5 research outputs found
New Valid Inequalities for the Two-Echelon Capacitated Vehicle Routing Problem
We introduce new valid inequalities for the two-echelon variant of the Capacitated
Vehicle Routing Problem (CVRP)In particular, a first group of inequalities is obtained
by extending to 2E-CVRP some of the most effective among the existing
CVRP valid inequalities. A second group of inequalities is explicitly derived for
the 2E-CVRP and concerns the flow feasibility at customer nodes and the satellitecustomer
route connectivity. The inequalities are then introduced in a Branch &
Cut algorithm. Computational results show that the proposed algorithm is able
both to solve to optimality many open literature instances and significantly reduce
the optimality gap for the remaining instances
Two-Echelon Vehicle and UAV Routing for Post-Disaster Humanitarian Operations with Uncertain Demand
Humanitarian logistics service providers have two major responsibilities
immediately after a disaster: locating trapped people and routing aid to them.
These difficult operations are further hindered by failures in the
transportation and telecommunications networks, which are often rendered
unusable by the disaster at hand. In this work, we propose two-echelon vehicle
routing frameworks for performing these operations using aerial uncrewed
autonomous vehicles (UAVs or drones) to address the issues associated with
these failures. In our proposed frameworks, we assume that ground vehicles
cannot reach the trapped population directly, but they can only transport
drones from a depot to some intermediate locations. The drones launched from
these locations serve to both identify demands for medical and other aids
(e.g., epi-pens, medical supplies, dry food, water) and make deliveries to
satisfy them. Specifically, we present two decision frameworks, in which the
resulting optimization problem is formulated as a two-echelon vehicle routing
problem. The first framework addresses the problem in two stages: providing
telecommunications capabilities in the first stage and satisfying the resulting
demands in the second. To that end, two types of drones are considered. Hotspot
drones have the capability of providing cell phone and internet reception, and
hence are used to capture demands. Delivery drones are subsequently employed to
satisfy the observed demand. The second framework, on the other hand, addresses
the problem as a stochastic emergency aid delivery problem, which uses a
two-stage robust optimization model to handle demand uncertainty. To solve the
resulting models, we propose efficient and novel solution approaches
Comparative analysis of models and performance indicators for optimal service facility location
This study investigates the optimal process for locating generic service facilities by applying and comparing several well-known basic models from the literature. At a strategic level, we emphasize that selecting the right location model to use could result in a problematic and possibly misleading task if not supported by appropriate quantitative analysis. For this reason, we propose a general methodological framework to analyze and compare the solutions provided by several models to obtain a comprehensive evaluation of the location decisions from several different perspectives. Therefore, a battery of key performance indicators (KPIs) has been developed and calculated for the different models’ solutions. Additional insights into the decision process have been obtained through a comparative analysis. The indicators involve topological, coverage, equity, robustness, dispersion, and accessibility aspects. Moreover, a specific part of the analysis is devoted to progressive location interventions over time and identifying core location decisions. Results on randomly generated instances, which simulate areas characterized by realistic geographical or demographic features, are reported to analyze the models’ behavior in different settings and demonstrate the methodology’s general applicability. Our experimental campaign shows that the p-median model behaves very well against the proposed KPIs. In contrast, the maximal covering problem and some proposed back-up coverage models return very robust solutions when the location plan is implemented through several progressive interventions over time
New Valid Inequalities for the Two-Echelon Capacitated Vehicle Routing Problem
We introduce new valid inequalities for the two-echelon variant of the Capacitated Vehicle Routing Problem (CVRP)In particular, a first group of inequalities is obtained by extending to 2E-CVRP some of the most effective among the existing CVRP valid inequalities. A second group of inequalities is explicitly derived for the 2E-CVRP and concerns the flow feasibility at customer nodes and the satellitecustomer route connectivity. The inequalities are then introduced in a Branch & Cut algorithm. Computational results show that the proposed algorithm is able both to solve to optimality many open literature instances and significantly reduce the optimality gap for the remaining instances