-356 swaps, 333,350,351-352,354-355,408

SLOW DOWN command, OMS, 210 SNAG, 358, 361

472

SOCC. see Station Operations Control Centers (SOCCs)

Space-Time Network model, crew pairing repair

computational experiences, 277-285 formulation, 269-271 model, 266-269 solution methodology, 271-277

Space-Time Network (STN) model, ATC, 101-102,293,294-295

algorithm overview, 114, 116 arc types, II 0-112 assumptions, 105, 108--113 example, 119-121 guaranteed integer solution, 118-119 improving cycles, 114 mathematical formulation, 112-113 method,107-108 multi commodity improving cycles, 118 other models compared, 298--302 single commodity cycle classification,

116-118 solution method, 114-121 spatial networks, 109-110

SPEED UP command, OMS, 210,216 Speed ups, 333 Spoke stations, 371

delays at, 335, 336, 342-344 staffing, 181 tum time reduction by, 333

SSIM (Standard Schedules Information Manual), 359

Standard Schedules Information Manual (SSIM),359

START command, OMS, 209-210, 215 Static input data, OMS, 194 Station Operations Control Centers

(SOCCs), 320, 321, 325, 328--330 Stations. see also Hub stations; Spoke

stations requirements of, 6

Station-sink nodes, 21 Station-time nodes, 21 STOP AT INTERSECTION command,

OMS, 209, 215 STOP command, OMS, 209, 215 Stops, OMS network, 225 Sun Spare Station 2, 142 Swedish Railways, 253 System configuration, OMS, 194

INDEX

System operations control. see Operations control

System Timing/Synchronization/Control module, OMS, 193, 195-196

T

Takeoff ODP restrictions, 425 roll, OMS aircraft motion, 197,207

TAKEOFF command, OMS, 208, 216 TAM. see Time Assignment Model

(TAM),ATC Taxipaths, OMS, 195, 204 Taxi time, 337 TAXI TO command, OMS, 209, 215 Taxi to gate, OMS aircraft motion, 196, 197 Taxi to runway, OMS aircraft motion, 197 Taxiways, OMS, 194,225 TCPIIP stream sockets, 191,210 TFM. see Traffic flow management (TFM) Through flights, 385 Through revenue, 385 Tier I ground delay programs, 351,

352-353 Tier 2 ground delay programs, 35 I,

352-353 Time Assignment Model (TAM), ATC,

288,293,294 EDCT compared, 306 formulation, 302-306 models compared to, 298--302 solution methodology/results, 306-307

Time-band approximation scheme, aircraft routing, 17-28, 42

model,24-28 sample data, 35-42 time-band network, 18--23

Time deviations, 331, 332, 341 Time-Line Network, fleet assignment,

388--389 Time-series cross-sectional models,

forecasting, 50 Time-series models, forecasting, 49 Timetables, 229, 232 TOWER controllers, 338 Tower - Pilot Sight (TPS) systems, 212 TPACS system, pair generation, 240 TRACON controllers, 338 Trade-ups, 69, 78, 86-87

INDEX

Traffic controller stations. OMS. 191 Traffic flow management (TFM). 287-308

FAA responsibility. \01.407 introduction. 288-289 MIT model. 295-296 model comparison. 298-302 model criteria, 292 Multiple Airport Scheduler (MAS). 297 OPTIFLOW.297-298 optimization models. 292-302 problem features, 290-291 STN model. 101-102. 107-121.293.

294-295.298-302 strategies, 289-290. 338-339 TAM model. 293-294. 302-307

Traffic Management Units (TMUs). 338 Transition activities, rostering. 127 TRIP system. pair generation. 240 TURN command, OMS. 208-209. 215 Turns. aircraft OMS motion, 202-203

U

Unisys.240 United Airlines. 230. 240. 263. 327. 328 U. S. Federal Aviation Administration

(FAA). see Federal Aviation Administration (FAA)

University ofPatras, Oreece. 256 UNIX workstations. 226, 380 Unplanned delays. 103-104 USAir. 63. 240. 241

v

Vacation policies. 266 Vertex, STN model. 110 Virtualnes~. 79.91-94 Visual flight rules (VFR). 327, 408 Visual System Interface, 212 Volpe National Transportation System

Center, 288. 297

w

Weather airline meteorology department. 326 ASD data. 326

473

deviations due to. 103.260,334-335. 348

dynamism of, 291 effect on flight planning, 324 SWAP,289,290 uncertainty of, 290. 291

Wingtip service, 377

y

YIELD command. OMS. 209, 215 Yield management, 69-70,159-160. see

also Revenue management