LOGISTICS PROCESS IMPROVEMENT USING SIMULATION OPTIMISATION

1 SAWICKI Piotr
Co-authors:
1 SAWICKA Hanna
Institution:
1 Poznań University of Technology, Poznań, Poland, EU, piotr.sawicki@put.poznan.pl, hanna.sawicka@put.poznan.pl
Conference:
CLC 2023 - Carpathian Logistics Congress, Wellness Hotel Step, Prague, Czech Republic, EU, November 8 - 10, 2023
Proceedings:
Proceedings CLC 2023 - Carpathian Logistics Congress
Pages:
128-134
ISBN:
978-80-88365-17-4
ISSN:
2694-9318
Published:
10th April 2024
Metrics:
15 views / 19 downloads
Abstract

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.

Keywords: Logistics process improvement, simulation optimisation, multiple criteria stochastic optimisation, ExtendSim

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