Logistics Decisions in Descriptive Freight Transportation Models: A Review

The objective of this paper is to provide an inventory of approaches to descriptively (as opposed to normatively) model logistics decisions within the context of freight transport modelling. Rather than taking transport modelling frameworks as a starting point, as has been the case in the literature so far, we depart from a framework of logistics decisions. The framework is developed by combining elements of over a dozen existing frameworks from the supply chain management literature. Based on this comprehensive framework, we review freight modelling approaches from the literature. We find that freight modelling can be extended by taking into account previously uncovered areas of logistics decisions, such as those related to marketing or logistics systems forecasting and planning, as well as in areas that are well known from an optimization perspective but not from a descriptive perspective, such as routing and scheduling decisions. We conclude with a systematic listing of such areas, which can be used by researchers and transport modelling practitioners to develop further those transport models that take agent decision making as a starting point

Towards a Multi-Agent Logistics and Commercial Transport Model: The Transport Service Provider's View

AbstractIt is widely recognized that micro-simulation and agent-based approaches can successfully be applied in transport policy analysis. However, logistic decisions and the complex relationships among freight actors make this a challenging task and a reason why the development of freight models is still behind the development of passenger models. In this paper, we present a multi-agent freight transport model in which logistics decisions are separated into two different roles: Transport service providers, which create transport chains, and carriers, which plan tours and schedule vehicles. Both agent types can consolidate on their respective level and realise economies of scale. The lowest tier of the model, which contains individual freight vehicles, is integrated into the MATSim traffic simulation to create an integrated model for freight and passenger traffic. Changes in passenger demand, disturbances in the traffic system or policy measures can be picked up by freight drivers and propagated upwards to influence decisions on the levels of vehicle scheduling and transport chain building. As proof of concept, we set up a scenario with a fictitious freight operator serving a set of customers. We demonstrate that freight traffic can be simulated under different traffic conditions and policy measures

A multi-agent platform for auction-based allocation of loads in transportation logistics

This paper describes an agent-based platform for the allocation of loads in distributed transportation logistics, developed as a collaboration between CWI, Dutch National Center for Mathematics and Computer Science, Amsterdam and Vos Logistics Organizing, Nijmegen, The Netherlands. The platform follows a real business scenario proposed by Vos, and it involves a set of agents bidding for transportation loads to be distributed from a central depot in the Netherlands to different locations across Germany. The platform supports both human agents (i.e. transportation planners), who can bid through specialized planning and bidding interfaces, as well as automated, software agents. We exemplify how the proposed platform can be used to test both the bidding behaviour of human logistics planners, as well as the performance of automated auction bidding strategies, developed for such settings. The paper first introduces the business problem setting and then describes the architecture and main characteristics of our auction platform. We conclude with a preliminary discussion of our experience from a human bidding experiment, involving Vos planners competing for orders both against each other and against some (simple) automated strategies

A framework for smart production-logistics systems based on CPS and industrial IoT

Industrial Internet of Things (IIoT) has received increasing attention from both academia and industry. However, several challenges including excessively long waiting time and a serious waste of energy still exist in the IIoT-based integration between production and logistics in job shops. To address these challenges, a framework depicting the mechanism and methodology of smart production-logistics systems is proposed to implement intelligent modeling of key manufacturing resources and investigate self-organizing configuration mechanisms. A data-driven model based on analytical target cascading is developed to implement the self-organizing configuration. A case study based on a Chinese engine manufacturer is presented to validate the feasibility and evaluate the performance of the proposed framework and the developed method. The results show that the manufacturing time and the energy consumption are reduced and the computing time is reasonable. This paper potentially enables manufacturers to deploy IIoT-based applications and improve the efficiency of production-logistics systems

A new model for solution of complex distributed constrained problems

In this paper we describe an original computational model for solving different types of Distributed Constraint Satisfaction Problems (DCSP). The proposed model is called Controller-Agents for Constraints Solving (CACS). This model is intended to be used which is an emerged field from the integration between two paradigms of different nature: Multi-Agent Systems (MAS) and the Constraint Satisfaction Problem paradigm (CSP) where all constraints are treated in central manner as a black-box. This model allows grouping constraints to form a subset that will be treated together as a local problem inside the controller. Using this model allows also handling non-binary constraints easily and directly so that no translating of constraints into binary ones is needed. This paper presents the implementation outlines of a prototype of DCSP solver, its usage methodology and overview of the CACS application for timetabling problems

