Roghayeh Hajizadeh
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Roghayeh Hajizadeh has a total of 1 co-authors. Here are the top co-authors by number of shared publications:
- Kaj Holmberg
Linköping Institute of Technology
1 shared publication
Latest Publications
- Open Access
- 15 September 2023
- Published by Linkoping University Electronic Press
Optimization of Snow Removal in Cities
Removing snow in a city is an unavoidable task in Nordic countries like Sweden. A number of streets in an area need to be cleared of snow by a limited number of vehicles and the tours for the vehic ...
- 15 September 2023
- Published by Linkoping University Electronic Press
Open AccessOptimization of Snow Removal in Cities
Removing snow in a city is an unavoidable task in Nordic countries like Sweden. A number of streets in an area need to be cleared of snow by a limited number of vehicles and the tours for the vehic ...
- Open Access
A branch‐and‐dive heuristic for single vehicle snow removal
This paper deals with planning of a tour for a vehicle to clear a certain set of streets in a city of snow. Our previous results on the problem contain a heuristic based on reformulation to an asymmetric traveling salesman problem (ATSP) which yields feasible solutions and upper bounds, and a relaxation of a MIP model for obtaining lower bounds. The goal now is to try to improve the solutions and bounds. In this paper we describe a branch‐and‐dive heuristic which is based on branch‐and‐bound principles. We discuss how branching can be done so that the fixations can be utilized in both the relaxation and the ATSP model, and how the search for better solutions can be done. The heuristic has been implemented and applied to real life city networks. The method is shown to outperform two other heuristics for the ATSP with precedence constraints.
Open AccessA branch‐and‐dive heuristic for single vehicle snow removal
This paper deals with planning of a tour for a vehicle to clear a certain set of streets in a city of snow. Our previous results on the problem contain a heuristic based on reformulation to an asymmetric traveling salesman problem (ATSP) which yields feasible solutions and upper bounds, and a relaxation of a MIP model for obtaining lower bounds. The goal now is to try to improve the solutions and bounds. In this paper we describe a branch‐and‐dive heuristic which is based on branch‐and‐bound principles. We discuss how branching can be done so that the fixations can be utilized in both the relaxation and the ATSP model, and how the search for better solutions can be done. The heuristic has been implemented and applied to real life city networks. The method is shown to outperform two other heuristics for the ATSP with precedence constraints.