arXiv subjects

Mohd Shoaib

Publications and source records attributed to Mohd Shoaib.

3 recordsLinked to original sources

arXiv2026

A Hybrid Discrete-Event and Agent-Based Simulation Approach to Model Circular Supply Chains in Healthcare: A Case Study of Laparoscopic Scissors

Circular healthcare supply chains are inherently complex, characterised by interdependencies among their actors and high uncertainty in product flows and performance. Current methods used to predict the outcomes of transitioning to circular economy (CE) are limited and mostly static. This paper demonstrates the use of simulation to assess the effect of introducing circular products and the implications across the healthcare supply chain accounting for variability. The laparoscopic scissors supply chain is chosen as a case study example. To the best of our knowledge, this is the first study that assesses the implications of introducing circular product (medical devices) designs at both the individual supply chain member and overall system level. The model can be also used to inform optimal inventory strategies for hospitals, to ensure that patient safety and hospital operations are maintained. Our findings suggest that adopting circular products can reduce the environmental impact, but to achieve significant reductions in both cost and emissions, it requires significant upfront investment. We discuss the theoretical and practical implications of our study in developing tools to support the transition to CE.

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arXiv2025

A Framework for Predicting Runtime Savings from Discrete-Event Simulation Model Simplification Operations

Abstraction or substitution and aggregation are the most widely used simulation model simplification operations. Abstraction involves replacing subsystems within a discrete-event simulation (DES) with one or more quantities - typically random variables - representing the lengths of stay in the subsystems(s) in question to create a `simplified' system comprising only of subsystems of interest to the analysis at hand. Aggregation involves replacing more than one subsystem of the original `parent' simulation with a single subsystem. However, the model simplification process itself can be expensive, in terms of the computational runtime and effort required to collect the data required to estimate the distributions of the length of stay variables, the distribution-fitting process, and testing and validation of the simplified model. Moreover, the savings in simulation runtime that the simplification process yields is \textit{a priori} unknown to the modeller. In this context, a method that predicts the runtime savings (RS) from DES model simplification operations before their execution - at the conceptualisation stage of the simplified model development process - may help judge whether its development is indeed worth undertaking. In this paper, we present a queueing-theoretic framework for the prediction of RS from model simplification operations. Our framework is applicable for DES models comprising $M/M/, M/G/ \text{ and } G/G/$ subsystems. The performance of the RS prediction framework is demonstrated using multiple computational experiments. Our proposed framework contributes to the literature around DES model complexity and more broadly to DES runtime prediction.

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arXiv2021

Simulation Modelling and Analysis of Primary Health Centre Operations

We present discrete-event simulation models of the operations of primary health centres (PHCs) in the Indian context. Our PHC simulation models incorporate four types of patients seeking medical care: outpatients, inpatients, childbirth cases, and patients seeking antenatal care. A generic modelling approach was adopted to develop simulation models of PHC operations. This involved developing an archetype PHC simulation, which was then adapted to represent two other PHC configurations, differing in numbers of resources and types of services provided, encountered during PHC visits. A model representing a benchmark configuration conforming to government-mandated operational guidelines, with demand estimated from disease burden data and service times closer to international estimates (higher than observed), was also developed. Simulation outcomes for the three observed configurations indicate negligible patient waiting times and low resource utilisation values at observed patient demand estimates. However, simulation outcomes for the benchmark configuration indicated significantly higher resource utilisation. Simulation experiments to evaluate the effect of potential changes in operational patterns on reducing the utilisation of stressed resources for the benchmark case were performed. Our analysis also motivated the development of simple analytical approximations of the average utilisation of a server in a queueing system with characteristics similar to the PHC doctor/patient system. Our study represents the first step in an ongoing effort to establish the computational infrastructure required to analyse public health operations in India, and can provide researchers in other settings with hierarchical health systems a template for the development of simulation models of their primary healthcare facilities.

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