Multi-start heuristics for the Two-Echelon Vehicle Routing Problem

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 accurac

A solution method for a two-layer sustainable supply chain distribution model

This article presents an effective solution method for a two-layer, NP-hard sustainable supply chain distribution model. A DoE-guided MOGA-II optimiser based solution method is proposed for locating a set of non-dominated solutions distributed along the Pareto frontier. The solution method allows decision-makers to prioritise the realistic solutions, while focusing on alternate transportation scenarios. The solution method has been implemented for the case of an Irish dairy processing industry׳s two-layer supply chain network. The DoE generates 6100 real feasible solutions after 100 generations of the MOGA-II optimiser which are then refined using statistical experimentation. As the decision-maker is presented with a choice of several distribution routes on the demand side of the two-layer network, TOPSIS is applied to rank the set of non-dominated solutions thus facilitating the selection of the best sustainable distribution route. The solution method characterises the Pareto solutions from disparate scenarios through numerical and statistical experimentations. A set of realistic routes from plants to consumers is derived and mapped which minimises total CO2 emissions and costs where it can be seen that the solution method outperforms existing solution methods

Heuristics for the two-echelon vehicle routing problem: A multi-start approach

Tech. Rep. CIRRELT-2011-16, CIRRELT, Montreal, Canad

Un algoritmo metaheurístico basado en recocido simulado con espacio de búsqueda granular para el problema de localización y ruteo con restricciones de capacidad.

Consideramos el problema de localización y ruteo con restricciones de capacidad (CLRP), en el cual la meta es determinar los depósitos a ser abiertos, los clientes a ser asignados a cada depósito abierto, y las rutas a ser construidas para satisfacer las demandas de los clientes. El objetivo es minimizar la suma de los costos de abrir depósitos, de los costos de los vehículos usados, y de los costos variables asociados con la distancia recorrida por las rutas. En este paper, proponemos una metaheurística basada en simulado y recocido con espacio de búsqueda granular para resolver el problema CLRP. Experimentos computacionales en instancias de benchmarking tomadas de la literatura muestran que el algoritmo propuesto es capaz de obtener, dentro de tiempos computacionales razonables, soluciones de alta calidad mostrando su eficacia

Métaheuristiques de recherche avec tabous pour le problème de synthèse de réseau multiproduits avec capacités

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal

A new distance measure based on the exchange operator for the HFF-AVRP

The Heterogeneous Fixed Fleet Asymmetric Vehicle Routing Prob- lem (HFF-AVRP) is a N P-hard optimization problem. Instances analysis and in particular, fitness landscape analysis, may help problem solving. Such anal- ysis require the definition of a distance between feasible solutions. Such a dis- tance does not exist for the HFF-AVRP and this report aims at proposing a new distance measure defined from the exchange operator. In order to compute the exchange-distance between two solutions, four algorithms are suggested and then experimented. One of them is proved to be robust and to give the exact distance whereas others only compute an upper bound

Sequential and parallel large neighborhood search algorithms for the periodic location routing problem

We propose a large neighborhood search (LNS) algorithm to solve the periodic location routing problem (PLRP). The PLRP combines location and routing decisions over a planning horizon in which customers require visits according to a given frequency and the specific visit days can be chosen. We use parallelization strategies that can exploit the availability of multiple processors. The computational results show that the algorithms obtain better results than previous solution methods on a set of standard benchmark instances from the literature

A Branch-Cut-and-Price Algorithm for the Location-Routing Problem

International audienc

Un algoritmo metaheurístico basado en recocido simulado con espacio de búsqueda granular para el problema de localización y ruteo con restricciones de capacidad.

Consideramos el problema de localización y ruteo con restricciones de capacidad (CLRP), en el cual la meta es determinar los depósitos a ser abiertos, los clientes a ser asignados a cada depósito abierto, y las rutas a ser construidas para satisfacer las demandas de los clientes. El objetivo es minimizar la suma de los costos de abrir depósitos, de los costos de los vehículos usados, y de los costos variables asociados con la distancia recorrida por las rutas. En este paper, proponemos una metaheurística basada en simulado y recocido con espacio de búsqueda granular para resolver el problema CLRP. Experimentos computacionales en instancias de benchmarking tomadas de la literatura muestran que el algoritmo propuesto es capaz de obtener, dentro de tiempos computacionales razonables, soluciones de alta calidad mostrando su eficacia

The Two-Echelon Multi-products Location-Routing problem with Pickup and Delivery: Formulation and heuristic approaches

The two-echelon location routing problem (LRP-2E) considers the first-level routes that serve from one depot a set of processing centers, which must be located and the second-level routes that serve customers from the open processing centers. In this paper, we consider an extension of the LRP-2E, where the second level routes include three constraints, that have not been considered simultaneously in the location routing literature, namely, multi-product, pickup and delivery and the use of the processing center as intermediate facility in the second-level routes. This new variant is named two-Echelon Multi-products Location-Routing problem with Pickup and Delivery (LRP-MPPD-2E). The objective of LRP-MPPD-2E is to minimize both the location and the routing costs, considering the new constraints. The first echelon deals with the selection of processing centers from a set of potential sites simultaneously with the construction of the first-level routes, such that each route starting from the main depot, visits the selected processing centers and returns to the main depot. The second echelon aims at assigning customers to the selected processing centers and defining the second-level routes. Each second-level route, starts at a processing center, visits a set of customers, through one or several processing centers, and then returns to the first processing center. We present a mixed integer linear model for the problem and use a Cplex solver to solve small-scale instances. Furthermore, we propose non-trivial extensions of nearest neighbour and insertion approaches. We also develop clustering based approaches that seldom investigated on location routing. Computational experiments are conducted to evaluate and to compare the performances of proposed approaches. The results confirm the effectiveness of clustering approaches.