Multi-objective modelling of a roadside mowing problem: a case study in France - 2022 ICE- IAMOT

Описание: Paper preprint: http://www.simonamihaita.com/papers/I...

The roadside maintenance is a significant challenge for many territories around the world. For safety reason, these roadsides have to be maintained regularly, which has an important economic impact requirement significant investment of staff and material. This paper addresses the problem of planning optimal trajectories of mowing machines within a dedicated territory in order to meet several objective criteria such as: minimising the travel distance, the number of mowing machines, as well as minimising the time and the cost associated with each yearly operation. Firstly, we define the mathematical methodology of the multi-objective criteria that we need to calculate. Secondly, we propose a clustering approach based on the k-means algorithm in order to identify the best sub-sectors of road sections that each technical centre needs to plan in order and maintain using existing equipment. Thirdly, we apply an optimal routing between each cluster based on TomTom API routing and identify the distance, cost and travel time associated with various mowing scenarios. Finally, we analyse the best setup that would satisfy all criteria in the current case study area and present future projections of a local versus global optimisation approach.

Presenter:
Simona Mihaita,
Head of the Future Mobility Lab
Senior Lecturer University of Technology Sydney

Co-authors
Brunelle Marche, ERPI, Nancy
Mauricio Camargo, ERPI, Nancy
Iman Rahimi, UTS, Australia

Industry partner: Christophe BACHMANN, Noremat

21st of June 2022