{"title":"单一制造商多买家集成生产-库存模式与第三方物流","authors":"Susheel Yadav, A. Agrawal, M. Vora","doi":"10.1504/ijbpscm.2020.10031444","DOIUrl":null,"url":null,"abstract":"This paper analyses a single manufacturer and multiple buyers supply chain where each buyer faces a price-sensitive demand. The manufacturer produces the item at a finite rate and ships to the buyers in multiple shipments of equal sized sub-batches. These shipments are made using third-party logistics support. The transportation cost is assumed to depend upon vehicle type and on the buyer to which shipment is made. The problem of determining right inventory policies to maximise the overall supply chain profit is formulated as a mixed-integer nonlinear programming (MINLP) model and a meta-heuristic based on particle swarm optimisation (PSO) is also proposed. The sensitivity analyses carried out shows the impact of the change in vehicle capacities, setup cost, unit cost, production rate and holding rate of the manufacturer on inventory policy and its related costs. The sensitivity analysis will provide a practical guide to the managers in reacting to a certain change in some parameter values, such as in the eventuality of increase in the setup cost for taking production of a larger lot size in one setup and supply the same to the buyers in more number of sub-batches without changing the sub-batch size.","PeriodicalId":37630,"journal":{"name":"International Journal of Business Performance and Supply Chain Modelling","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"A single manufacturer multiple buyers integrated production-inventory model with third-party logistics\",\"authors\":\"Susheel Yadav, A. Agrawal, M. Vora\",\"doi\":\"10.1504/ijbpscm.2020.10031444\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper analyses a single manufacturer and multiple buyers supply chain where each buyer faces a price-sensitive demand. The manufacturer produces the item at a finite rate and ships to the buyers in multiple shipments of equal sized sub-batches. These shipments are made using third-party logistics support. The transportation cost is assumed to depend upon vehicle type and on the buyer to which shipment is made. The problem of determining right inventory policies to maximise the overall supply chain profit is formulated as a mixed-integer nonlinear programming (MINLP) model and a meta-heuristic based on particle swarm optimisation (PSO) is also proposed. The sensitivity analyses carried out shows the impact of the change in vehicle capacities, setup cost, unit cost, production rate and holding rate of the manufacturer on inventory policy and its related costs. The sensitivity analysis will provide a practical guide to the managers in reacting to a certain change in some parameter values, such as in the eventuality of increase in the setup cost for taking production of a larger lot size in one setup and supply the same to the buyers in more number of sub-batches without changing the sub-batch size.\",\"PeriodicalId\":37630,\"journal\":{\"name\":\"International Journal of Business Performance and Supply Chain Modelling\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-08-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Business Performance and Supply Chain Modelling\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/ijbpscm.2020.10031444\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Business, Management and Accounting\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Business Performance and Supply Chain Modelling","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/ijbpscm.2020.10031444","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Business, Management and Accounting","Score":null,"Total":0}
A single manufacturer multiple buyers integrated production-inventory model with third-party logistics
This paper analyses a single manufacturer and multiple buyers supply chain where each buyer faces a price-sensitive demand. The manufacturer produces the item at a finite rate and ships to the buyers in multiple shipments of equal sized sub-batches. These shipments are made using third-party logistics support. The transportation cost is assumed to depend upon vehicle type and on the buyer to which shipment is made. The problem of determining right inventory policies to maximise the overall supply chain profit is formulated as a mixed-integer nonlinear programming (MINLP) model and a meta-heuristic based on particle swarm optimisation (PSO) is also proposed. The sensitivity analyses carried out shows the impact of the change in vehicle capacities, setup cost, unit cost, production rate and holding rate of the manufacturer on inventory policy and its related costs. The sensitivity analysis will provide a practical guide to the managers in reacting to a certain change in some parameter values, such as in the eventuality of increase in the setup cost for taking production of a larger lot size in one setup and supply the same to the buyers in more number of sub-batches without changing the sub-batch size.
期刊介绍:
IJBPSCM covers original, high-quality and cutting-edge research on all aspects of supply chain modelling, aiming at bridging the gap between theory and practice with applications analysing the real situation to improve business performance. Topics covered include Business performance modelling, strategy Vendor/supplier selection, supplier development, purchasing management Supply chain management (SCM), green supply chain modelling Reverse logistics, closed loop/knowledge-based supply chains, 3PL/4PL Sustainable/quality based/agile/leagile/intelligent SCM Supply chain performance/optimisation/risk/decision making/support systems AI, information sharing in SCM, systems approach to SCM Coordinated/global/flexible SCM, risk mitigation strategies Stochastic supply chain games IT-enabled SCM, fuzzy modelling, data mining Supply chain network management, modelling/simulation, implementation Training/education, information security, RFID Supply chain analysis, transportation decisions, vehicle routing, bullwhip effect Logistics in disaster management Cross-country comparison.