论文

A Post-Brexit Transportation System Analysis for an Agri-Fresh Produce Supply Chain


The ever-increasing demand for fresh and healthy products initiated an urgency for transportation system analysis and effective planning for Agri-Fresh Produce Supply Chains (AFPSC). However, AFPSC faces many challenges, including product vulnerability to market disruption and limited shelf-life. In case of a no-deal Brexit (i.e., the UK leaving the EU without an agreement), trade between Ireland and the UK will most probably be subjected to customs control. In effect, transportation delays and products deterioration rates will increase.

Based on interviews with an Irish AFPSC forwarder, a simulation model was developed to investigate different systems’ dynamics and operating rules under different delay patterns on the (yet non-existent) inner-Irish border.

A Case Study in Last-Mile Delivery Concepts for Parcel Robots using Delivery Optimization Software


This study was designed to evaluate innovative last-mile delivery concepts involving autonomous parcel robots with simulation and optimization. In the proposed concept, the last mile of parcel delivery is split into a two-tiered system, where parcels are first transported to a transfer point by conventional trucks and then delivered with parcel robots on customer demand.

The purpose of this publication is to compare different time slot selection options for customers, namely due window and on demand selection, in the context of city logistics measures such as access regulations and driving bans for city centers. The researchers use AnyLogic as delivery optimization software. They build an agent-based simulation model, including a Geographic Information System environment and optimization algorithms for allocation and scheduling of delivery robots.

Simulation-based Tool for Maintenance Planning using Field Service Scheduling Software


A common challenge in field service planning is to evaluate different design choices, related to staffing decisions, technician scheduling strategies, and technological improvements in order to make the system more efficient. This work provides a simulation-based optimization tool to support decision makers in tackling this challenging problem. The proposed framework relies on an optimization engine for the generation of the daily plans.

The study uses AnyLogic as field service planning software to evaluate the applicability of such plans by taking into account the stochastic factors. Furthermore, an interface manages the communication between these two components and allows a feedback loop between the simulator and the optimizer to achieve more robust plans. The applicability of the framework is demonstrated through a business case to evaluate different staffing decisions.

Modeling Home Grocery Delivery Using Electric Vehicles and Transport Network Analysis Results


This paper presents transportation network analysis results based on data from an agent-based simulation study. The research is aimed at establishing whether a fleet of electric vans with different charging options can match the performance of a diesel fleet. The researchers describe a base model imitating the operations of a real-world retailer using agents. They then introduce electric vehicles and charging hubs into their model. After that, they evaluate how the use of electric vehicles, charging power, and charging hubs influence the retailer’s operations. The simulation experiment suggests that, though they are useful, technological interventions alone are not sufficient to match the performance of a diesel fleet. Hence, reorganization of the urban delivery system is required in order to reduce carbon emissions significantly.

On the Extension of Schelling's Segregation Model


Schelling’s social segregation model has been extensively used for human behavior analysis and studied over the years. A major implication of the model is that individual preferences of similarity lead to a collective segregation behavior. Schelling used Agent-Based Modeling (ABM) with uni-dimensional agents. In reality, people are multidimensional. This raises the question of whether multi-dimensionality can boost stability or reduce segregation in society.

Airport Passenger Shopping Modeling and Simulation: Targeting Distance Impacts


The ever-increasing importance of airport retail has encouraged both industry and academics to look into ways to increase airport retail revenue. Despite the growing interest in this topic, there is a lack of passenger shopping behavioral model. This paper aims to fill this gap and enhance our understanding of how the location of the shop affects passenger decision. This paper first investigates the possible passenger shopping behavioral model through an exploratory Eye-tracking exercise. Data was collected to calibrate and validate the behavioral model through the use of an Agent-Based Simulation Model.

STTAR: a Simheuristics-enabled Scheme for Multi-stakeholder Coordination of Aircraft Turnaround Operations


Aircraft ground handling involves all services to an aircraft (e.g. passenger boarding/disembarking, re-fuelling, deicing) between its arrival and immediately following departure. The aircraft, parked at its stand, witnesses a number of service providers move around it to perform their duties. Inter-dependencies among service providers abound, and knock-on effects at disrupted times are rife. Coordination from the side of the airport operator is difficult.

The research team proposes a tactical robust scheme by which ground handlers and the airport operator cooperate, although indirectly, in the development of plans for the next day that are less likely to be impacted by at least the more frequent operational disruptions. The scheme is based on a simheuristic approach which integrates ad-hoc heuristics with a hybrid simulation model (agent-based/discrete-event).

Electric Vehicles: The Driving Power for Energy Transition - Blockchain-based Decentralised Energy Trading


The purpose of this research is to investigate how electric vehicles can promote energy transition and how blockchain can facilitate the decentralisation of future energy systems.

With the slow but steady rollout of smart meters and advancements in internet of things (IoT) technology, and with the help of agent-based modeling, the results from this study will prove the worth of blockchain’s inclusion in the smart grids of the future.

Simulation of epidemic trends for a new coronavirus under effective control measures


In December 2019, there was a case of viral pneumonia in Wuhan. After confirming that the pathogen of this disease is a new coronavirus, the World Health Organization (WHO) confirmed and named it 2019-nCoV. The pneumonia caused by this pathogen infection is called a novel corona virus pneumonia.

To better understand the mode of transmission of 2019-nCoV among the population and the effects of control measures, the study was conducted using agent-based modeling (ABM) to simulate an interactive environment over a certain space-time range. The study simulates the trend of 2019-nCoV infection at different levels of close contact in order to provide relevant information and references.