Comparison of agent-based scheduling to look-ahead heuristics for real-time transportation problems

We consider the real-time scheduling of full truckload transportation orders with time windows that arrive during schedule execution. Because a fast scheduling method is required, look-ahead heuristics are traditionally used to solve these kinds of problems. As an alternative, we introduce an agent-based approach where intelligent vehicle agents schedule their own routes. They interact with job agents, who strive for minimum transportation costs, using a Vickrey auction for each incoming order. This approach offers several advantages: it is fast, requires relatively little information and facilitates easy schedule adjustments in reaction to information updates. We compare the agent-based approach to more traditional hierarchical heuristics in an extensive simulation experiment. We find that a properly designed multiagent approach performs as good as or even better than traditional methods. Particularly, the multi-agent approach yields less empty miles and a more stable service level

Multi Agent Systems in Logistics: A Literature and State-of-the-art Review

Based on a literature survey, we aim to answer our main question: “How should we plan and execute logistics in supply chains that aim to meet today’s requirements, and how can we support such planning and execution using IT?†Today’s requirements in supply chains include inter-organizational collaboration and more responsive and tailored supply to meet specific demand. Enterprise systems fall short in meeting these requirements The focus of planning and execution systems should move towards an inter-enterprise and event-driven mode. Inter-organizational systems may support planning going from supporting information exchange and henceforth enable synchronized planning within the organizations towards the capability to do network planning based on available information throughout the network. We provide a framework for planning systems, constituting a rich landscape of possible configurations, where the centralized and fully decentralized approaches are two extremes. We define and discuss agent based systems and in particular multi agent systems (MAS). We emphasize the issue of the role of MAS coordination architectures, and then explain that transportation is, next to production, an important domain in which MAS can and actually are applied. However, implementation is not widespread and some implementation issues are explored. In this manner, we conclude that planning problems in transportation have characteristics that comply with the specific capabilities of agent systems. In particular, these systems are capable to deal with inter-organizational and event-driven planning settings, hence meeting today’s requirements in supply chain planning and execution.supply chain;MAS;multi agent systems

Agent-based transportation planning compared with scheduling heuristics

Here we consider the problem of dynamically assigning vehicles to transportation orders that have di¤erent time windows and should be handled in real time. We introduce a new agent-based system for the planning and scheduling of these transportation networks. Intelligent vehicle agents schedule their own routes. They interact with job agents, who strive for minimum transportation costs, using a Vickrey auction for each incoming order. We use simulation to compare the on-time delivery percentage and the vehicle utilization of an agent-based planning system to a traditional system based on OR heuristics (look-ahead rules, serial scheduling). Numerical experiments show that a properly designed multi-agent system may perform as good as or even better than traditional methods

Evaluating urban freight transport policies within complex urban environments

Urban Freight Transport (UFT) entails significant advantages for the economic growth of cities, but can also hamper population quality of life, obstructing vehicles and people movements while exacerbating environmental problems. Many initiatives have been engaged by many city administrators in order to efficiently manage UFT, evaluating different policies at a global scale. From the perspective of operators, most works analyze a limited set of policies or only focus on the benefits of companies. In this work, a decisionmaking process is used to evaluate a large set of UFT policies, through different attributes representing the advantages and limitations of each policy over promoter companies and the society. To do so, an ex-ante procedure in five steps is proposed to classify the policies: (1) attributes definition, (2) attributes weighting, (3) policy-attribute assessment, (4) policy ranking, and (5) feasibility threshold satisfaction. The whole process is supported on consultations to 26 experts regarding shop supply and restocking activities within complex urban environments. Results show a classification of the analyzed policies, according to their suitability for implementation ; which could be extended (directly or with small adjustments) to other contexts, given the flexibility of the decision-making procedure developed.Peer ReviewedPostprint (author's final draft