Kris Braekers

The vehicle routing problem

Taxonomic review of vehicle routing literature published between 2009 and mid 2015.An adapted version of an existing comprehensive taxonomy is presented.277 VRP articles are classified based on problem characteristics and assumptions.The classification table allows researchers to quickly find relevant literature.Recent trends in VRP literature are discussed. Over the past decades, the Vehicle Routing Problem (VRP) and its variants have grown ever more popular in the academic literature. Yet, the problem characteristics and assumptions vary widely and few literature reviews have made an effort to classify the existing articles accordingly. In this article, we present a taxonomic review of the VRP literature published between 2009 and June 2015. Based on an adapted version of an existing comprehensive taxonomy, we classify 277 articles and analyze the trends in the VRP literature. This classification is the first to categorize the articles to this level of detail.

Integrated planning of loaded and empty container movements

Efficiently planning drayage operations is an important task for transportation companies since these operations constitute a large part of the cost of an intermodal transport. In this paper, a full truckload vehicle routing problem for transporting loaded and empty containers in drayage operations is studied. For empty container transports, either the origin or the destination is not predefined. The problem is formulated as an asymmetric multiple vehicle Travelling Salesman Problem with Time Windows (am-TSPTW). Two solution approaches are proposed: a sequential and an integrated approach. For both approaches, a single- and a two-phase deterministic annealing algorithm are presented. Results show that the proposed algorithms are able to find good quality solutions in a small amount of computation time. The integrated approach clearly outperforms the sequential one and the results confirm the advantage of using a two-phase algorithm for vehicle routing problems with hierarchical objectives. Finally, it is shown that the proposed integrated solution method improves previous results on a similar problem.

Challenges in Managing Empty Container Movements at Multiple Planning Levels

Empty container management deals with repositioning empty containers at minimum costs while fulfilling empty container demands. Due to imbalances in trade, some areas have a surplus of empty containers, while others have a shortage. Therefore, empty containers need to be repositioned globally to make sure that sufficient empty containers are available everywhere. Besides, empty containers need to be repositioned regionally between shippers, consignees, inland depots, terminals and ports in order to fulfil demand. In this paper, the focus is on the empty container management problem at a regional level. The problem is described in detail and opportunities for reducing empty container movements are discussed. Decisions to be taken at each planning level (strategic, tactical and operational) are described, and for each planning level, a detailed overview of planning models proposed in the literature is presented. Planning models considering decisions at several planning levels are discussed as well. Finally, interesting opportunities for future research are identified.

A bi-objective home care scheduling problem: Analyzing the trade-off between costs and client inconvenience

Organizations providing home care services are inclined to optimize their activities in order to meet the constantly increasing demand for home care. In this context, home care providers are confronted with multiple, often conflicting, objectives such as minimizing their operating costs while maximizing the service level offered to their clients by taking into account their preferences. This paper is the first to shed some light on the trade-off relationship between these two objectives by modeling the home care routing and scheduling problem as a bi-objective problem. The proposed model accounts for qualifications, working regulations and overtime costs of the nurses, travel costs depending on the mode of transportation, hard time windows, and client preferences on visit times and nurses. A distinguishing characteristic of the problem is that the scheduling problem for a single route is a bi-objective problem in itself, thereby complicating the problem considerably. A metaheuristic algorithm, embedding a large neighborhood search heuristic in a multi-directional local search framework, is proposed to solve the problem. Computational experiments on a set of benchmark instances based on real-life data are presented. A comparison with exact solutions on small instances shows that the algorithm performs well. An analysis of the results reveals that service providers face a considerable trade-off between costs and client convenience. However, starting from a minimum cost solution, the average service level offered to the clients may already be improved drastically with limited additional costs.

Optimal shipping routes and vessel size for intermodal barge transport with empty container repositioning

Despite the growing role of barge transportation in the hinterland access of major seaports in Northwestern Europe, service network design for intermodal barge transportation has received little research attention. In this paper, a decision support model for service network design in intermodal barge transportation is presented. The model determines optimal shipping routes for roundtrip services between a major seaport and several hinterland ports located along a single waterway. Vessel capacity and service frequency decisions may be analyzed by the model. A case study on the hinterland network of the port of Antwerp in Belgium is discussed. The decision support model is applied from the perspective of barge operators as well as from the perspective of shipping lines that offer door-to-door transport services. In the latter case, empty container repositioning decisions are taken into account. Numerical experiments are presented to indicate how the model may be used in practice.

