Internal report cluster 1: Urban freight innovations and solutions for sustainable deliveries (1/4)

Technical report about sustainable urban freight solutions, part 1 of

Subproblem Separation in Logic-Based Benders\u27 Decomposition for the Vehicle Routing Problem with Local Congestion

Subproblem separation is a common strategy for the acceleration of the logic-based Benders\u27 decomposition (LBBD). However, it has only been applied to problems with an inherently separable subproblem structure. This paper proposes a new method to separate the subproblem using the connected components algorithm. The subproblem separation is applied to the vehicle routing problem with local congestion (VRPLC). Accordingly, new Benders\u27 cuts are derived for the new subproblem formulation. The computational experiments evaluate the effectiveness of subproblem separation for different methods applying new cuts. It is shown that subproblem separation significantly benefits the LBBD scheme

Internal report cluster 1: Urban freight innovations and solutions for sustainable deliveries (2/4)

Technical report about sustainable urban freight solutions, part 2 of

Last-mile logistics optimization in the on-demand economy

L'abstract è presente nell'allegato / the abstract is in the attachmen

Time and multiple objectives in scheduling and routing problems

Many optimization problems encountered in practice are multi-objective by nature, i.e., different objectives are conflicting and equally important. Many times, it is not desirable to drop some of them or to optimize them in a composite single objective or hierarchical manner. Furthermore, cost parameters change over time which makes optimization problems harder. For instance, in the transport sector, travel costs are a function of travel time which changes depending on the time of the day a vehicle is travelling (e.g., due to road congestion). Road congestion results in tremendous delays which lead to a decrease in the service quality and the responsiveness of logistic service providers. In Chapter 2, we develop a generic approach to deal with Multi-Objective Scheduling Problems (MOSPs) with State-Dependent Cost Parameters. The aim is to determine the set of Pareto solutions that capture the trade offs between the different conflicting objectives. Due to the complexity of MOSPs, an efficient approximation based on dynamic programming is developed. The approximation has a provable worse case performance guarantee. Even though the generated approximate Pareto front consist of fewer solutions, it still represents a good coverage of the true Pareto front. Furthermore, considerable gains in computation times are achieved. In Chapter 3, the developed methodology is validated on the multi-objective timedependent knapsack problem. In the classical knapsack problem, the input consists of a knapsack with a finite capacity and a set of items, each with a certain weight and a cost. A feasible solution to the knapsack problem is a selection of items such that their total weight does not exceed the knapsack capacity. The goal is to maximize the single objective function consisting of the total pro t of the selected items. We extend the classical knapsack problem in two ways. First, we consider time-dependent profits (e.g., in a retail environment profit depends on whether it is Christmas or not)

Minimum cost VRP with time-dependent speed data and congestion charge

A heuristic algorithm, called LANCOST, is introduced for vehicle routing and scheduling problems to minimize the total travel cost, where the total travel cost includes fuel cost, driver cost and congestion charge. The fuel cost required is influenced by the speed. The speed for a vehicle to travel along any road in the network varies according to the time of travel. The variation in speed is caused by congestion which is greatest during morning and evening rush hours. If a vehicle enters the congestion charge zone at any time, a fixed charge is applied. A benchmark dataset is designed to test the algorithm. The algorithm is also used to schedule a fleet of delivery vehicles operating in the London area