300 likes | 576 Views
Studies in Route Optimization of Cargo Airlines in India. Dr. Rajkumar S. Pant Associate Professor of Aerospace Engineering Indian Institute of Technology, Bombay rkpant@aero.iitb.ac.in. Typical Airline Network. Routes. A. Airports Aircraft Routes Schedule. Airports. Aircraft. B.
E N D
Studies in Route Optimization of Cargo Airlines in India Dr. Rajkumar S. Pant Associate Professor of Aerospace Engineering Indian Institute of Technology, Bombay rkpant@aero.iitb.ac.in
Typical Airline Network Routes A • Airports • Aircraft • Routes • Schedule Airports Aircraft B Scheduled Flights Time varying Demand D C
Literature Review • Objectives – Kanafani (1982),Teodorovic (1988) Max. Revenue Min. Cost Max. Profit Max. Level of Service Max. Aircraft Utilization
Objectives – Kanafani (1982),Teodorovic (1988) Multi Criteria Model – Teodorovic & Krcmar-nozic (1989) Max. Profit Max. number of passenger flown Min. Schedule Delay Literature Review
Objectives – Kanafani (1982),Teodorovic (1988) Multi Criteria Model – Teodorovic & Krcmar-nozic (1989) Day of Operation – Teodorovic and Stojkovic (1995) Min. Canceled flights and Min. Total Passenger Delay Literature Review
Literature Review • Objectives – Kanafani (1982),Teodorovic (1988) • Multi Criteria Model – Teodorovic & Krcmar-nozic (1989) • Day of Operation – Teodorovic and Stojkovic (1995) • Fleet Assignment –Gvozdenovic (1999)
Objectives – Kanafani (1982),Teodorovic (1988) Multi Criteria Model – Teodorovic & Krcmar-nozic (1989) Day of Operation – Teodorovic and Stojkovic (1995) Fleet Assignment –Gvozdenovic (1999) Route Selection – Hsu and Wen (2000) Application of Grey Theory Literature Review
Objectives – Kanafani (1982),Teodorovic (1988) Multi Criteria Model – Teodorovic & Krcmar-nozic (1989) Day of Operation – Teodorovic and Stojkovic (1995) Fleet Assignment –Gvozdenovic (1999) Route Selection – Hsu and Wen (2000) Crew –Kornilakis et al (2002) Crew pairing & Assignment Literature Review
Objectives – Kanafani (1982),Teodorovic (1988) Multi Criteria Model – Teodorovic & Krcmar-nozic (1989) Day of Operation – Teodorovic and Stojkovic (1995) Fleet Assignment –Gvozdenovic (1999) Route Selection – Hsu and Wen (2000) Crew –Kornilakis et al (2002) Maintenance- Sriram and Haghani (2003) Minimum Maintenance Cost Literature Review
Objectives – Kanafani (1982),Teodorovic (1988) Multi Criteria Model – Teodorovic & Krcmar-nozic (1989) Day of Operation – Teodorovic and Stojkovic (1995) Fleet Assignment –Gvozdenovic (1999) Route Selection – Hsu and Wen (2000) Crew –Kornilakis et al (2002) Maintenance- Sriram and Haghani (2003) Departure Time: Chang & Schonfeld (2004), Pollack (1974) Min. average schedule delay per passenger Literature Review
Objectives – Kanafani (1982),Teodorovic (1988) Multi Criteria Model – Teodorovic & Krcmar-nozic (1989) Day of Operation – Teodorovic and Stojkovic (1995) Fleet Assignment –Gvozdenovic (1999) Route Selection – Hsu and Wen (2000) Crew –Kornilakis et al (2002) Maintenance- Sriram and Haghani (2003) Departure Time: Chang & Schonfeld (2004), Pollack (1974) Air Cargo fleet routing: Yan, Chen & Chen (2006) Dedicated methodology for Cargo Airlines Literature Review
Objectives – Kanafani (1982),Teodorovic (1988) Multi Criteria Model – Teodorovic & Krcmar-nozic (1989) Day of Operation – Teodorovic and Stojkovic (1995) Fleet Assignment –Gvozdenovic (1999) Route Selection – Hsu and Wen (2000) Crew –Kornilakis et al (2002) Maintenance- Sriram and Haghani (2003) Departure Time: Chang & Schonfeld (2004), Pollack (1974) Air Cargo fleet routing: Yan, Chen & Chen (2006) Integrated Transportation Network Design & Optimization- Taylor & De-Weck (2007) Optimization of Aircraft & Route Network at one go Literature Review
Features • Demand responsive, flexible scheduling • Arrive at ‘‘Schedule-of-the-day“ • Maintenance and operational constraints applicable • Combined scheduling and optimisation • Route selection using Grey Theory (Deng, 1982) • Optimization of user-selectable objective functions • Airline can assign priorities to certain routes
Inputs required • Airport Details • Network Details • Demand Data • Base Station Details • Fleet Details • Route Priorities (if any)
Overview of the methodology Control Parameters • Demand index • Cost Index • Time Index • Route Priority Index
Constraints • Airport Slots • Break Even Load Factor • Base Station and Hanger Capacity • Maintenance
Overnight Express Cargo • Late night cutoffs, early morning delivery • Varying demand • Dedicated Freighter aircraft • Fixed window for Flight Operations
Assumptions • Dedicated Cargo airline • Demand is known a priori • Route Lengths ≤ Harmonic Range • Same Turn Around Time at all airports
Constraints in Schedule Generation • Operational • Airport Slot availability • Break-even Load Factor • Operating time window • Maintenance • Base station to go to at the end of the day • Hangar Capacity • Maximum flight time available for each aircraft
Typical Results Improvements compared to existing schedule being operated
Conclusions • Methodology for demand responsive scheduling of day’s operation • Grey Theory for route selection • Genetic Algorithms for Optimization • Case Study for Express Cargo airline • ~ 20% improvement • Cargo Carried • Cargo/Cost
Grey Theory By Deng (1982) - Can deal with multidisciplinary characteristics of the system - Can handle systems for which exact information is lacking
Whitening Functions 3 Types Less then a number Approx to a number Greater then a number