slides_thesis_proposal

Work Schedule III

Stage 3

11. Write the thesis document. [4 months]
12. Present the thesis.

51/72

Thanks for your attention.
Questions?

52/72

Matheuristic Algorithms
for Green Vehicle Routing Problems

Thesis Project

Alejandro Fernández Gil

Director: Dr. Carlos Castro
Co-Director: Dr. Eduardo Lalla-Ruiz

Departamento de Informática
Universidad Técnica Federico Santa María

July 10, 2020, Valparaíso, Chile

53/72

ICCL2020

Cumulative VRP with Time Windows

• Presents hard and soft time windows constraints for CumVRP.
• Investigate the contribution of soft time windows penalty and

environmental related costs.

54/72

ICCL2020

Mathematical programming model

Define:

• xij ∈ {0, 1}, ∀i, j ∈ V : 0-1 if the arc (i, j) is in the tour of a vehicle.
• wij , ∀i, j ∈ V : the flow on the arc (i, j) if the vehicle (traveler) goes from i to j,

and 0 otherwise.
• Ui , ∀i ∈ V : the upper bounds of the time window during which the customer i

must be served.
• Si , ∀i ∈ V : the service time to serve customer i.
• dij : representing the travel distance between each arc (i, j) ∈ A.
• k: number of vehicles.
• ti : the real time at which the service begins in the customer i.
• yi ∈ {0, 1}, ∀i ∈ V : 0-1 if not complied with the upper limit for the time

window in the customer i.
• P: penalty value.

The CumVRP with time windows can be modeled as a MILP:

hard TW soft TW

VV V

f1 = dij wij f3 = (P(ti + Si − Ui ))yi

i=0 j=0 i =1

f2 = Mk Min λ1f1 + f2 + λ3f3
Min f1 + f2
55/72

ICCL2020

Decomposition-based Matheuristic
Cluster First

56/72

ICCL2020

Decomposition-based Matheuristic
Cluster First

57/72

ICCL2020

Decomposition-based Matheuristic
Cluster First

58/72

ICCL2020

Decomposition-based Matheuristic
Route Second (MILP)

59/72

ICCL2020

Decomposition-based Matheuristic
Local Search

60/72

ICCL2020

Results

• Considering time window violations, the routes obtained have lower
cumulative costs.

• Cumulative cost can be25/5/2020 proportional to the emissions of GHGs,about:blank then by
allowing some of dissatisfaction in the quality of service to customers,
allowing to reduce the emissions.

Instances:
PRPLIB [DBL12]
- 9 groups
- 10 and 200
customers.

Cost emissions is obtained using as a emission factors for averagely loaded
diesel for rigid vehicles weighted between 7.5 t and 17 t a value of 0.41693 kg
CO2e/tkm suggested by DEFRA [DP10].

61/72

POPMUSIC

Partial Optimization Metaheuristic Under Special Intensification Conditions

• Eduardo Lalla-Ruiz and Stefan Voß, A popmusic approach
for the multi-depot cumulative capacitated vehicle routing
problem, Optimization Letters (2019), 1–21.

• Eduardo Lalla-Ruiz and Stefan Voß, Popmusic as a
matheuristic for the berth allocation problem, Annals of
Mathematics and Artificial Intelligence 76 (2016), no. 1-2,
173–189.

• Eduardo Lalla-Ruiz, Silvia Schwarze, and Stefan Voß, A
matheuristic approach for the p-cable trench problem,
Learning and Intelligent Optimization, Springer International
Publishing, 2016, pp. 247–252.

62/72

References I

R. Ayadi, A. E. ElIdrissi, Y. Benadada, and A. El Hilali Alaoui,
Evolutionary algorithm for a green vehicle routing problem with multiple
trips, 2014 International Conference on Logistics Operations Management,
2014, pp. 148–154.

Claudia Archetti and M Grazia Speranza, A survey on matheuristics for
routing problems, EURO Journal on Computational Optimization 2
(2014), no. 4, 223–246.

