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2775. Optimization of electric mobility investments in Kathmandu
Invited abstract in session TB-18: Optimization of sustainable urban mobiltiy II, stream Sustainable Cities.
Tuesday, 10:30-12:00Room: 42 (building: 116)
Authors (first author is the speaker)
| 1. | Eric VONG
|
| DTU Management, Department of Technology, Management and Economics, Technical University of Denmark | |
| 2. | David Ruehmkorf
|
| Technical University of Denmark | |
| 3. | Dario Fiorica
|
| Technical University of Denmark | |
| 4. | George Panagakos
|
| Department of Technology, Management and Economics, Technical University of Denmark | |
| 5. | Michael Bruhn Barfod
|
| Department of Management Engineering, Technical University of Denmark |
Abstract
The EU-funded SOLUTIONSplus project aims at promoting e-mobility in 9 cities around the world, including Kathmandu, Nepal. This paper develops a systematic approach for selecting the fleet of electric vehicles (among 8 different types including buses, shuttle vans, 3-wheelers, trucks, and waste collectors) that maximizes societal benefit within a specific budget. It introduces a framework combining Multi-Criteria Decision Making (MCDM) and optimization techniques. The MCDM aspect employs over twenty key performance indicators to assess the impact of various alternatives against specific attributes that include financial viability, alignment with institutional framework, effects on climate change and environment, effects on society and the wider economy. A set of weights defines the values and priorities of the local stakeholders. As this problem is non-linear and the objective function is discontinuous, a metaheuristic is needed to find a good solution. It appears that the Evolutionary Algorithm produces good solutions at reasonable computational times. The proposed framework can identify an optimal solution configuration for problems with discontinuous objective functions and predefined preferences. In practical terms, this research not only advances the field of urban mobility but also offers a scalable model for other cities facing similar challenges.
Keywords
- Decision Analysis
- Metaheuristics
- OR in Sustainability
Status: accepted
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