Capacitated vehicle routing problem with sequence-based pallet loading and axle weight constraints

In this paper, we introduce and study the capacitated vehicle routing problem with sequence-based pallet loading and axle weight constraints. To the best of our knowledge, it is the first time that axle weight restrictions are incorporated in a vehicle routing model. The aim of this paper is to demonstrate that incorporating axle weight restrictions in a vehicle routing model is possible and necessary for a feasible route planning. Axle weight limits impose a great challenge for transportation companies. Trucks with overloaded axles represent a significant threat for traffic safety and may cause serious damage to the road surface. Transporters face high fines when violating these limits. A mixed integer linear programming formulation for the capacitated vehicle routing problem with sequence-based pallet loading and axle weight constraints is provided. Results of the model are compared to the results of the model without axle weight restrictions. Computational experiments demonstrate that the model performs adequately and that the integration of axle weight constraints in vehicle routing models is required for a feasible route planning.

Multi-directional local search for a bi-objective dial-a-ride problem in patient transportation

Abstract This paper considers a generalization of a bi-objective dial-a-ride problem, incorporating real-life characteristics of patient transportation. It studies the impact of combination restrictions, preventing particular user combinations and limiting the set of drivers to which particular users can be assigned. The academic literature currently lacks insights into the effect of these restrictions on the cost structure of a service provider. A multi-directional local search algorithm is developed to solve this problem, taking into account the fundamental tradeoff between operational efficiency and service quality. Local search is integrated into a variable neighborhood descent framework that applies an intelligent candidate list principle to reduce computation time. Moreover, a new scheduling procedure is proposed, constructing time schedules that minimize total user ride time. It proves to be faster and more efficient than existing scheduling procedures. Overall, computational experiments on existing benchmark data extended with combination restrictions reveal a general pattern in the effect of the combination restrictions. Such insights are essential for service providers in order to support policy choices, e.g. related to service quality or medical education of drivers.

Typology and literature review for dial-a-ride problems

Dial-a-ride problems consist of designing vehicle routes and time schedules in a system of demand-dependent, collective people transportation. In the standard problem, operational costs are minimized, subject to full demand satisfaction and service level requirements. However, to enhance the practical applicability of solution methods, authors increasingly focus on problem variants that adopt additional real-life characteristics. First, this work introduces an up-to-date classification that distinguishes multiple categories of real-life characteristics. Second, the wide range of solution methods proposed in the literature is reviewed in a structured manner. Although the existing literature is reviewed exhaustively, specific attention is devoted to recent developments. Third, an extensive overview table provides full details on all problem characteristics and solution methods applied in each paper discussed. Fourth, lacunae in research conducted to date and opportunities for future work are identified.

Operational effects of service level variations for the dial-a-ride problem

The dial-a-ride problem consists of designing a number of minimum-cost vehicle routes in a system of demand-dependent, collective people transportation. Quality is ensured by taking into account service level requirements. However, little research has been conducted into the effect of service level variations on operational costs incurred by service providers. This study investigates the evolution of operational costs for 78 combinations of two service level parameters, being the maximum deviation from a user’s preference time and the relative maximum exceedance of a user’s direct ride time. A distinction is made between various operating circumstances, including the size of the service provider, the traffic conditions in the service area and the heterogeneity of the customers. The resulting tradeoffs between quality and costs should encourage service providers to make informed decisions regarding potential changes in the service level they offer. The sensitivity analysis in this paper is performed on well-known benchmark data from literature and applies a state-of-the-art deterministic annealing metaheuristic to compute operational costs.

An exact algorithm for the full truckload pick–up and delivery problem with time windows: concept and implementation details

Intermodal goods transport is characterised by a main transport by rail, barge or seaborne vessel, preceded and followed by short in time but expensive road transport. Many times trucks pick–up or deliver a single container which leads to a full truckload vehicle routing problem in terms of economically efficient transport services. Time windows induced by the customer or due to external situations increase the complexity of an efficient planning by a logistics provider. An exact algorithm for this type of pick–up and delivery problem is developed and the details of its implementation are explained. A set partitioning problem is automatically generated, which may be solved to optimality by an optimising software.