An artificial bee colony algorithm for the capacitated vehicle routing problem

This paper introduces an artificial bee colony heuristic for solving the capacitated vehicle routing problem. The artificial bee colony heuristic is a swarm-based heuristic, which mimics the foraging behavior of a honey bee swarm. An enhanced version of the artificial bee colony heuristic is also proposed to improve the solution quality of the original version. The performance of the enhanced heuristic is evaluated on two sets of standard benchmark instances, and compared with the original artificial bee colony heuristic. The computational results show that the enhanced heuristic outperforms the original one, and can produce good solutions when compared with the existing heuristics. These results seem to indicate that the enhanced heuristic is an alternative to solve the capacitated vehicle routing problem. © 2011 Elsevier B.V. All rights reserved.postprin

Creación de celdas cooperativas en un grupo de tiendas de una misma franquicia

En este trabajo se resuelve un problema de creación de celdas cooperativas en un grupo de tiendas que forman parte de una misma franquicia, que permitan evitar las posibles roturas de stocks derivadas de incrementos puntuales de la demanda. El problema de las celdas cooperativas se inscribe en el marco del Vehicle Routing Problem (VRP). Para la resolución del problema se aplicaron dos procedimientos basados en el estudio de las distancias entre los componentes de las celdas. El primero (GCSI) sigue dos fases: en primer lugar se genera una solución inicial intuitiva y posteriormente se aplica un procedimiento de mejora fundamentado en el Variable Neighborhood Search (VNS) con aportaciones propias del Multi-Start Local Search (MSLS). En el segundo (GCGRASP) se aplica un GRASP. Los dos procedimientos se experimentaron en un caso real que consta de 116 tiendas, todas pertenecientes a la misma cadena de franquicias y ubicadas en la zona sur de Inglaterra. Los resultados demuestran que el procedimiento GCGRASP puede alcanzar valores de la distancia media por celda inferiores a los que se obtienen aplicando el procedimiento GCSI. No obstante, los tiempos de cálculo en aplicar el procedimiento GCSI son muy inferiores a los tiempos obtenidos para el procedimiento GCGRASP.Postprint (published version

Creating very large scale neighborhoods out of smaller ones by compounding moves: A study on the vehicle routing problem

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Optimization models and methods for transportation services

Managing transportation services efficiently is essential to both public and private sectors. This dissertation addresses three scheduling problems in modern transportation systems: the network design problem, the train dispatching problem, and the service route design problem. The transportation network design problem with service requirements designs arcs on a directed network and route commodities on the designed arcs so that i) commodities satisfy service requirements and ii) the total cost is minimized. We develop three mathematical programming models: a compact but weak arc-flow formulation, a large but strong path-flow formulation, and a hybrid formulation that uses both the arc-flow and the path-flow representations. We show that the hybrid formulation can significantly strengthen the LP formulation without introducing many variables. To find a good hybrid formulation, we develop columnization and decolumnization algorithms that uses the LP relaxation information to identify commodities that should use the path-flow representation. We also develop valid inequalities for commodities using the path-flow representation. The train dispatching problem schedules the movements of trains on scarce railroad tracks so as to improve the average velocity of trains. We develop a mathematical programming model and strengthen the model using valid inequalities. Besides, we present a heuristic to find a feasible solution quickly, which can serve as the warm-start solution to the MIP solver. For the third problem, we seek to design vehicle routes to deliver and pickup orders for a major grocery chain. We design a GRASP that can incorporate various operational requirements, including warehouse loading capacity, loading sequence, time window requirements, truck volume and weight capacities, and driver time limits. Our GRASP procedure consists of two phases: the solution construction (Phase I) and the Tabu search (Phase II). We show that the neighborhood structure of solutions is highly degenerate, which limits the solution space explored by the Tabu search. We apply the Tabu search with random variable neighborhood to increase the solution space explored.Operations Research and Industrial Engineerin

OPTIMIZATION OF RAILWAY TRANSPORTATION HAZMATS AND REGULAR COMMODITIES

Transportation of dangerous goods has been receiving more attention in the realm of academic and scientific research during the last few decades as countries have been increasingly becoming industrialized throughout the world, thereby making Hazmats an integral part of our life style. However, the number of scholarly articles in this field is not as many as those of other areas in SCM. Considering the low-probability-and-high-consequence (LPHC) essence of transportation of Hazmats, on the one hand, and immense volume of shipments accounting for more than hundred tons in North America and Europe, on the other, we can safely state that the number of scholarly articles and dissertations have not been proportional to the significance of the subject of interest. On this ground, we conducted our research to contribute towards further developing the domain of Hazmats transportation, and sustainable supply chain management (SSCM), in general terms. Transportation of Hazmats, from logistical standpoint, may include all modes of transport via air, marine, road and rail, as well as intermodal transportation systems. Although road shipment is predominant in most of the literature, railway transportation of Hazmats has proven to be a potentially significant means of transporting dangerous goods with respect to both economies of scale and risk of transportation; these factors, have not just given rise to more thoroughly investigation of intermodal transportation of Hazmats using road and rail networks, but has encouraged the competition between rail and road companies which may indeed have some inherent advantages compared to the other medium due to their infrastructural and technological backgrounds. Truck shipment has ostensibly proven to be providing more flexibility; trains, per contra, provide more reliability in terms of transport risk for conveying Hazmats in bulks. In this thesis, in consonance with the aforementioned motivation, we provide an introduction into the hazardous commodities shipment through rail network in the first chapter of the thesis. Providing relevant statistics on the volume of Hazmat goods, number of accidents, rate of incidents, and rate of fatalities and injuries due to the incidents involving Hazmats, will shed light onto the significance of the topic under study. As well, we review the most pertinent articles while putting more emphasis on the state-of-the-art papers, in chapter two. Following the discussion in chapter 3 and looking at the problem from carrier company’s perspective, a mixed integer quadratically constraint problem (MIQCP) is developed which seeks for the minimization of transportation cost under a set of constraints including those associating with Hazmats. Due to the complexity of the problem, the risk function has been piecewise linearized using a set of auxiliary variables, thereby resulting in an MIP problem. Further, considering the interests of both carrier companies and regulatory agencies, which are minimization of cost and risk, respectively, a multiobjective MINLP model is developed, which has been reduced to an MILP through piecewise linearization of the risk term in the objective function. For both single-objective and multiobjective formulations, model variants with bifurcated and nonbifurcated flows have been presented. Then, in chapter 4, we carry out experiments considering two main cases where the first case presents smaller instances of the problem and the second case focuses on a larger instance of the problem. Eventually, in chapter five, we conclude the dissertation with a summary of the overall discussion as well as presenting some comments on avenues of future work

MATHEMATICAL PROGRAMMING ALGORITHMS FOR TRANSPORTATION PROBLEMS

The thesis deals with the study of transportation problems, and in particular focuses on developing new exact and heuristic algorithms for two interesting variants of the well known Vehicle Routing Problem: the multi-depot heterogeneous-fleet vehicle routing problem with time windows and the multi-depot heterogeneous-fleet pickup and delivery problem with soft time windows. The studied problems consider additional real-world requirements, often neglected in the literature. They lead to more involved problems but on the other hand more realistic ones, that call for powerful optimization methods in order to tackle such difficult applications. The proposed algorithms are based on mathematical programming techniques, such as branch-and-price, column generation and dynamic programming. The performance of the algorithms is analyzed with extensive computational experiments and compared with the most effective algorithms from the literature, showing the usefulness of the proposed methods