Depending on the amount of data to process, file generation may take longer.

If it takes too long to generate, you can limit the data by, for example, reducing the range of years.

Chapter

Download BibTeX

Title

Logistics process improvement using simulation optimisation

Authors

[ 1 ] Instytut Transportu, Wydział Inżynierii Lądowej i Transportu, Politechnika Poznańska | [ P ] employee

Scientific discipline (Law 2.0)

[2.7] Civil engineering, geodesy and transport

Year of publication

2024

Chapter type

chapter in monograph / paper

Publication language

english

Keywords
EN
  • logistics process improvement
  • simulation optimisation
  • multiple criteria stochastic optimisation
  • ExtendSim
Abstract

EN This paper refers to the problem of delivery process improvement. The subject of supply are parts and components for a vehicle production company. The deliveries are performed upon just-in-time strategy from the external warehouse to the factory. The authors propose a six-stage procedure which combines three research areas, i.e. process analysis, dynamic simulation and simulation optimisation. In Stage 1 of this procedure, the logistics process is analysed and modelled using process notation. The major process operations, cause and effect relationships, key human and technical resources and their assignment to the activities are identified. In Stage 2, the process’ model is converted into the simulation model of deliveries to enable a dynamic simulation of its operations and to evaluate the process performance. In Stage 3, the simulation model is customised and the computational experiments are carried out. Based on the analysis of results weaknesses of the process are identified. In Stage 4, the simulation model is extended by a formulation of objective functions and constraints to run a simulation optimisation (Stage 5). Finally, the compromise solution is selected and the logistics process improvement is proposed. It is compared with the previous result of the authors’ research where this problem was solved using a stochastic multiple criteria ranking approach. Then the alternative process scenarios were ranked and the one with the highest position in the hierarchy was recommended. This solution and the new one from the current research are juxtaposed in this paper, and the differences between methodological approaches are presented.

Pages (from - to)

128 - 134

DOI

10.37904/clc.2023.4857

URL

https://www.confer.cz/clc/2023/4857-logistics-process-improvement-using-simulation-optimisation

Book

CLC 2023 Logistics & Supply Chain Management. Conference Proceedings. 11th Carpathian Logistics Congress - CLC 2023, November 8 - 10, 2023, Wellness Hotel Step, Prague, Czech Republic, EU

Presented on

11th Carpathian Logistics Congress, CLC 2023, 8-10.11.2023, Prague, Czech Republic

Open Access Mode

publisher's website

Open Access Text Version

final published version

Date of Open Access to the publication

at the time of publication

Ministry points / chapter

5

This website uses cookies to remember the authenticated session of the user. For more information, read about Cookies and Privacy Policy.