Forthcoming and Online First Articles

International Journal of Simulation and Process Modelling

International Journal of Simulation and Process Modelling (IJSPM)

Forthcoming articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

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International Journal of Simulation and Process Modelling (2 papers in press)

Regular Issues

  • DrugApp: a simulation of drug suspects and offenders classification   Order a copy of this article
    by Donald D. Atsa'am, Terlumun Gbaden, Ruth Wario 
    Abstract: A prototype web application, named DrugApp, was developed in this study to simulate the classification of illicit drug suspects. The application logic implements an existing Artificial Neural Network (ANN) model that uses four attributes namely, type of exhibit, age of suspect, weight of exhibit, and gender of suspect, to predict the class of a drug suspect as either a drug peddler or non-drug peddler. System design was carried out using Unified Modeling Language (UML) tools, and development of the system followed the object-oriented programming paradigm. The app consists of graphical user interfaces (GUIs) to facilitate suspect’s classification in an easy and efficient manner. DrugApp could be a valuable tool to aid the Police, Immigration, and other law enforcement agents at airports, seaports, and land borders for classifying drug-related suspects while in transit.
    Keywords: DrugApp; drug suspects classification; drug peddler; non-drug peddler; security agents.
    DOI: 10.1504/IJSPM.2024.10066647
     
  • Dynamic rolling optimisation model and VNTSA algorithm for timely delivery servicesServices   Order a copy of this article
    by Siqi Zhang, Wei Jia 
    Abstract: This paper tackles the challenges of order allocation and intelligent scheduling in online-to-offline fresh food instant delivery services, focusing on timely delivery and enhancing consumer experience in dynamic environments. We develop a dynamic time-domain rolling optimisation model to maximise customer satisfaction while minimising business costs. The model incorporates a novel variable neighbourhood tabu simulated annealing (VNTSA) algorithm, which combines variable neighbourhood search and a tabu list to enhance the simulated annealing (SA) algorithm. Our approach addresses dynamic order insertion, allocation, and scheduling effectively. Case analyses demonstrate that the proposed model and VNTSA algorithm excel in handling dynamic environments, outperforming traditional SA and the widely used the non-dominated sorting genetic algorithm II in solving efficiency and customer satisfaction. This leads to significant cost reductions and improvements in delivery times, underscoring the practical value of our contributions.
    Keywords: dynamic optimisation; rolling optimisation model; improved SA algorithm; timely delivery; online-to-offline; O2O.
    DOI: 10.1504/IJSPM.2024.10066945