Multi-item multi-constraint supply chain integrated inventory model with multi-variable demand under the effect of preservation technology. Issue 1 (31st December 2016)

• Record Type: Journal Article
• Authors: Yadav, Dharmendra; Singh, S.R.; Arora, Vandana
• Editors: Li, Yibing
• Is Part Of: Cogent engineering. Volume 3:Issue 1(2016)
• Publication Date: 2016-12-31
• Subjects: integrated model -- multi-variable demand -- budget and space constraint -- trade credit -- Lagrangian multiplier method; Engineering -- Periodicals; Technology -- Periodicals; Engineering; Technology; Periodicals; 620
• DOI: 10.1080/23311916.2016.1272159
• Languages: English
• ISSNs: 2331-1916

Abstract

Abstract: Today's every firms have realized that managing supply chain (SC) and deciding their integrated scheduling policy is substantial. Decision-makers of all the firms always keep searching different policies such as trade credit, preservation technology. By adopting these policies they help in strengthen the relationship among different players of supply chain. It is also observed that decision-makers develop policies for integrated system under some restrictions such as budget constraint. Infeasible solutions of many real world problems are obtained by ignoring such restriction. On focusing all these issues, in this paper, a multi-item integrated supply chain inventory model is formulated by considering one manufacturer and one retailer over a finite planning horizon. Manufacturer provides trade credit period to its retailer to strengthen the supply chain. It is assumed that the demand is multi-variable which depends on trade credit period and selling price of the items. In a real-life integrated supply chain inventory system, limitations on available budget and storage space are always faced by the manufacturer and the retailer. So, model is formulated to minimize the total integrated cost of the system subject to space and budget constraints. Optimal values of decision variables and objective function is obtained by using Lagrangian Multiplier Method (LMM). Proposed model is illustrated with the help of numerical and sensitive analysis is carried out with respect to different parameters.