Academic articles

Simulation of Allocation Policies for a Serial Inventory System under Advance Demand Information using Supply Chain Management Software

In this paper, we simulate allocation policies for a two-stage inventory system that receives perfect advance demand information (ADI) from customers belonging to different demand classes using AnyLogic as supply chain management software. Demands for each customer class are generated by independent Poisson processes while the processing times are deterministic. All customers in the same class have the same demand lead time (the difference between the due date and the requested date) and back-ordering costs.

Each stage in the inventory system follows order-base-stock-policies where the replenishment order is issued upon arrival of a customer order. The researchers employ discrete event simulation to obtain output parameters such as inventory costs, fill rates, waiting time, and order allocation times. A numerical analysis is conducted to identify a reasonable policy to use in this type of system.

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.

Analyzing the Influence of Costs and Delays on Mode Choice in Intermodal Transportation Network by Combining Sample Average Approximation and Discrete Event Simulation

Besides transportation costs the punctual delivery of the goods is a key factor for mode choice in intermodal transportation networks. However, only a limited number of studies have included stochastic transportation time in Service Network Design, which refers to decisions regarding transportation mode and services, so far.

The paper on hand combines a Sample Average Approximation approach with Discrete Event Simulation for transportation network optimization with stochastic transportation times. This includes the corresponding vehicle routing problem for road vehicles. The share of orders transported by intermodal road-rail vs. unimodal road transportation in dependence of costs and delays of the trains is evaluated for a generic transportation relation in Central Europe. The data is backed by empirical data for transportation orders and delay distributions.

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.

Simulation-based Production Planning Optimization of a Manufacturing Facility with Vertical Automated Storage and Retrieval Systems

Klein Mechanisch Werkplaats Eindhoven (KMWE) is a precision manufacturing company situated in the Netherlands and recently relocated to a new location known as the 'Brainport Industries Campus' (BIC). This move allowed KMWE to improve the performance of its manufacturing facility by investing in vertical automated storage and retrieval systems (AS/RSs). However, these decisions needed to be made under input uncertainties since the move to BIC and modernization of existing equipment would cause changes in operating parameters inside the facility.

In this study, the researchers show how hybrid simulation modelling was used in production planning optimization, in particular to assess the impact of input uncertainties (such as operator productivity, vertical storage height) on the throughput performance of TSC.

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.

Assessment of the Impact of Teledermatology using Discrete Event Simulation

Evolution of technology and the complexity of the medical system have contributed to the increasing interest in telemedicine. The purpose of this paper is to present a discrete event simulation model of the teledermatology process using the tool TelDerm. The logic of the simulation describes the telemedicine work flow from the detection of the problem to its resolution. The scenarios reflect different changes in the flow in order to quantify the impact of telemedicine on the healthcare system. Several key performance indicators measure medical and administrative workload variations for all human resources involved. In addition, we assess the impact on the patient’s journey through the process.