Parallel branch and cut for capacitated vehicle routing
Parallel Computing - Special issue: Parallel computing in logistics
A compact model and tight bounds for a combined location-routing problem
Computers and Operations Research
Formulations and relaxations for a multi-echelon capacitated location-distribution problem
Computers and Operations Research
Models for Evaluating and Planning City Logistics Systems
Transportation Science
A simulated annealing heuristic for the capacitated location routing problem
Computers and Industrial Engineering
A Branch-and-Cut method for the Capacitated Location-Routing Problem
Computers and Operations Research
The Two-Echelon Capacitated Vehicle Routing Problem: Models and Math-Based Heuristics
Transportation Science
A Branch-and-Cut Algorithm for the Symmetric Two-Echelon Capacitated Vehicle Routing Problem
Transportation Science
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In this paper we address the Two-Echelon Vehicle Routing Problem (2E-VRP), an extension of the classical Capacitated VRP, where the delivery from a single depot to the customers is managed by routing and consolidating the freight through intermediate depots called satellites. We present a family of Multi-Start heuristics based on separating the depot-to-satellite transfer and the satellite-to-customer delivery by iteratively solving the two resulting routing subproblems, while adjusting the satellite workloads that link them. The common scheme on which all the heuristics are based consists in, after having found an initial solution, applying a local search phase, followed by a diversification; if the new obtained solutions are feasible, then local search is applied again, otherwise a feasibility search procedure is applied, and if it successful, the local search is applied on the newfound solution. Different diversification strategies and feasibility search rules are proposed. We present computational results on a wide set of instances up to 50 customers and 5 satellites and compare them with results from the literature, showing how the new methods outperform previous existent methods, both in efficiency and accuracy.