Kyle E. C. Booth and J. Christopher Beck, A constraint programming
approach to electric vehicle routing with time windows, Integration of
Constraint Programming, Artificial Intelligence, and Operations Research
(Cham) (Louis-Martin Rousseau and Kostas Stergiou, eds.), Springer
International Publishing, 2019, pp. 129–145.

Tolga Bektaş, Jan Fabian Ehmke, Harilaos N. Psaraftis, and Jakob
Puchinger, The role of operational research in green freight transportation,
European Journal of Operational Research 274 (2019), no. 3, 807 – 823.

63/72

References II

Didem Cinar, Beyzanur Cayir Ervural, Konstantinos Gakis, and Panos M.
Pardalos, Constructive algorithms for the cumulative vehicle routing
problem with limited duration, pp. 57–86, Springer International
Publishing, Cham, 2017.

N. Christofides and S. Eilon, An algorithm for the vehicle-dispatching
problem, Journal of the Operational Research Society 20 (1969), no. 3,
309–318.

Didem Cinar, Konstantinos Gakis, and Panos M Pardalos, Reduction of
co2 emissions in cumulative multi-trip vehicle routing problems with
limited duration, Environmental Modeling & Assessment 20 (2015), no. 4,
273–284.

G. Clarke and J. W. Wright, Scheduling of vehicles from a central depot
to a number of delivery points, Operations Research 12 (1964), no. 4,
568–581.

Emrah Demir, Tolga Bektaş, and Gilbert Laporte, An adaptive large
neighborhood search heuristic for the pollution-routing problem, European
Journal of Operational Research 223 (2012), no. 2, 346 – 359.

64/72

References III

Emrah Demir, Tolga Bektaş, and Gilbert Laporte, A review of recent
research on green road freight transportation, European Journal of
Operational Research 237 (2014), no. 3, 775 – 793.

Said Dabia, Emrah Demir, and Tom Van Woensel, An exact approach for
a variant of the pollution-routing problem, Transportation Science 51
(2017), no. 2, 607–628.

Food Statistics Pocketbook Defra and Ecosystems Evidence Plan,
Department for environment, Food and Rural Affairs (2010), 1–200.

George B Dantzig and John H Ramser, The truck dispatching problem,
Management science 6 (1959), no. 1, 80–91.

Airam Expósito, Christopher Expósito, Julio Brito, and José A. Moreno,
Solving an eco-efficient vehicle routing problem for waste collection
with grasp, Intelligent Distributed Computing XII (Cham) (Javier Del Ser,
Eneko Osaba, Miren Nekane Bilbao, Javier J. Sanchez-Medina, Massimo
Vecchio, and Xin-She Yang, eds.), Springer International Publishing, 2018,
pp. 215–224.

65/72

References IV

Sevgi Erdoğan and Elise Miller-Hooks, A green vehicle routing problem,
Transportation Research Part E: Logistics and Transportation Review 48
(2012), no. 1, 100 – 114, Select Papers from the 19th International
Symposium on Transportation and Traffic Theory.

Alejandro Fernández, Mariam Gómez, Eduardo Lalla-Ruíz, and Carlos
Castro, Cumulative vrp with time windows: a trade-off analysis,
(unpublished), International Conference on Computational Logistics 2020.

Aurélien Froger, Jorge E. Mendoza, Ola Jabali, and Gilbert Laporte, A
Matheuristic for the Electric Vehicle Routing Problem with Capacitated
Charging Stations, Research report, Centre interuniversitaire de recherche
sur les reseaux d’entreprise, la logistique et le transport (CIRRELT), June
2017.
Yanling Feng, Ren-Qian Zhang, and Guozhu Jia, Vehicle routing problems
with fuel consumption and stochastic travel speeds, Mathematical
Problems in Engineering 2017 (2017), 1–16.

66/72

References V

Frederico Gonçalves, Sónia R Cardoso, Susana Relvas, and APFD
Barbosa-Póvoa, Optimization of a distribution network using electric
vehicles: A vrp problem, Proceedings of the IO2011-15 Congresso da
associação Portuguesa de Investigação Operacional, Coimbra, Portugal,
2011, pp. 18–20.

