Minimum Viable Model (MVM) Methodology for Integration of Agile Methods into Operational Simulation of Logistics (2022)
Type of ContentJournal Article
<jats:p>Background: Logistics problems involve a large number of complexities, which makes the development of models challenging. While computer simulation models are developed for addressing complexities, it is essential to ensure that the necessary operational behaviours are captured, and that the architecture of the model is suitable to represent them. The early stage of simulation modelling, known as conceptual modelling (CM), is thus dependent on successfully extracting tacit operational knowledge and avoiding misunderstanding between the client (customer of the model) and simulation analyst. Objective: This paper developed a methodology for managing the knowledge-acquisition process needed to create a sufficient simulation model at the early or the CM stage to ensure the correctness of operation representation. Methods: A minimum viable model (MVM) methodology was proposed with five principles relevant to CM: iterative development, embedded communication, soliciting tacit knowledge, interactive face validity, and a sufficient model. The method was validated by a case study of freight operations, and the results were encouraging. Conclusions: The MVM method improved the architecture of the simulation model through eliciting tacit knowledge and clearing up communication misunderstandings. It also helped shape the architecture of the model towards the features most appreciated by the client, and features not needed in the model. Originality: The novel contribution of this work is the presentation of a method for eliciting tacit information from industrial clients, and building a minimally sufficient simulation model at the early modelling stage. The framework is demonstrated for logistics operations, though the principles may benefit simulation practitioners more generally.</jats:p>
CitationLyu Z, Pons D, Zhang Y, Ji Z Minimum Viable Model (MVM) Methodology for Integration of Agile Methods into Operational Simulation of Logistics. Logistics. 6(2). 37-37.
This citation is automatically generated and may be unreliable. Use as a guide only.
Keywordssimulation conceptual modelling; discrete-event simulation; communication and collaboration; agile method; tacit knowledge; freight logistics
ANZSRC Fields of Research46 - Information and computing sciences::4612 - Software engineering
35 - Commerce, management, tourism and services::3509 - Transportation, logistics and supply chains::350903 - Logistics
RightsAll rights reserved unless otherwise stated
Showing items related by title, author, creator and subject.
Freight Operations Modelling for Urban Delivery and Pickup with Flexible Routing: Cluster Transport Modelling Incorporating Discrete-Event Simulation and GIS Lyu Z; Ji Z; Pons, Dirk; zhang, yilei (MDPI AG, 2021)Urban pickup and delivery (PUD) activities are important for logistics operations. Real operations for general freight involve a high degree of complexity due to daily variability. Discrete-event simulation (DES) is a ...
A sequential optimization-simulation approach for planning the transition to the low carbon freight system with case study in the North Island of New Zealand Gallardo, Patricio; Murray, Rua; Krumdieck, Susan (MDPI AG, 2021)Freight movement has always been, and always will be an essential activity. Freight transport is one of the most challenging sectors to transition to net-zero carbon. Traffic assignment, mode allocation, network planning, ...
A freight distribution exercise Murray R; Bishop D; Krumdieck S; Gallardo, Patricio (2020)Current state-of-the-art freight transport models capture behaviour-level processes driven by decisions on logistics aspects (i.e. choice of transport chain) and micro-level terminal operations (i.e. crane operation). Yet, ...