scholarly journals An integrated agent-based model of travel demand and package deliveries

2021 ◽  
Vol 3 (2) ◽  
Author(s):  
Anna Reiffer ◽  
Jelle Kübler ◽  
Lars Briem ◽  
Martin Kagerbauer ◽  
Peter Vortisch
Keyword(s):  
Travel Demand ◽  
Integrated Modelling ◽  
Success Rates ◽  
Delivery Methods ◽  
Model Framework ◽  
Agent Based ◽  
Last Mile ◽  
Great Pressure ◽  
Surrounding Areas ◽  
Modelling Approach

With the increased shift from in-store shopping to e-commerce, we can expect the share of delivery vehicles in cities to rise as well. This puts great pressure on cities and surrounding areas as emissions rise and space becomes scarce. Because the last leg of the delivery chain is so costly, there have been many studies on how the last-mile issue can be diminished. However, most studies only cover deliveries independently from the orders. This paper presents a modelling approach that integrates travel demand, package orders and subsequent deliveries within the same framework. One of the benefits of the integrated modelling approach is that the model can evaluate the agents’ locations at all times during the simulation. This allows us to model different states of delivery on a microscopic level. We have applied the model to Karlsruhe, Germany with a synthetic population of just over 300.000 agents. The results show that the model simulates both package orders and the subsequent delivery tours realistically. The model framework allows for detailed analysis of delivery states and success rates and can be used for scenario analysis of different delivery methods and changes in online shopping behaviour.

scholarly journals Hierarchical Agent-Based Integrated Modelling Approach for Microgrids with Adoption of EVs and HRES

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Peng Han ◽  
Jinkuan Wang ◽  
Yan Li ◽  
Yinghua Han
Keyword(s):  
Electricity Consumption ◽  
Integrated Modelling ◽  
Agent Based ◽  
Complex Interactions ◽  
Hybrid Renewable Energy Systems ◽  
Proposed Model ◽  
Hybrid Renewable Energy ◽  
The Impact ◽  
Modelling Approach ◽  
Modelling Approaches

The large adoption of electric vehicles (EVs), hybrid renewable energy systems (HRESs), and the increasing of the loads shall bring significant challenges to the microgrid. The methodology to model microgrid with high EVs and HRESs penetrations is the key to EVs adoption assessment and optimized HRESs deployment. However, considering the complex interactions of the microgrid containing massive EVs and HRESs, any previous single modelling approaches are insufficient. Therefore in this paper, the methodology named Hierarchical Agent-based Integrated Modelling Approach (HAIMA) is proposed. With the effective integration of the agent-based modelling with other advanced modelling approaches, the proposed approach theoretically contributes to a new microgrid model hierarchically constituted by microgrid management layer, component layer, and event layer. Then the HAIMA further links the key parameters and interconnects them to achieve the interactions of the whole model. Furthermore, HAIMA practically contributes to a comprehensive microgrid operation system, through which the assessment of the proposed model and the impact of the EVs adoption are achieved. Simulations show that the proposed HAIMA methodology will be beneficial for the microgrid study and EV’s operation assessment and shall be further utilized for the energy management, electricity consumption prediction, the EV scheduling control, and HRES deployment optimization.

scholarly journals Integrating Urban Last-Mile Package Deliveries into an Agent-Based Travel Demand Model

2021 ◽  
Vol 184 ◽  
pp. 178-185
Author(s):  
Anna Reiffer ◽  
Jelle Kübler ◽  
Lars Briem ◽  
Martin Kagerbauer ◽  
Peter Vortisch
Keyword(s):  
Travel Demand ◽  
Demand Model ◽  
Agent Based ◽  
Last Mile ◽  
Travel Demand Model

scholarly journals An Agent-Based Crop Model Framework for Heterogeneous Soils

Agronomy ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 85
Author(s):  
Jorge Lopez-Jimenez ◽  
Nicanor Quijano ◽  
Alain Vande Wouwer
Keyword(s):  
Growth Models ◽  
Control Strategies ◽  
Low Cost ◽  
Soil Heterogeneity ◽  
Crop Growth ◽  
Negative Effects ◽  
Model Framework ◽  
Agent Based ◽  
Crop Growth Models ◽  
Definition Of

Climate change and the efficient use of freshwater for irrigation pose a challenge for sustainable agriculture. Traditionally, the prediction of agricultural production is carried out through crop-growth models and historical records of the climatic variables. However, one of the main flaws of these models is that they do not consider the variability of the soil throughout the cultivation area. In addition, with the availability of new information sources (i.e., aerial or satellite images) and low-cost meteorological stations, it is convenient that the models incorporate prediction capabilities to enhance the representation of production scenarios. In this work, an agent-based model (ABM) that considers the soil heterogeneity and water exchanges is proposed. Soil heterogeneity is associated to the combination of individual behaviours of uniform portions of land (agents), while water fluxes are related to the topography. Each agent is characterized by an individual dynamic model, which describes the local crop growth. Moreover, this model considers positive and negative effects of water level, i.e., drought and waterlogging, on the biomass production. The development of the global ABM is oriented to the future use of control strategies and optimal irrigation policies. The model is built bottom-up starting with the definition of agents, and the Python environment Mesa is chosen for the implementation. The validation is carried out using three topographic scenarios in Colombia. Results of potential production cases are discussed, and some practical recommendations on the implementation are presented.

scholarly journals How model paradigms affect our representation of future land-use change

2020 ◽  
Author(s):  
Calum Brown ◽  
Ian Holman ◽  
Mark Rounsevell
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
System Development ◽  
Active Management ◽  
Integrated Modelling ◽  
Agent Based Model ◽  
Agent Based ◽  
Modelling Framework ◽  
Land Use Models ◽  
Landscape Scales

Abstract. Land use models operating at regional to global scales are almost exclusively based on the single paradigm of economic optimisation. Models based on different paradigms are known to produce very different results, but these are not always equivalent or attributable to particular assumptions. In this study, we compare two pan-European land use models that are based on the same integrated modelling framework and utilise the same climatic and socio-economic scenarios, but which adopt fundamentally different model paradigms. One of these is a constrained optimising economic-equilibrium model and the other is a stochastic agent-based model. We run both models for a range of scenario combinations and compare their projections of spatial and aggregate land use change and ecosystem service supply. We find that the agent-based model projects more multifunctional and heterogeneous landscapes in most scenarios, providing a wider range of ecosystem services at landscape scales, as agents make individual, time-dependent decisions that reflect economic and non-economic motivations. This tendency also results in food shortages under certain scenario conditions. The optimisation model, in contrast, maintains food supply through intensification of agricultural production in the most profitable areas, sometimes at the expense of active management in large, contiguous parts of Europe. We relate the principal differences observed to underlying model assumptions, and hypothesise that optimisation may be appropriate in scenarios that allow for coherent political and economic control of land systems, but not in scenarios where economic and other scenario conditions prevent the normal functioning of price signals and responses. In these circumstances, agent-based modelling allows explicit consideration of behavioural processes, but in doing so provides a highly flexible account of land system development that is harder to link to underlying assumptions. We suggest that structured comparisons of parallel, transparent but paradigmatically distinct models are an important method for better understanding the potential scope and uncertainties of future land use change.

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