15h30 - 15h55
The pollution-routing problem with stochastic travel times
We will introduce a new variant of the Pollution Routing Problem, new stochastic speed limits are considered. We will describe a single-stage stochastic programming model with complete recourse. Recourse variables correspond to delays experienced in servicing the customers and to violations of the speed limits, the expected cost is minimised.
15h55 - 16h20
Scheduling the replenishments of network of clients with gasolines by a heterogeneous fleet of compartmented vehicles: A decomposition approach
In this paper, we solve a rich variant of the general inventory and routing problem from the point of view of a specific gasolines’ dealer company buying four types of gasolines from an unique refinery, storing them in four privately owned depots, doing business with four external transportation companies with limited-capacity and variable-availability heterogeneous fleet of compartmented vehicles. In addition to replenishments costs, a minimal fleet of vehicles must be assigned and routed within a week to a network of three types of clients: regular gas stations, fishing boats gas stations and bakeries. We propose a decomposition approach based on the bipartite acyclic structure of the network of products. Our model is tested on real-world data from a gasolines’ dealer company.
Keywords: Inventory and Routing problem, heterogeneous fleet of compartmented vehicles, bipartite acyclic network of products, decomposition approach.
16h20 - 16h45
The truck driver scheduling problem with idling options
We introduce the Truck Driver Scheduling Problem with Idling Options. The aim is to minimize the costs of driving, fuel and C02 emissions, and idling. We explore the use of cleaner alternatives to idling such as resting at Electrified Parking Space or using Auxiliary Power Unit while idling.
16h45 - 17h10
Production and inventory routing with an assembly structure
We aim at integrating the production planning of a single end item at a plant with the inbound collection planning of several components, sourced from different suppliers. The decisions relate to the production and routing plans. We propose a mathematical formulation and a heuristic algorithm to solve the problem.