Possibilities of using Incoterms clauses in a country logistics performance assessment and benchmarking

In supply chain management, fast and accurate decisions in supplier selection and order quantity allocation have a strong influence on the company's profitability and the total cost of finished products. In this paper, a novel and non-linear model is proposed for solving the supplier selection and order quantity allocation problem. The model is introduced for minimizing the total cost per time unit, considering ordering, purchasing, inventory, and transportation cost with freight rate discounts. Perfect rate and capacity constraints are also considered in the model. Since metaheuristic algorithms have been successfully applied in supplier selection, and due to the non-linearity of the proposed model, particle swarm optimization (PSO), genetic algorithm (GA), and differential evolution (DE), are implemented as optimizing solvers instead of analytical methods. The model is tested by solving a reference model using PSO, GA, and DE. The performance is evaluated by comparing the solution to the problem against other solutions reported in the literature. Experimental results prove the effectiveness of the proposed model, and demonstrate that metaheuristic algorithms can find lower-cost solutions in less time than analytical methods.

Inventory replenishment decision model for the supplier selection problem using metaheuristic algorithms

Adoption of the Paris Agreement in December 2015 and its subsequent ratification through Nationally Determined Contribution (NDC) marked, among other things, India’s commitment to reduce the emissi...

A fuzzy multi-criteria approach for evaluating the contribution of freight transportation towards India’s Nationally Determined Contributions (NDCs)

As the demand for transport is growing, more and more attention is being paid to its quality aspects. These include, among other things, efficiency, safety, and a continuous effort to reduce external costs. That is why the transport policies of the EU countries and individual regions are increasingly addressing the issue of sustainable transport development. Multimodal transport, which is seen as a key element to effectively counterbalance the dominant role of vehicle transport in the economic progress of the European Community, plays an important role in these programmes. For consistency and continuity of freight flows, cooperation between neighbouring countries and regions is essential. The future of multimodal freight transport within the cross-border area of Poland, Czech Republic and Slovakia is not as evident as the transport policies imply. Therefore, the purpose of the paper is to identify a set of factors determining the development of multimodal transport within the cross-border area of TRITIA (The European Grouping of Territorial Cooperation of the four regional governments of Moravian-Silesian Region (CZ), Opole Voivodeship (PL), Silesian Voivodeship (PL) and Žilina Self-governing Region (SK)) and to develop four scenarios, the execution of which in the 2030 perspective depends on the implementation of cross-border infrastructure and organisational projects and the increasing level of cooperation in the field of multimodal transport. The article contains the methodology for developing scenarios of multimodal freight transport development. The research showed that initiating activities targeted at the development of multimodal transport within the cross-border area requires the involvement of all participants in the process, i.e., all countries (Poland, Czech Republic and Slovakia), along with many different stakeholders. The future development of multimodal transport as provided for in the scenarios is not linearly correlated with the increase in cooperation and the number of implemented infrastructure and organisational projects. It is vital for future research to define the role of stakeholders both in terms of cooperation and collaboration development.

Scenarios for the Development of Multimodal Transport in the TRITIA Cross-Border Area

Agent-based simulation (ABS) appears to be a suitable tool for research and application in the field of city logistics. In this paper, an attempt was made to classify the current literature on ABS in urban freight distribution following some homogeneity criteria. A set of six criteria was adopted and relevant papers were classified accordingly. It emerges that agent-based simulation models are suitable for use in simulating urban freight distribution, identifying a set of agents (at most, one agent per stakeholder) that operate to achieve their objectives, following rules, interacting, and learning from experience. However, this approach is still to be fully developed: the applications provided in the literature are only for test cases, refer to small study areas and a limited number of agents.

Agent-Based Simulation of urban goods distribution: a literature review

Single Wagonload (SWL) is still a major component in Swiss and European Logistic networks. Due to changing market requirements and a higher infrastructure load by passenger trains the SWL production schemes have to be optimised. The existing models do not cover both network levels, the production schemes and the physical infrastructure, which are required to optimise the SWL. So the IVT at ETH Zurich has developed an agent-based simulation for SWL based on MATSim. The first results of the simulation show, that this method is suitable for SWL simulation.

