A Joint Demand and Supply Management Approach to Large Scale Urban Evacuation Planning: Evacuate or Shelter-in-Place, Staging and Dynamic Resource Allocation

Urban evacuation management is challenging to implement as it requires planning and coordination over a large geographical area. To address these challenges and to bolster evacuation planning and management, joint supply and demand management strategies should be considered. In this study, we explore and jointly optimize evacuate or shelter-in-place, dynamic resource allocation, and staging decisions … Read more

Solving the Home Service Assignment, Routing, and Appointment Scheduling (H-SARA) problem with Uncertainties

The Home Service Assignment, Routing, and Appointment scheduling (H-SARA) problem integrates the strategical fleet-sizing, tactical assignment, operational vehicle routing and scheduling subproblems at different decision levels, with a single period planning horizon and uncertainty (stochasticity) from the service duration, travel time, and customer cancellation rate. We propose a two-stage stochastic mixed-integer linear programming model for … Read more

Optimal Eco-Routing for Hybrid Vehicles with Mechanistic/Data-Driven Powertrain Model Embedded

Hybrid Electric Vehicles (HEVs) are regarded as an important (transition) element of sustainable transportation. Exploiting the full potential of HEVs requires (i) a suitable route selection and (ii) suitable power management, i.e., deciding on the split between combustion engine and electric motor usage as well as the mode of the electric motor, i.e., driving or … Read more

Dynamic Repositioning in Free-Floating Bike Sharing Systems Using Approximate Dynamic Programming

In bike sharing systems, the spatiotemporal imbalance of bike flows leads to shortages of bikes in some areas and overages in some others, depending on the time of the day, resulting in user dissatisfaction. Repositioning needs to be performed timely to deal with the spatiotemporal imbalance and to meet customer demand in time. In this … Read more

The value of stochastic crowd resources and strategic location of mini-depots for last-mile delivery: A Benders decomposition approach

Crowd-shipping is an emergent solution to avoid the negative effects caused by the growing demand for last-mile delivery services. Previous research has studied crowd-shipping typically at an operational planning level. However, the study of support infrastructure within a city logistics framework has been neglected, especially from a strategic perspective. We investigate a crowd-sourced last-mile parcel … Read more

Maintenance Optimization of Wagons Mix

This work proposes to create a tool for support for cost reduction in wagon maintenance through the distribution of the annual plan in workshops. The distribution depends on the type of wagon, the scope of the maintenance service that each workshop serves, and the capacity that is supported by the workshops. This plan is a … Read more

A Chance-Constrained Two-Echelon Vehicle Routing Problem with Stochastic Demands

Two-echelon distribution systems are often considered in city logistics to maintain economies of scale and satisfy the emission zone requirements in the cities. In this work, we formulate the two-echelon vehicle routing problem with stochastic demands as a chance-constrained stochastic optimization problem, where the total demand of the customers in each second-echelon route should fit … Read more

Decomposition strategies for vehicle routing heuristics

Decomposition techniques are an important component of modern heuristics for large instances of vehicle routing problems. The current literature lacks a characterisation of decomposition strategies and a systematic investigation of their impact when integrated into state-of-the-art heuristics. This paper fills this gap: we discuss the main characteristics of decomposition techniques in vehicle routing heuristics, highlight … Read more

Robust Vehicle Routing under Uncertainty via Branch-Price-and-Cut

This paper contemplates how branch-price-and-cut solvers can be employed along with the robust optimization paradigm to address parametric uncertainty in the context of vehicle routing problems. In this setting, given postulated uncertainty sets for customer demands and vehicle travel times, one aims to identify a set of cost-effective routes for vehicles to traverse, such that … Read more

Improving Column-Generation for Vehicle Routing Problems via Random Coloring and Parallelization

We consider a variant of the Vehicle Routing Problem (VRP) where each customer has a unit demand and the goal is to minimize the total cost of routing a fleet of capacitated vehicles from one or multiple depots to visit all customers. We propose two parallel algorithms to efficiently solve the column-generation based linear-programming relaxation … Read more