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1
Angel A. Juan
Computer, Multimedia &
Telecommunication Dept.
IN3 - UOC, Barcelona, SPAIN
Tolga Bektas
University of Sout...
• Conext & Motivation
• Introduction to VRP
• Our Problem: Heterogenous + Green VRP
• How we solve it?
• Results
• Conclus...
1. Context & Motivation
3
CAN WE GO GREENER?
• Reducing “carbon footprint” and
addressing other environmental issues
• Cos...
2. Introduction – VRP and Rich VRP
Vehicle Routing Problem (VRP), is a
combinatorial problem seeking to service a
number o...
3. Heterogeneous & Green
Heterogeneous VRP, Different types of
vehicles:
• EV: Electric Vehicles
• ICE: internal combustio...
4. How we solve it? (1/2)
6
CVRP* = CVRP with route
maximum distance
Round 1: ICE
MDR: unlimited
Assumed fleet:
2 ICEs + 3...
5. How we solve it? (2/2)
7
Notes:
(a) Number of rounds <= Number of veh. types
(b) If heterogeneity index  0 then Multi-...
6. Results
8
Changing the distribution to greener vehicles we maintain the distance cost
associated to each problem (bench...
7. Conclusions & Future research
9
• Support the hypothesis that hybrid and electric vehicles can be used in routing
probl...
10
Angel A. Juan
Computer, Multimedia &
Telecommunication Dept.
IN3 - UOC, Barcelona, SPAIN
Tolga Bektas
University of Sou...
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Routing Fleets with Multiple Driving Ranges: is it possible to use greener fleet configurations?

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In this presentation the authors (Angel A. Juan, Jarrod Goentzel, Tolga Bektas) discuss the vehicle routing problem with multiple driving ranges. The presentation describes an integer programming formulation and a multi-round heuristic algorithm
that iteratively constructs a solution to the problem. Using a set of benchmarks adapted
from the literature, the algorithm is employed to analyse how distance-based costs are increased when considering ‘greener’ fleet configurations – ie, when using electric vehicles
with different degrees of autonomy.

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Routing Fleets with Multiple Driving Ranges: is it possible to use greener fleet configurations?

  1. 1. 1 Angel A. Juan Computer, Multimedia & Telecommunication Dept. IN3 - UOC, Barcelona, SPAIN Tolga Bektas University of Southampton, Southampton, UK Jarrod Goentzel Massachusetts Institute of Technology, Cambridge, MA, USA Routing fleets with multiple driving ranges: is it possible to use greener fleet configurations? Presenting: Pol Arias, MSc Visiting Researcher IN3 - Smart Logistics & Production
  2. 2. • Conext & Motivation • Introduction to VRP • Our Problem: Heterogenous + Green VRP • How we solve it? • Results • Conclusions and Future Research Content 2
  3. 3. 1. Context & Motivation 3 CAN WE GO GREENER? • Reducing “carbon footprint” and addressing other environmental issues • Cost risk associated with dependence on oil-based energy • Availability of government subsidies • Advances in alternative energy technology ICEs and PHEVs have almost unlimited driving-range capabilities (they can rapidly refuel at any service station throughout the route). However the driving range for an electric vehicle is constrained by the amount of electricity stored in its battery (it cannot rapidly recharge during the route).
  4. 4. 2. Introduction – VRP and Rich VRP Vehicle Routing Problem (VRP), is a combinatorial problem seeking to service a number of costumers with a fleet of vehicles (Dantzig and Ramser, 1959). 4 Customers (demand) Edge in a route Depot (resources) Caceres-Cruz, J., Arias, P., Guimarans, D., Riera, D., & Juan, A. A. (2014). Rich Vehicle Routing Problem: Survey. ACM Computing Surveys (CSUR), 47(2), 32. Rich VRP (Caceres et al., 2014) adds real life constraints to the base problem: • Heterogeneous VRP • Green VRP • Open Routes VRP
  5. 5. 3. Heterogeneous & Green Heterogeneous VRP, Different types of vehicles: • EV: Electric Vehicles • ICE: internal combustion engine • PHEV: plug-in- hybrid electric vehicles. 5 Green VRP, tries to minimize de ecological impact of different factors: • Fuel consumption • Electric Engines Objective: minimise the distance cost of using the greenest configuration
  6. 6. 4. How we solve it? (1/2) 6 CVRP* = CVRP with route maximum distance Round 1: ICE MDR: unlimited Assumed fleet: 2 ICEs + 3 EVs 1 1 2 3 4 3 4 5 2
  7. 7. 5. How we solve it? (2/2) 7 Notes: (a) Number of rounds <= Number of veh. types (b) If heterogeneity index  0 then Multi-round sols  VRP sols Round 1: ICE MDR: unlimited Assumed fleet: 2 ICEs + 3 EVs 1 2 3 4 5 1 2 3 4 5 CVRP* = CVRP with route maximum distance
  8. 8. 6. Results 8 Changing the distribution to greener vehicles we maintain the distance cost associated to each problem (benchmark’s used cost). At the same time we can choose between different configurations that can be used as a decision making tool.
  9. 9. 7. Conclusions & Future research 9 • Support the hypothesis that hybrid and electric vehicles can be used in routing problems without necessarily incurring significantly higher distance-based costs. • Numerical experiments demonstrate that this approach provides attractive solutions for all tested benchmarks. • Models that monetize the carbon footprint could be incorporated to evaluate solutions across an economic-environmental continuum. • The impact of topography could be explored. Caceres-Cruz, J., Arias, P., Guimarans, D., Riera, D., & Juan, A. A. (2014). Rich Vehicle Routing Problem: Survey. ACM Computing Surveys (CSUR), 47(2), 32, (indexed in ISI SCI, 2013 IF = 4.043, Q1). Juan, A. A., Goentzel, J., & Bektaş, T. (2014). Routing fleets with multiple driving ranges: Is it possible to use greener fleet configurations?. Applied Soft Computing, 21, 84-94, (indexed in ISI SCI, 2012 IF = 2.140, Q1).
  10. 10. 10 Angel A. Juan Computer, Multimedia & Telecommunication Dept. IN3 - UOC, Barcelona, SPAIN Tolga Bektas University of Southampton, Southampton, UK Jarrod Goentzel Massachusetts Institute of Technology, Cambridge, MA, USA Routing fleets with multiple driving ranges: is it possible to use greener fleet configurations? Presenting: Pol Arias, MSc Visiting Researcher IN3 - Smart Logistics & Production

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