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Title:Hierarchical hybrid simulation optimization of the pharmaceutical supply chain
Authors:ID Altarazi, S. (Author)
ID Shqair, M. (Author)
Files:.pdf APEM18-1_066-078.pdf (993,32 KB)
MD5: D9E3BB6DB6F1C56CBDE27E0CA583D256
 
URL https://apem-journal.org/Archives/2023/Abstract-APEM18-1_066-078.html
 
Language:English
Work type:Article
Typology:1.01 - Original Scientific Article
Organization:FS - Faculty of Mechanical Engineering
Abstract:In this paper, a global simulation optimization approach is developed to imitate and optimize the performance of the Pharmaceutical Supply Chain (PSC). Firstly, a hierarchical hybrid simulation model is developed in which aggregate and detailed data levels are addressed simultaneously. The model consists of two types of interdependent paradigms: the system dynamics paradigm, which depicts the echelons of pharmacies and wholesalers in the PSC, and the discrete event paradigm, which simulates the manufacturers with their detailed production operations, as well as the echelons of suppliers. Secondly, the "As is" scenario analysis and a screening process are performed to extract significant input parameters as well as sensitive outputs of the model. The final step optimizes the performance of PSC. The proposed approach validity is appraised by being applied to the PSC of a leading pharmaceutical company in Jordan. As a result, the opportunity loss cost has considerably decreased for both the manufacturer and wholesalers’ echelons and the service level has improved throughout the PSC.
Keywords:system dynamics, discrete-event, simulation optimizatoin, hybrid simulation, scatter search, tabu search, artificial neural networks, ANN, anyLogic simulation software, optQuest optimization package, pharmaceutical supply chain
Publication status:Published
Publication version:Version of Record
Submitted for review:31.12.2022
Article acceptance date:15.04.2023
Publication date:29.04.2023
Publisher:Chair of Production Engineering (CPE), University of Maribor Faculty of Mechanical Engineering
Year of publishing:2023
Number of pages:str. 66-78
Numbering:Vol. 18, no. 1
PID:20.500.12556/DKUM-97023 New window
UDC:658.5
ISSN on article:1854-6250
COBISS.SI-ID:267961603 New window
DOI:10.14743/apem2023.1.457 New window
Copyright:Content from this work may be used under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0). Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
Publication date in DKUM:12.02.2026
Views:142
Downloads:4
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Categories:Misc.
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Record is a part of a journal

Title:Advances in production engineering & management
Shortened title:Adv produc engineer manag
Publisher:Fakulteta za strojništvo, Inštitut za proizvodno strojništvo
ISSN:1854-6250
COBISS.SI-ID:229859072 New window

Document is financed by a project

Funder:the deanship of scientific research at the German Jordanian University
Project number:grant number SATS/48/2018

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

Secondary language

Language:Slovenian
Keywords:dinamika, nevronske mreže


Collection

This document is a part of these collections:
  1. Advances in production engineering & management

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