TY - GEN
T1 - Assessment of Supply Chain Performance in an Assembly Company
T2 - International Conference on Computer Science, Electronics and Industrial Engineering, CSEI 2020
AU - Orellana, Josselin
AU - Peña, Mario
AU - Llivisaca, Juan
N1 - Publisher Copyright:
© 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
PY - 2021
Y1 - 2021
N2 - In current globalized markets, companies no longer compete with each other. They now compete with the supply chains (SC) to which they belong. SC optimization allows efficient and effective management of resources. In many cases, optimization goals can conflict with one another. Therefore, the purpose of this work was to evaluate SC performance by comparing three optimization algorithms in a case study with multiple objectives. Two objectives are maximizing profit and maximizing the level of customer service. Also, the modeled problem considers multiple products and periods for two security inventory scenarios (maximum and minimum inventory levels). Evolutionary algorithms were compared: NSGA-II, MOPSO, and MOMA. The NSGA-II algorithm obtained the best result. With a minimum inventory level, NSGA-II presented 97.87% service level and the best benefit. Results show the importance of SC management and its optimization as well as some relevant variables to be considered.
AB - In current globalized markets, companies no longer compete with each other. They now compete with the supply chains (SC) to which they belong. SC optimization allows efficient and effective management of resources. In many cases, optimization goals can conflict with one another. Therefore, the purpose of this work was to evaluate SC performance by comparing three optimization algorithms in a case study with multiple objectives. Two objectives are maximizing profit and maximizing the level of customer service. Also, the modeled problem considers multiple products and periods for two security inventory scenarios (maximum and minimum inventory levels). Evolutionary algorithms were compared: NSGA-II, MOPSO, and MOMA. The NSGA-II algorithm obtained the best result. With a minimum inventory level, NSGA-II presented 97.87% service level and the best benefit. Results show the importance of SC management and its optimization as well as some relevant variables to be considered.
KW - Algorithms
KW - MOPSO
KW - MPAES
KW - Multi-objective optimization
KW - NSGA-II
KW - Supply chain
UR - https://www.scopus.com/pages/publications/85104832391
U2 - 10.1007/978-981-33-4565-2_11
DO - 10.1007/978-981-33-4565-2_11
M3 - Contribución a la conferencia
AN - SCOPUS:85104832391
SN - 9789813345645
T3 - Advances in Intelligent Systems and Computing
SP - 167
EP - 183
BT - Advances and Applications in Computer Science, Electronics and Industrial Engineering - Proceedings of CSEI 2020
A2 - García, Marcelo V.
A2 - Fernández-Peña, Félix
A2 - Gordón-Gallegos, Carlos
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 26 October 2020 through 30 October 2020
ER -