Winter road maintenance planning involves a variety of decision-making problems related to the routing of vehicles for spreading chemicals and abrasives, for plowing roadways and sidewalks, for loading snow into trucks, and for transporting snow to disposal sites. In this paper, we present a model and two heuristic solution approaches based on mathematical optimization for the routing of vehicles for snow plowing operations in urban areas. Given a district and a single depot where a number of vehicles are based, the problem is to determine a set of routes, each performed by a single vehicle that starts and ends at the district's depot, such that all road segments are serviced while satisfying a set of operational constraints and minimizing a time objective. The formulation models general precedence relation constraints with no assumption on class connectivity, different service and deadhead speed possibilities, separate pass requirements for multi-lane road segments, class upgrading possibilities, and vehicleroad segment dependencies. Several extensions, such as turn restrictions, load balancing constraints, and tandem service requirements, which are required in a real-life application, are also discussed. Two objectives are considered: a hierarchical objective and a makespan objective. The resulting model is based on a multi-commodity network flow structure to impose the connectivity of the route performed by each vehicle. The two solution strategies were tested on data from the City of Dieppe in Canada.
This paper considers the problem of designing a supply chain assuming routing decisions. The objective is to select a subset of depots to open from a set of candidates, the inventory policies for a two-echelon system, and the set of routes to perform distribution from the upper echelon to the next by a homogeneous fleet of vehicles over a finite planning horizon considering deterministic demand. To solve the problem, a partition is proposed using a Dantzig-Wolfe formulation on the routing variables. A hybridization between column generation, Lagrangian relaxation, and local search is presented within a heuristic procedure. Results demonstrate the capability of the algorithm to compute high quality solutions and empirically estimate the improvement in the cost function of the proposed model at up to 9% compared to the sequential approach. Furthermore, the suggested pricing problem is a new variant of the shortest path problem with applications in urban transportation and telecommunications.
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