Izvorni znanstveni članak

https://doi.org/10.17559/TV-20220723180901

Pareto Optimality of Centralized Procurement Based on Genetic Algorithm

Fengxia Ding ; 1) School of Economics and Management, Beijing Jiaotong University, 2) China Energy Investment Corporation Limited, NO. 3, Shangyuancun, Haidianqu Beijing Jiaotong University, Beijing 100044, China
Shifeng Liu orcid.org/0000-0002-5996-3384 ; School of Economics and Management, Beijing Jiaotong University, NO. 3, Shangyuancun, Haidianqu Beijing Jiaotong University, Beijing 100044, China
Xuewei Li ; School of Economics and Management, Beijing Jiaotong University, NO. 3, Shangyuancun, Haidianqu Beijing Jiaotong University, Beijing 100044, China

Sažetak

In the process of purchasing materials, small enterprises are often unable to meet the minimum availability of suppliers in the process of purchasing due to the lack of economic strength and storage capacity of goods. Therefore, they will encounter difficulties in the process of purchasing.To solve this problem, the group-led centralized procurement strategy for small enterprises has become a new craze. In this paper, we transform the problem of centralized procurement lot into a multi-objective optimization problem by establishing a multi-objective optimization model with cost, quality and logistics as sub-objectives, and use genetic algorithms to solve the multi-objective optimization problem in order to achieve Pareto optimality among each purchaser and supplier. Finally, an example of procurement by the China Energy Investment Corporation is used to verify that the multi-objective optimization model for the collection of lots constructed in this paper can effectively promote the cooperation between purchasers and suppliers, and stimulate the competitive vitality of enterprises in the market.

Ključne riječi

centralized procurement; genetic algorithm; multi-objective optimization; Pareto optimal

Hrčak ID:

284924

URI

https://hrcak.srce.hr/284924

Datum izdavanja:

29.10.2022.

Posjeta: 713 *