Katrien Ramaekers

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.

Collaborative Logistics from the Perspective of Road Transportation Companies

ABSTRACT To survive under the ever increasing competitive and global pressures to operate more efficiently, transportation companies are obliged to adopt a collaborative focus. Various types of cooperative supply chain relationships have been discussed in both professional and academic literature over the last decades. However, research on horizontal cooperation in logistics remains scarce and scattered across various research domains. Companies operating at the same level of the supply chain and performing comparable logistics functions may cooperate horizontally to increase their productivity, improve their service level and enhance their market position. In this paper, the focus is on the operational planning of horizontal cooperations between road transportation carriers. Following a scientific literature review, a distinction may be made between two operational approaches to horizontal logistics collaboration: order sharing and capacity sharing. For both research streams, a detailed overview of solution techniques proposed in literature is presented. Moreover, some interesting opportunities for future research are identified.

On the choice of a demand distribution for inventory management models

An inventory system containing uncertainty, e.g., in demand, in costs, in lead time, or in supplied quantity or quality, needs a probability distribution of demand for reorder point models. In the literature on inventory control, many times reference is made to the Normal or Gamma distribution for describing the demand in the lead time. The Poisson distribution has been found to provide a reasonable fit when the demand is very low. However, information about the functional form of the probability distribution is often incomplete in practice. For example, it might be that only the first moments of the probability distribution are known. This incomplete information is a problem as the shape of the distribution is important in terms of the performance of inventory control. A procedure is described to determine shape characteristics when only the first two moments of the distribution of demand during the lead time are known, using a compound Poisson distribution and the Pearson chart. [Received 18 August 2006; Revised 15 November 2007; Accepted 11 February 2008]

Integrating production scheduling and vehicle routing decisions at the operational decision level

A review of integrated production schedulingvehicle routing problems is provided.A production-distribution classification matrix is presented.Simple production and distribution environments are mostly considered.Integrated studies with more real-life characteristics are necessary.Fast and robust solution approaches for integrated studies need to developed. Production scheduling and vehicle routing are two well-studied problems in literature. Although these supply chain functions are interrelated, they are often solved sequentially. This uncoordinated approach can lead to suboptimal solutions. In the current competitive business environment, companies are searching for methods to save costs and improve their service level. Integrating production and distribution scheduling operations can be an approach to improve the overall performance. This paper focuses on integrated production-distribution operational level scheduling problems, which explicitly take into account vehicle routing decisions of the delivery process. Existing literature on integrated production scheduling and vehicle routing problems is reviewed and classified. Both the problem characteristics of mathematical models and the accompanying solution approaches are discussed to identify directions for further research.

Analysis of collaborative savings and cost allocation techniques for the cooperative carrier facility location problem

Transport companies may cooperate to increase their efficiency levels by, for example, the exchange of orders or vehicle capacity. In this paper a new approach to horizontal carrier collaboration is presented: the sharing of distribution centres (DCs) with partnering organisations. This problem can be classified as a cooperative facility location problem and formulated as an innovative mixed integer linear programme. To ensure cooperation sustainability, collaborative costs need to be allocated fairly to the different participants. To analyse the benefits of cooperative facility location and the effects of different cost allocation techniques, numerical experiments based on experimental design are carried out on a UK case study. Sharing DCs may lead to significant cost savings up to 21.6%. In contrast to the case of sharing orders or vehicles, there are diseconomies of scale in terms of the number of partners and more collaborative benefit can be expected when partners are unequal in size. Moreover, results indicate that horizontal collaboration at the level of DCs works well with a limited number of partners and can be based on intuitively appealing cost sharing techniques, which may reduce alliance complexity and enforce the strength of mutual partner relationships.

