Henning Rekersbrink

A distributed routing concept for vehicle routing problems

Traditional solution concepts for the vehicle routing problem (VRP) are pushed to their limits, when applied on dynamically changing vehicle routing scenarios—which are more close to reality than the static formulation. By contrast, the introduced distributed routing concept is designed to match packages and vehicles and to continuously make route decisions especially within a dynamic environment. In this autonomous control concept, each of these objects makes its own decisions. The developed algorithm was entitled Distributed Logistics Routing Protocol (DLRP). But in spite of the restricted suitability of the traditional VRP concepts for dynamic environments, they are still the benchmark for any VRP-similar task. Therefore, we first present a description of the developed DLRP. Then an adapted vehicle routing problem is defined, which both sides, static and dynamic concepts, can cope with. Finally, both concepts are compared using a tabu search algorithm as a well working instance of traditional VRP-concepts. For a quantitative comparison, four solutions are given for the same adapted problem: the optimal solution as a lower bound, the DLRP solution, a tabu search solution and a random-like solution as an upper bound.

Dynamik logistischer Systeme

Produktionsunternehmen mussen heute in einem hochdynamischen Unternehmensumfeld agieren. Die fur Wettbewerbsfahigkeit und Markterfolg notwendige Flexibilitat und Anpassungsfahigkeit hat jedoch eine zunehmende strukturelle und dynamische Komplexitat des Produktionssystems selbst zur Folge (Scholz-Reiter et al. 2002). Das fuhrt unter Umstanden zu unvorhersehbarem Systemverhalten, das entgegen den ursprunglichen Zielsetzungen zu Leistungsminderungen fuhren kann (Larsen et al. 1999). Ursache dafur ist die Diskrepanz zwischen den der Produktionsplanung und -steuerung (PPS) zugrunde liegenden Modellen und der produktionslogistischen Realitat.

Autonomous Control by Means of Distributed Routing

In current logistic practices, routing and assignment of transport orders to vehicles are done centrally by a dispatching system and/or a human dispatcher. Here, the dispatching problem is generally of static nature and is solved either by the use of heuristics, e.g. evolutionary algorithms or Tabu search, or by applying “rules” that are gained from experience, when done by a human dispatcher.

An Autonomous Control Concept for Production Logistics

The German Collaborative Research Centre 637 ‘Autonomous Cooperating Logistic Processes’ tries to make a paradigm shift from central planning to autonomous control in the field of logistics. Among other things, autonomous routing algorithms based on internet routing protocols are developed. The Distributed Logistics Routing Protocol (DLRP) was originally designed for transport networks to match goods and vehicles and to continuously make route decisions. Now the protocol was transferred to production logistics as a promising autonomous control method. The DLRP enables the abilities for logistic objects, orders and machines, to make own decisions with the information actually and locally available. In contrast to common scheduling algorithms, the DLRP is not a planning, but a control method with the capability for multiple, user defined optimization goals. The new autonomous control concept for production logistics will be presented in this paper and a first evaluation with common scheduling heuristics will be given.

Scalability investigations on communication traffic in distributed routing of autonomous logistic objects

In current transport logistics, routing is usually done centrally. A dedicated routing instance solves the optimisation problem of finding the best solution to handle the current set of orders with the set of available vehicles under constraints such as vehicle utilisation, punctuality etc. Because of the increasing complexity of logistic processes, approaches have been suggested recently which change this centralised routing paradigm towards a distributed approach with autonomous logistic entities (vehicles and goods) deciding on their own. To be able to obtain enough knowledge for reasonable decisions, the logistic entities have to communicate with each other. For this interaction, the information exchange concept DLRP (Distributed Logistic Routing Protocol) has been proposed before. The work presented in this paper will focus on the aspect of scalability of communication in a DLRP scenario. Message flooding is identified as potential challenge for the scalability of DLRP, and intelligent flooding restrictions to the communication traffic are applied.

A SURVEY OF AUTONOMOUS CONTROL ALGORITHMS BY MEANS OF ADAPTED VEHICLE ROUTING PROBLEMS

The German Collaborative Research Centre 637 “Autonomous Cooperating Logistic Processes – A Paradigm Shift and its Limitations”, develops, among other things, autonomous routing algorithms for transport networks. The discussed algorithm is designed to match goods and vehicles and to continuously make route decisions within a dynamic transport network. Here, each object makes its own decisions. It is called Distributed Logistics Routing Protocol – DLRP. Because of obvious similarities to the Vehicle Routing Problem (VRP), one question arises for both practitioners and researchers: How efficient is this protocol compared to traditional, established algorithms or in comparison to the optimal solution? This article tries to answer this question, which appears simple on the first and challenging on the second view.Copyright

Dynamic Transport Reference Scenarios

Reference scenarios are a common technique in simulations allowing the evaluation and comparison of different algorithms and approaches. For transport logistic processes these approaches can be for example different strategies to select the packets to be loaded.

Weighted Multiplicative Decision Function for Distributed Routing in Transport Logistics

In transport logistics, routing is usually done by a central instance that is solving the optimization problem of finding the best solution to cover the current set of orders with the current set of vehicles under constraints such as punctuality, vehicle utilization etc. Approaches have been suggested recently which change this paradigm towards a distributed approach with autonomous entities deciding on their own. Autonomous entities denote, in this case, the vehicles as well as the goods. When each of the entities makes its own route decisions, it has to consider multiple parameters, which are partially static (e.g. distances) and partially dynamic. An example for a dynamic parameter is the knowledge about vehicle availability that goods need for their decisions. The work presented here is based on the information exchange concept DLRP (Distributed Logistic Routing Protocol), which has been proposed before. Within that framework, the concept of weighted multiplicative combination of context values into a decision function is now introduced for the route decisions made by autonomous entities.

Potentials and Limitations of Autonomously Controlled Production Systems

The application of autonomous control to production logistic systems has already shown promising results. Especially, in highly dynamic situations autonomous control outperforms conventional production planning and control methods. However, the implementation of autonomous control to production systems seems to be unsuitable to some situations. It appears that classical planning methods perform best in well-defined situations with less dynamics. This contribution addresses the potentials and the limitations of autonomous control compared to centralized planning and controll algorithms. Therefore, scenarios of the flexible flow shop problem with varying degrees of complexity and dynamics are used for evaluating autonomous control methods. The results are compared to classical scheduling algorithms for the flexible flow shop scheduling, in order to identify limitations and potentials of autonomous control.

Vehicle and Commodity Flow Synchronization

Network freight ow consolidation organizes the commodity ow with special attention to the minimization of the ow costs but the efficiency of transport resources is not addressed. In contrast, vehicle routing targets primarily the maximization of the efficiency of transport resources but the commodity-related preferences are treated as inferior requirements. This article is about the problem of synchronizing simultaneously the use of vehicles and the ow of commodities in a given transport network. Section 2 introduces the investigated scenario. Section 3 proposes a multi-commodity network ow model for the representation of the ow synchronization problem and Section 4 presents results from numerical experiments. Related and Previous Work. The synchronization of ows along independently determined paths in a network is investigated under the term multi-commodity network ow problem [3]. While most of the contributions aim at minimizing the sum of travel length (or similar objectives) only little work has been published on the assignment of commodity path parts to transport resources with intermediate resource change [1, 2].