{"title":"A location-inventory-pricing supply chain network design for perishable products under disruption","authors":"Toba Asghari, S. Aghamohamadi-Bosjin, M. Rabbani","doi":"10.22059/IJMS.2020.287086.673754","DOIUrl":null,"url":null,"abstract":"In this study, we discuss a location-inventory-pricing model considering thecapacity constraints of the warehouses, disruption, and multiple perishable products.We extend a model with assuming that warehouses may face disruption, failedwarehouses cannot cover any service and also their customers are assigned to otherwarehouses. For decreasing the risk of disruption, we examine the efficiency ofmarkup pricing strategy and support services. The objective function of this MINLPis to maximize the total profit of warehouses. To solve this model, GeneticAlgorithm (GA) and Grasshopper Optimization Algorithm (GOA) are used. Toevaluate the recommended model, several sensitivity analyses are proposed. Finally,the results of numerical experiments implicate the high-performance of GOA indealing with problems and achieving better results. According to the results, backupservices and markup pricing strategies are very effective in reducing the damagecaused by the disruption.","PeriodicalId":51913,"journal":{"name":"Iranian Journal of Management Studies","volume":" ","pages":""},"PeriodicalIF":0.8000,"publicationDate":"2020-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Iranian Journal of Management Studies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22059/IJMS.2020.287086.673754","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MANAGEMENT","Score":null,"Total":0}
引用次数: 1
Abstract
In this study, we discuss a location-inventory-pricing model considering thecapacity constraints of the warehouses, disruption, and multiple perishable products.We extend a model with assuming that warehouses may face disruption, failedwarehouses cannot cover any service and also their customers are assigned to otherwarehouses. For decreasing the risk of disruption, we examine the efficiency ofmarkup pricing strategy and support services. The objective function of this MINLPis to maximize the total profit of warehouses. To solve this model, GeneticAlgorithm (GA) and Grasshopper Optimization Algorithm (GOA) are used. Toevaluate the recommended model, several sensitivity analyses are proposed. Finally,the results of numerical experiments implicate the high-performance of GOA indealing with problems and achieving better results. According to the results, backupservices and markup pricing strategies are very effective in reducing the damagecaused by the disruption.