Time Petri nets as an evaluation tool for handling travel time uncertainty in vehicle routing solutions

Congestion on roads leads to uncertainty in travel times, which is important in delivery of goods, especially in a business environment where high levels of customer service are expected. Delivery periods to customers might be constrained by time windows, which makes the scheduling and routing of vehicles from the suppliers side more difficult. Operations Research methods turn into heuristics for this type of application. But when, on top, uncertainty on travel times are the case, any hope of a simple and well-performing heuristic is lost. This study applies a methodology in which a heuristic is used to find a solution for scheduling and routing under deterministic travel times and, by means of simulation, though the use of Time Petri nets evaluates the sensitivity of the solution to uncertainties in travel times from one customer to the next in a route.

A linear programming formulation for an inventory management decision problem with a service constraint

Inventory systems with uncertainty go hand in hand with the determination of a safety stock level. The decision on the safety stock level is based on a performance measure, for example the expected shortage per replenishment period or the probability of a stock-out per replenishment period. The performance measure assumes complete knowledge of the probability distribution during lead time, which might not be available. In case of incomplete information regarding the lead-time distribution of demand, no single figure for the safety stock can de determined in order to satisfy a performance measure. However, an optimisation model may be formulated in order to determine a safety stock level which guarantees the performance measure under the worst case of lead-time demand, of which the distribution is known in an incomplete way. It is shown that this optimisation problem can be formulated as a linear programming problem.

Designing efficient order picking systems by combining planning problems: State-of-the-art classification and review

Warehouses deliver labor-intensive services to customers. Underperformance may result in high costs and unsatisfied customer demand. New market developments force warehouses to handle a large number of orders within tight time windows. To cope with this, order picking operations need to be optimized by solving a wide range of planning problems. Optimizing order picking planning problems sequentially may yield a suboptimal overall warehouse performance. Still, previous warehouse planning reviews focus on individual planning problems. This literature review differs by investigating combinations of multiple order picking planning problems. A state-of-the-art review and classification of the scientific literature investigating combinations of tactical and operational order picking planning problems in picker-to-parts systems is presented with the aim of determining how planning problems are related. Furthermore, this literature review aims to find excellent policy combinations and to provide guidelines how warehouse managers can benefit from combining planning problems, in order to design efficient order picking systems and improve customer service. Combining multiple order picking planning problems results in substantial efficiency benefits, which are required to face new market developments.

The use of time series forecasting in zone order picking systems to predict order pickers’ workload

In order to differentiate from competitors in terms of customer service, warehouses accept late orders while providing delivery in a quick and timely way. This trend leads to a reduced time to pick an order. This paper introduces workload forecasting in a warehouse context, in particular a zone picking warehouse. Improved workforce planning can contribute to an effective and efficient order picking process. Most order picking publications treat demand as known in advance. As warehouses accept late orders, the assumption of a constant given demand is questioned in this paper. The objective of this study is to present time series forecasting models that perform well in a zone picking warehouse. A real-life case study demonstrates the value of applying time series forecasting models to forecast the daily number of order lines. The forecast of order lines, along with order pickers’ productivity, can be used by warehouse supervisors to determine the daily required number of order pickers, as well as the allocation of order pickers across warehouse zones. Time series are applied on an aggregated level, as well as on a disaggregated zone level. Both bottom-up and top-down approaches are evaluated in order to find the best-performing forecasting method.

On the use of bounds on the stop-loss premium for an inventory management decision problem

Abstract A specific integral, which is used in insurance mathematics for the determination of a stop-loss premium, corresponds to the definition of a performance characteristic of an inventory management decision problem. It is investigated whether the operational management problem might benefit from specific results obtained in the actuarial world. In the case little information is available on the demand distribution during the lead-time, which is relevant in inventory decision-making, interesting results might be used from the actuarial problem where limited information (e.g., only a few moments of the claim size distribution) is known. With a limited transformation of the actuarial results, upper and lower bounds may be determined for the safety stock in the inventory management problem. Also a numerical approximation using linear programming is shown to be equivalent to the problem under study.