Academic articles

Simulating an Automated Breakpack System to Improve Warehouse Efficiency and Operations


This case study focuses on the simulation of a soon-to-be-implemented automation system within a Walmart Canada warehouse. This new system's aim is more efficient warehouse operations. Many stock-keeping units (SKUs) cannot be sent to retail stores in full case quantities. They are slow movers and would require individual stores to carry excessive inventory.

Breakpack is the process of breaking cases down to individual eaches (pieces) and combining them into mixed SKU cartons. Automating breakpack offers significant labor and quality savings, that are important to ensure efficient warehouse operations, but also a high degree of complexity.

Electric Vehicles Modelling and Simulations for Long-Haul Logistics


Long-haul trailer operations are a critical part of supply chains in many of the world’s developed economies. In the UK, it is estimated that long-haul logistics contributes around 45% of all greenhouse gas emissions from road freight.

One way to reduce greenhouse gas emissions in this sector is by fitting a battery on the trailer. However, long-haul operations are very energy-intensive and electric vehicles would require batteries of considerable size and weight. Applying agent-based modelling and simulation, this paper aims at analyzing if electrification (e.g., electric vehicle fleet, electric road system, etc.) would help reduce greenhouse gas emissions.

Multi-agent Optimization of the Intermodal Terminal Main Parameters: Research Based on a Case Study


Due to numerous uncertainties such as bad weather conditions, frequent changes in the schedules of vessels, breakdowns of equipment, port managers are aiming at providing adaptive and flexible strategic planning of their facilities, especially intermodal terminals (dry ports).

This research shows that the combination of the agent-based modeling with other simulation approaches simplifies the process of designing simulation models and increases their visibility. The developed set of models allows the researchers to compute the balanced values of the parameters. Consequently, it helps achieve effective operation of a seaport – intermodal terminal system. The provided case study on one of the busiest ports in China proves the adequacy and validity of the developed simulation models.

Transportation Optimization Model of an Ambulance System in India


According to a World Health Organization (WHO) report in 2018, 1.35 million people die each year due to road accidents globally. In a country like India, it is becoming increasingly difficult to provide post-accident services on time with an increase in congestion. In this paper, the researchers propose a system which decreases the post-accident response time of Emergency Medical Services (EMS) in India by adding another layer of the patient transport vehicle. Based on a transportation system analysis, the paper discusses a new algorithm and a system design with a transportation optimization simulation model.

Supply Chain Simulation Modeling to design the Second-generation Biofuel Transportation Network


The goal of this study is to contribute to commercialization of the second-generation cellulosic biofuels (SGCBs) by reducing its operational cost. A hybrid simulation-based optimization approach is devised to design a cost-effective SGCB supply chain model. The approach includes feedstock yield estimation and location-allocation of feedstock storages between farms and refineries. An agent-based simulation (ABS) implemented in AnyLogic is utilized to estimate operational cost of a SGCB supply chain. The simulation-based optimization with adaptive replication (AR) is devised to find an appropriate SGCB network design in terms of operational cost. The approach is applied to a SGCB transportation network design problem in Southern Great Plains of U.S.

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.