{"title":"A resilient poultry vaccine supply chain network design considering perishability and stress test","authors":"Mina Mehravaran, Arash Nemati","doi":"10.1016/j.sca.2024.100098","DOIUrl":null,"url":null,"abstract":"<div><div>Vaccines and seeds are the most significant resources in the poultry industry, particularly for chicken as a global staple. However, designing a resilient network for the poultry vaccine supply chain to create a viable poultry industry has been neglected. Hence, this paper contributes to the poultry vaccine supply chain network design and planning problem by proposing a multi-period mixed-integer linear mathematical model. This model formulizes several resiliency strategies, including considering surplus vaccine production capacity, inventory holding in the customers and manufacturers, simultaneous utilization of both offshore suppliers and domestic manufacturers, and the necessity for fulfilling a proportion of periodic demand using warehoused vaccines. In addition, time-based prices and limited holding periods of poultry vaccines are considered in the model formulation to consider vaccine perishability. The newly developed model minimizes the poultry vaccine supply chain’s total costs, including vaccine purchasing, transportation, warehousing, manufacturer establishment, and opportunity cost, to make decisions on poultry vaccine manufacturer location-allocation, offshore supplier selection, customer order allocation, depot selection, and production capacity allocation. This model is solved in a case study of the chicken industry from Iran using CPLEX solver to design a new supply chain network for Newcastle, Gumboro, and Bronchitis vaccines from 2025 to 2030. Results showed that 6, 7, and 7 locations of 8 candidates have opted for Newcastle, Gumboro, and Bronchitis vaccine production lines establishment, respectively, and two offshore suppliers are selected between 4 potential ones. In addition, the results of stress tests verified the effectiveness of employed resiliency strategies, and sensitivity analysis showed the significant impact of demand variability on establishment and purchasing costs.</div></div>","PeriodicalId":101186,"journal":{"name":"Supply Chain Analytics","volume":"9 ","pages":"Article 100098"},"PeriodicalIF":0.0000,"publicationDate":"2024-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Supply Chain Analytics","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2949863524000414","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Vaccines and seeds are the most significant resources in the poultry industry, particularly for chicken as a global staple. However, designing a resilient network for the poultry vaccine supply chain to create a viable poultry industry has been neglected. Hence, this paper contributes to the poultry vaccine supply chain network design and planning problem by proposing a multi-period mixed-integer linear mathematical model. This model formulizes several resiliency strategies, including considering surplus vaccine production capacity, inventory holding in the customers and manufacturers, simultaneous utilization of both offshore suppliers and domestic manufacturers, and the necessity for fulfilling a proportion of periodic demand using warehoused vaccines. In addition, time-based prices and limited holding periods of poultry vaccines are considered in the model formulation to consider vaccine perishability. The newly developed model minimizes the poultry vaccine supply chain’s total costs, including vaccine purchasing, transportation, warehousing, manufacturer establishment, and opportunity cost, to make decisions on poultry vaccine manufacturer location-allocation, offshore supplier selection, customer order allocation, depot selection, and production capacity allocation. This model is solved in a case study of the chicken industry from Iran using CPLEX solver to design a new supply chain network for Newcastle, Gumboro, and Bronchitis vaccines from 2025 to 2030. Results showed that 6, 7, and 7 locations of 8 candidates have opted for Newcastle, Gumboro, and Bronchitis vaccine production lines establishment, respectively, and two offshore suppliers are selected between 4 potential ones. In addition, the results of stress tests verified the effectiveness of employed resiliency strategies, and sensitivity analysis showed the significant impact of demand variability on establishment and purchasing costs.