Multi-objective Green Delivery Routing with Flexible Time Windows: Minimizing Fossil Fuel Consumption versus Maximizing Quality of Service

Abstract: The Delivery Routing Problem with Time Windows (DRTW) is a logistics optimization problem that involves determining the most efficient route for a fleet of vehicles to deliver goods or services to customers within specific time windows. The challenge is to satisfy customer demands while minimizing delivery costs and maximizing vehicle utilization. DRTW considers various constraints, such as vehicle capacity, travel time, and time windows, and aims to find a solution that satisfies all these constraints while minimizing the total travel time and distance. Our proposal is to develop a multiobjective solver for delivery routing problems with hybrid trucks. These trucks use diesel engines for long haul distances and electric engines for short range drives within urban areas. We assume that customers have some flexibility with regards to time windows and can provide a ranked list of preferred time windows. The selection of the time window introduces a decision variable for each delivery that influences the objective of user satisfaction and fuel consumption, which are potentially conflicting. For example, using a less preferred time window might help to avoid a detour and thereby reduce fuel consumption. Our solver aims to meet the client's preferences for delivery time windows and provide a cost-efficient delivery route that minimizes fossil fuel consumption. We use tri-objective optimization algorithms to solve this problem and analyze the shape of the Pareto frontier. The route planner can select a good compromise solution by identifying knee point solutions on the 3-D Pareto optimal surface. Our solver is based on previous studies for vehicle routing and green label models for flexible time windows. For fuel cost estimates and hybrid engine modeling, we use insights summarized in existing literature. Lastly, we use the open-source DESDEO solver, developed by the University of Jyväskylä, Finland, which allows for a rich variety of visual analytics packages for result visualization and subsequent interactive decision making.

Keywords: Green logistics, Delivery routing, Multi-objective optimization, Flexible time windows, Hybrid transport

Publication details: Conference abstract presented at the CM3 – Transport 2023: New Greener and Digital Modern Transport – its Challenges in Design Methods, Tools and Technologies (ECCOMAS Thematic Conference) (CM3 Transport 2023), 15-17 May 2023, Jyväskylä, Finland. Published in: CM3 – Transport 2023: Book of Abstracts and Programme (Reports on Scientific Computing and Optimization 1/2023), pp. 39. Publisher: University of Jyväskylä. ISBN: 978-951-39-9610-9.

Acknowledgement: Burak Gülmez acknowledges financial support under the TÜBİTAK 2219 postdoctoral fellowship programme (Scientific and Technological Research Council of Türkiye).

How to cite / Kaynak gösterimi

APA 7: Emmerich, M., Gülmez, B., & Fan, Y. (2023, May). Multi-objective Green Delivery Routing with Flexible Time Windows: Minimizing Fossil Fuel Consumption versus Maximizing Quality of Service [Conference abstract]. In L. Kettunen, P. Neittaanmäki, T. Tuovinen, & D. Knoerzer (Eds.), CM3 – Transport 2023: Book of Abstracts and Programme (Reports on Scientific Computing and Optimization 1/2023) (p. 39). University of Jyväskylä. CM3 – Transport 2023: New Greener and Digital Modern Transport – its Challenges in Design Methods, Tools and Technologies (ECCOMAS Thematic Conference) (CM3 Transport 2023), Jyväskylä, Finland. https://doi.org/10.5281/zenodo.23036864

IEEE: M. Emmerich, B. Gülmez, and Y. Fan, "Multi-objective Green Delivery Routing with Flexible Time Windows: Minimizing Fossil Fuel Consumption versus Maximizing Quality of Service," in CM3 – Transport 2023: Book of Abstracts and Programme (Reports on Scientific Computing and Optimization 1/2023), Jyväskylä, Finland, May 2023, p. 39, ISBN: 978-951-39-9610-9, doi: 10.5281/zenodo.23036864.

Chicago: Emmerich, Michael, Burak Gülmez, and Yingjie Fan. 2023. "Multi-objective Green Delivery Routing with Flexible Time Windows: Minimizing Fossil Fuel Consumption versus Maximizing Quality of Service." In CM3 – Transport 2023: Book of Abstracts and Programme (Reports on Scientific Computing and Optimization 1/2023), 39. Jyväskylä, Finland: University of Jyväskylä. https://doi.org/10.5281/zenodo.23036864.

MLA 9: Emmerich, Michael, et al. "Multi-objective Green Delivery Routing with Flexible Time Windows: Minimizing Fossil Fuel Consumption versus Maximizing Quality of Service." CM3 – Transport 2023: Book of Abstracts and Programme (Reports on Scientific Computing and Optimization 1/2023), University of Jyväskylä, 2023, p. 39. https://doi.org/10.5281/zenodo.23036864.

Harvard: Emmerich, M., Gülmez, B. and Fan, Y. (2023) 'Multi-objective Green Delivery Routing with Flexible Time Windows: Minimizing Fossil Fuel Consumption versus Maximizing Quality of Service', in CM3 – Transport 2023: Book of Abstracts and Programme (Reports on Scientific Computing and Optimization 1/2023). Jyväskylä, Finland: University of Jyväskylä, pp. 39. doi: 10.5281/zenodo.23036864.

BibTeX:

@inproceedings{Emmerich2023multiobjective,
  author    = {Emmerich, Michael and Gülmez, Burak and Fan, Yingjie},
  title     = {Multi-objective Green Delivery Routing with Flexible Time Windows: Minimizing Fossil Fuel Consumption versus Maximizing Quality of Service},
  booktitle = {CM3 – Transport 2023: Book of Abstracts and Programme (Reports on Scientific Computing and Optimization 1/2023)},
  year      = {2023},
  month     = {may},
  pages     = {39},
  address   = {Jyväskylä, Finland},
  publisher = {University of Jyväskylä},
  isbn      = {978-951-39-9610-9},
  doi       = {10.5281/zenodo.23036864},
  url       = {https://doi.org/10.5281/zenodo.23036864}
}