Dominik Goeke, Granular tabu search for the pickup and delivery problem
with time windows and electric vehicles, European Journal of Operational
Research 278 (2019), no. 3, 821 – 836.

Daya Ram Gaur and Rishi Ranjan Singh, Cumulative vehicle routing
problem: A column generation approach, Algorithms and Discrete Applied
Mathematics (Cham) (Sumit Ganguly and Ramesh Krishnamurti, eds.),
Springer International Publishing, 2015, pp. 262–274.

Che-Fu Hsueh, The green vehicle routing problem with stochastic travel
speeds, pp. 1–12, ASCE Library, 2016.

67/72

References VI

İmdat Kara, Bahar Y. Kara, and M. Kadri Yetis, Energy minimizing
vehicle routing problem, Combinatorial Optimization and Applications
(Berlin, Heidelberg) (Andreas Dress, Yinfeng Xu, and Binhai Zhu, eds.),
Springer Berlin Heidelberg, 2007, pp. 62–71.

İmdat Kara, Bahar Yetiş Kara, and M Kadri Yetiş, Cumulative vehicle
routing problems, Vehicle routing problem, In-Teh, 2008, pp. 85–98.

Iman Kazemian, Masoud Rabbani, and Hamed Farrokhi-Asl, A way to
optimally solve a green time-dependent vehicle routing problem with time
windows, Computational and Applied Mathematics 37 (2018), no. 3,
2766–2783.

Raphael Kramer, Anand Subramanian, Thibaut Vidal, and Lucídio dos
Anjos F. Cabral, A matheuristic approach for the pollution-routing
problem, European Journal of Operational Research 243 (2015), no. 2,
523 – 539.

Canhong Lin, K.L. Choy, G.T.S. Ho, S.H. Chung, and H.Y. Lam, Survey
of green vehicle routing problem: Past and future trends, Expert Systems
with Applications 41 (2014), no. 4, Part 1, 1118 – 1138.

68/72

References VII

Yan Li, Ming K Lim, and Ming-Lang Tseng, A green vehicle routing model
based on modified particle swarm optimization for cold chain logistics,
Industrial Management & Data Systems (2019), 473–494.

Eduardo Lalla-Ruiz and Stefan Voß, A popmusic approach for the
multi-depot cumulative capacitated vehicle routing problem, Optimization
Letters (2019), 1–21.

Yongbo Li, Hamed Soleimani, and Mostafa Zohal, An improved ant colony
optimization algorithm for the multi-depot green vehicle routing problem
with multiple objectives, Journal of Cleaner Production 227 (2019), 1161
– 1172.

Karl Menger, Das botenproblem, Ergebnisse eines mathematischen
kolloquiums 2 (1932), no. 4, 11–12.

Alejandro Montoya, Christelle Guéret, Jorge E. Mendoza, and Juan G.
Villegas, A multi-space sampling heuristic for the green vehicle routing
problem, Transportation Research Part C: Emerging Technologies 70
(2016), 113 – 128.

69/72

References VIII

Samuel Nucamendi-Guillén, Francisco Angel-Bello, Iris Martínez-Salazar,
and Alvaro E. Cordero-Franco, The cumulative capacitated vehicle routing
problem: New formulations and iterated greedy algorithms, Expert
Systems with Applications 113 (2018), 315 – 327.

Narges Norouzi, Mohsen Sadegh-Amalnick, and Reza
Tavakkoli-Moghaddam, Modified particle swarm optimization in a
time-dependent vehicle routing problem: minimizing fuel consumption,
Optimization Letters 11 (2017), no. 1, 121–134.

PUBLIC SECTOR PROTOCOL, The greenhouse gas protocol initiative, A
Corporate Accounting and Reporting Standard (2008), 1–155.

Amirhosein Patoghi, Zohreh Shakeri, and Mostafa Setak, A time
dependent pollution routing problem in multi-graph, International Journal
of Engineering 30 (2017), no. 2, 234–242.

Robert A. Russell, Technical note—an effective heuristic for the m-tour
traveling salesman problem with some side conditions, Operations
Research 25 (1977), no. 3, 517–524.

70/72