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1351. Scheduling Large-Scale Infrastructure Renovation Projects Minimizing Emissions Using a Hybrid Genetic Algorithm
Invited abstract in session MD-23: Scheduling for sustainability, stream Circular Economy, Remanufacturing and Recycling .
Monday, 14:30-16:00Room: 82 (building: 116)
Authors (first author is the speaker)
| 1. | Robbert Bosch
|
| BMS, University of Twente | |
| 2. | Patricia Rogetzer
|
| Department Industrial Engineering & Business Information Systems, University of Twente | |
| 3. | Wouter van Heeswijk
|
| University of Twente | |
| 4. | Martijn Mes
|
| IEBIS, University of Twente |
Abstract
The safety and accessibility of infrastructure such as bridges and quay walls in cities is important for the everyday life of its inhabitants. However, due to wear and tear over the years, these infrastructure pieces need to be maintained or renovated. These large-scale renovation projects generate CO2 emissions by the material production chain, the logistics surrounding the supply of material and equipment and removal of waste, and the increased traffic due to traffic diversions. The magnitude of these emissions can be difficult to predict, especially when multiple projects are executed in parallel due to time pressure. Parallel execution of projects may yield economies of scale regarding logistics but can also cause excessive congestion. Optimizing the schedule of these projects by finding the right combinations of projects to perform simultaneously can reduce the total emissions and reduce project delays. To aid decision-making, we use multi-objective optimization to minimize total emissions while simultaneously reducing project delays. We present a Hybrid Genetic Algorithm to produce a partial Pareto frontier of schedules for large-scale urban infrastructure renovation projects. This research applies the described solution method to the problem of renovation of bridges and quay walls in Amsterdam. The results illustrate the trade-off between sustainability and tempo of renovations.
Keywords
- Supply Chain Management
- OR in Environment and Climate change
- Multi-Objective Decision Making
Status: accepted
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