Joint Route Planning under Varying Market Conditions

Purpose - To provide empirical evidence on the level of savings that can be attained by joint route planning and how these savings depend on specific market characteristics.Design/methodology/approach - Joint route planning is a measure that companies can take to decrease the costs of their distribution activities. Essentially, this can either be achieved through horizontal cooperation or through outsourcing distribution to a Logistics Service Provider.The synergy value is defined as the difference between distribution costs in the original situation where all entities perform their orders individually, and the costs of a system where all orders are collected and route schemes are set up simultaneously to exploit economies of scale.This paper provides estimates of synergy values, both in a constructed benchmark case and in a number of real-world cases.Findings - It turns out that synergy values of 30% are achievable.Furthermore, intuition is developed on how the synergy values depend on characteristics of the distribution problem under consideration.Practical implications - The developed intuition on the nature of synergy values can help practitioners to find suitable combinations of distribution systems, since synergy values can quickly be assessed based on the characteristics of the distribution problem, without solving large and difficult Vehicle Routing Problems.Originality/value - this paper addresses a major impediment to horizontal cooperation: estimating operational savings upfront.Horizontal cooperation;Distribution;Outsourcing;Vehicle routing with time windows;Retail

Freight distribution performance indicators for service quality planning in large transportation networks

This paper studies the use of performance indicators in routing problems to estimate how transportation cost is affected by the quality of service offered. The quality of service is assumed to be directly dependent on the size of the time windows. Smaller time windows mean better service. Three performance indicators are introduced. These indicators are calculated directly from the data without the need of a solution method. The introduced indicators are based mainly on a "request compatibility", which describes whether two visits can be scheduled consecutively in a route. Other two indicators are introduced, which get their values from a greedy constructive heuristic. After introducing the indicators, the correlation between indicators and transportation cost is examined. It is concluded that the indicators give a good first estimation on the transportation cost incurred when providing a certain quality of service. These indicators can be calculated easily in one of the first planning steps without the need of a sophisticated solution tool. The contribution of the paper is the introduction of a simple set of performance indicators that can be used to estimate the transportation cost of a routing problem with time window

Improving fleet solution – a case study

Transportation management is a logistical activity with a high impact on a company’s ability to compete in the market. Although the focus on cost reduction is the most usual concern with this activity, lead times and the quality of the service provided should also be considered depending on the market to be served. The goal of this research was to compare different fleet alternatives for a specific construction materials company and discuss which scenario is the most suited to fulfil the company’s customer service policy. A case study approach was developed, and four alternative scenarios were considered. These were compared both regarding the costs they involve, which was analysed using a vehicle routing problem heuristic, and the quality of the customer service they allow, which was assessed based on their ability to provide flexibility in the fleet occupancy rate to respond to unexpected orders. Evidence showed that the current fleet solution is not adequate and investment should be made only if the demand level increases, otherwise outsourcing should be considered along with a minimum level of the self-owned fleet.info:eu-repo/semantics/acceptedVersio

Spatial, Temporal, and Hybrid Decompositions for Large-Scale Vehicle Routing with Time Windows

This paper studies the use of decomposition techniques to quickly find high-quality solutions to large-scale vehicle routing problems with time windows. It considers an adaptive decomposition scheme which iteratively decouples a routing problem based on the current solution. Earlier work considered vehicle-based decompositions that partitions the vehicles across the subproblems. The subproblems can then be optimized independently and merged easily. This paper argues that vehicle-based decompositions, although very effective on various problem classes also have limitations. In particular, they do not accommodate temporal decompositions and may produce spatial decompositions that are not focused enough. This paper then proposes customer-based decompositions which generalize vehicle-based decouplings and allows for focused spatial and temporal decompositions. Experimental results on class R2 of the extended Solomon benchmarks demonstrates the benefits of the customer-based adaptive decomposition scheme and its spatial, temporal, and hybrid instantiations. In particular, they show that customer-based decompositions bring significant benefits over large neighborhood search in contrast to vehicle-based decompositions

Logistics for decision support - an application in cases of natural disasters

Considering that every disaster is unique and doing research during natural disasters is difficult, we show the possibility to learn from solutions of logistics research. One main problem of logistics planning in cases of natural disasters is relief good distribution. While this problem belongs to the class of vehicle routing problems (VRP) under uncertainty, the task of transshipping relief goods needs to be considered more intensively. Especially, assigning trucks to doors to load or discharge has a high impact on the performance of a transshipment facility. In our approach, known and specially developed scheduling heuristics are applied to logistic operations in disaster relief. Therefore, we transfer the given problem of relief goods handling to transshipment of less-than-truckload (LTL) items. Here, our main objective is to improve efficiency of handling relief goods in terminals under consideration of urgent shipments. Based on limited resources for cargo handling in disaster areas, various weights and sizes of relief goods, time-sensitive shipments like medicaments or food, improper truck arrival times and different departure times, we apply and evaluate several strategies to schedule trucks in the unloading process. We apply and compare strategies to schedule incoming trucks, buffer areas and handling equipment like forklift trucks based on real data. Therefore, we developed fast decision algorithms to react to uncertain and changing information. Additionally, six different scheduling heuristics were developed to solve the complex problem of planning the utilization of unloading gates, one buffer area belonging to each unloading zone and a fleet of forklift trucks. The algorithms allow the implementation into a real-time system