Optimization of SWL production schemes using an agent based simulation

Im Rahmen der nationalen Verkehrsmodellierung im UVEK (VM-UVEK) betreiben ARE, ASTRA und BAV neben dem Nationalen Personenverkehrsmodell (NPVM) auch ein disaggregiertes Modell zum Guterverkehr (NGVM). Methodische und technische Grunde schranken den Anwendungsbereich des NGVM ein, zudem fokussiert es auf den Binnenverkehr. Vor diesem Hintergrund wurde eine Evaluierung der nationalen Guterverkehrsmodellierung angestossen. Die Evaluierung wurde nach drei Schwerpunkten gegliedert: Analyse des Bedarfs an Fragestellungen zum Guterverkehr, Auslegeordnung zu Methoden und (vergleichbaren nationalen) Modellen inkl. des bestehenden Modells sowie Sichtung der Verfugbarkeit von (modellrelevanten) Daten zum Guterverkehr. Ziel war es, aus der Evaluierung Stossrichtungen und Strategien fur die weitere Entwicklung der Nationalen Guterverkehrsmodellierung abzuleiten. Die Bedarfsanalyse hat gezeigt, dass es einen breiten, kunftig gar steigenden Bedarf an strategisch modellierten Daten zum Guterverkehr gibt. Die damit verbundenen Fragestellungen lassen sich grob in solche mit eher aggregiertem Blickwinkel (nationale Ebene, zusammengefasste Marktsegmente) und solche mit stark disaggregiertem Blickwinkel (ortlich eingegrenzt, auf Teilsegmente fokussierend) unterscheiden. Die Betrachtung von Methoden und Modellen hat gezeigt, dass die Komplexitat der Wirkungszusammenhange im Guterverkehr die Moglichkeiten der Modellierung begrenzt – zumindest ist derzeit kein Modell in Sicht, welches gegenuber dem bestehenden, eher disaggregiert arbeitendem NGVM signifikante Vorteile aufweisen wurde. Es gibt aber Methoden, welche mit aggregierten Ansatzen vereinfachend einige der ubergeordneten Fragestellungen besser abzubilden vermogen als disaggregiert arbeitende Modelle. Die Datenlage lasst sich ahnlich zweiteilen: Fur eher ubergeordnete Blickwinkel und den dafur infrage kommenden Modellen liegen deutlich mehr Daten vor als fur disaggregierte Betrachtungsweisen, wobei Daten mit Prognosecharakter generell nur eingeschrankt verfugbar sind. Die Einstellung der nationalen Guterverkehrsmodellierung ware aus Sicht des Bedarfes kontraproduktiv; der Aufbau eines neuen disagregierten Modells bietet sich ebenfalls nicht an. Daher erscheint es empfehlenswert, im weiteren Umgang zu einer nationalen Guterverkehrsmodellierung eine Strategie zu verfolgen, die modular die aggregierten und disaggregierten Blickwinkel berucksichtigt und dabei das bestehende NGVM einbezieht. Etappenweise konnte mit dem Aufbau eines aggregiert arbeitenden Modells begonnen werden – abgestimmt auf spatere Querbeziehungen zum bestehenden Modell. Dieses ist dann fur disaggregierte Betrachtungen zu optimieren. Begleitet werden sollte die Nationale Guterverkehrsmodellierung von einem Betriebskonzept und einer angemessenen Kommunikation zu den Moglichkeiten und Grenzen der Daten, Methoden und Modelle.

Verkehrsmodellierung im UVEK: Evaluierung der nationalen Güterverkehrsmodellierung

Previous research at ETH Zurich (Moll 2012b) already found that freight railway undertakings could increase their efficiency by far, by integrating demand predictions into their regular planning process. The shippers, as main sources of the demand data, often do not have their own forecasts, which have been done in an appropriate way, or are not willing to provide their forecast data to the railway undertakings. So the freight railway undertakings have to find other sources to enhance their own demand forecasts. The railway undertakings have a lot of detailed data from former transports such as the “Wagenverlaufsdatei” (wagon run data), which contains a dataset for each transported wagon containing its origin, its destination, the demand date, the transported type of goods, the shipper, the route and the type of wagon used for the transport. One promising approach is to exploit time series methods and machine learning algorithms to forecast the demand using this existing data. The project presented here would therefore contribute a novel new field of application for existing machine learning and time series methods. In other fields of transport demand forecast, for example in passenger demand forecast and in traffic flow forecasts on highways in Switzerland (a previous project completed by ZHAW) these methodological approaches have already shown good results. So in this project, which has just been started, ETH Zurich, Institute for Transport Planning and Systems and ZHAW Wadenswil, Institute of Applied Simulation, are testing a broad range of machine learning and time series methods for forecasting freight demand to enhance the efficiency of rail freight undertakings. This evaluation will include the identification of driver variables for freight demand depending on the type of goods, which are transported. The methods will then be further developed to include these driver variables and then the effect that the application of these methods could have on the efficiency of railway undertakings will be investigated. So this research will fill a gap in current knowledge as until now, only a small number of methods have been tested on limited data. This project would contribute to this field of knowledge by providing a thorough review and evaluation of a broad range of possible methods which could be applied to freight demand forecasting. The wagon demand data for each day of one year (2012) has already been obtained from SBB Infrastructure. As a proof of concept, a simple neural network and a ARMA(5,5) model have been used to forecast the demand for the last 60 days, using the rest of the year’s data for training the methods. The results from these methods are presented here, but we expect to develop methods which are better suited to the problem and to obtain better results as the project, which is still in the very early stages, progresses. As we only have a few preliminary results so far, the main purpose of this paper is to present the project and the ideas behind it.

Improving the Forecast of Freight Transport Demand Using Machine Learning and Time Series Methods

The advanced internationalisation of markets and production processes continuously adds to the complexity of supply chains. At the same time improving the sustainability of the related international freight transport processes and optimising their efficiency is becoming a topic of central relevance. International freight transport models are an important tool to simulate impacts of measures taken to achieve such improvements of transport processes. Yet, the requirements towards international freight transport models are complex: they need to include various modes of transport, they need to cover different industries and their dynamics, they need to consider seasonality of supply and demand of goods, demographic parameters, economic developments, technological developments including their impact on production processes and structures, and many other aspects. Furthermore, international freight transport models need to include freight flows within countries as well as freight flows between the considered countries. This paper discusses the challenges which need to be confronted when developing international freight transport models which are able to correspond to the described complexity of international freight transport. Furthermore, it maps out the most important research gaps which need to be addressed by international freight transport modelling research in order to ensure that the challenges identified are captured within the models developed to improve international freight transport.

Challenges and future research needs towards international freight transport modelling

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Papers

Optimization of SWL production schemes using an agent based simulation

Verkehrsmodellierung im UVEK: Evaluierung der nationalen Güterverkehrsmodellierung

Improving the Forecast of Freight Transport Demand Using Machine Learning and Time Series Methods

Challenges and future research needs towards international freight transport modelling