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Title:A imatheuristic approach combining genetic algorithm and mixed integer linear programming model for production and distribution planning in the supply chain
Authors:ID Guzman, E. (Author)
ID Poler, Raúl (Author)
ID Andres, B. (Author)
Files:.pdf APEM18-1_019-031.pdf (778,79 KB)
MD5: 7765E74A0A5F0EC6ACA6F4136261648A
 
URL https://apem-journal.org/Archives/2023/Abstract-APEM18-1_019-031.html
 
Language:English
Work type:Article
Typology:1.01 - Original Scientific Article
Organization:FS - Faculty of Mechanical Engineering
Abstract:A number of research studies have addressed supply chain planning from various perspectives (strategical, tactical, operational) and demonstrated the advantages of integrating both production and distribution planning (PDP). The globalisation of supply chains and the fourth industrial revolution (Industry 4.0) mean that companies must be more agile and resilient to adapt to volatile demand, and to improve their relation with customers and suppliers. Hence the growing interest in coordinating production-distribution processes in supply chains. To deal with the new market’s requirements and to adapt business processes to industry’s regulations and changing conditions, more efforts should be made towards new methods that optimise PDP processes. This paper proposes a matheuristic approach for solving the PDP problem. Given the complexity of this problem, combining a genetic algorithm and a mixed integer linear programming model is proposed. The matheuristic algorithm was tested using the Coin-OR Branch & Cut open-source solver. The computational outcomes revealed that the presented matheuristic algorithm may be used to solve real sized problems. idance for large group enterprises to carry out centralized procurement management.
Keywords:production and distribution planning, supplay chain, matheuristic, genetic algorithm, mixed integer linear programming model
Publication status:Published
Publication version:Version of Record
Submitted for review:29.04.2022
Article acceptance date:27.12.2022
Publication date:29.03.2023
Publisher:Chair of Production Engineering (CPE), University of Maribor Faculty of Mechanical Engineering
Year of publishing:2023
Number of pages:str. 19-31
Numbering:Vol. 18, no. 1
PID:20.500.12556/DKUM-96991 New window
UDC:658.5
ISSN on article:1854-6250
COBISS.SI-ID:267807747 New window
DOI:10.14743/apem2023.1.454 New window
Copyright:Content from this work may be used under the terms of the Creative Commons Attribution 4.0 International Licence (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:10.02.2026
Views:155
Downloads:3
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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 Conselleria de Educación, Investigación, Cultura y Deporte - Generalitat Valenciana
Funding programme:Hiring predoctoral research staff
Project number:ACIF/2018/170

Funder:European Social Fund
Funding programme:Grant Operational Program of FSE 2014-2020, the Valencian Community

Funder:EC - European Commission
Funding programme:European Union H2020 Programme
Project number:No. 958205
Name:"Industrial Data Services for Quality Control in Smart Manufacturing" (i4Q)

Funder:the Regional Department of Innovation, Universities, Science and Digital Society of the Generalitat Valenciana
Project number:Ref. PRO- METEO/ 2021/065
Name:"Industrial Production and Logistics Optimization in Industry 4.0" (i4OPT)

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:dobavna veriga, matevristika, genetski algoritmi


Collection

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

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