Integrated supply, production and distribution scheduling under disruption risks
This paper presents a bi-objective stochastic mixed integer programming approach for a joint selection of suppliers and scheduling of production and distribution in a multi-echelon supply chain subject to local and regional disruption risks. Two conflicting problem objectives are minimization of cos...
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| Vydané v: | Omega (Oxford) Ročník 62; s. 131 - 144 |
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| Médium: | Journal Article |
| Jazyk: | English |
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Oxford
Elsevier Ltd
01.07.2016
Pergamon Press Inc |
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| ISSN: | 0305-0483, 1873-5274 |
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| Abstract | This paper presents a bi-objective stochastic mixed integer programming approach for a joint selection of suppliers and scheduling of production and distribution in a multi-echelon supply chain subject to local and regional disruption risks. Two conflicting problem objectives are minimization of cost and maximization of service level. The three shipping methods are considered for distribution of products: batch shipping with a single shipment of different customer orders, batch shipping with multiple shipments of different customer orders and individual shipping of each customer order immediately after its completion. The stochastic combinatorial optimization problem is formulated as a time-indexed mixed integer program with the weighted-sum aggregation of the two objective functions. The supply portfolio is determined by binary selection and fractional allocation variables while time-indexed assignment variables determine the production and distribution schedules. The problem formulation incorporates supply–production, production–distribution and supply–distribution coordinating constraints to efficiently coordinate supply, production and distribution schedules. Numerical examples modelled after an electronics supply chain and computational results are presented and some managerial insights are reported. The findings indicate that for all shipping methods, the service-oriented supply portfolio is more diversified than the cost-oriented portfolio and the more cost-oriented decision-making, the more delayed the expected supply, production and distribution schedules.
•Joint supply, production and distribution scheduling under disruptions is studied.•Cost and service level for batch or individual shipping are optimized by MIP.•Supply–production, production–distribution and supply–distribution coordinating constraints are developed.•The more service-oriented decision-making, the more diversified supply portfolio.•The more cost-oriented decision-making, the more delayed expected schedules. |
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| AbstractList | This paper presents a bi-objective stochastic mixed integer programming approach for a joint selection of suppliers and scheduling of production and distribution in a multi-echelon supply chain subject to local and regional disruption risks. Two conflicting problem objectives are minimization of cost and maximization of service level. The three shipping methods are considered for distribution of products: batch shipping with a single shipment of different customer orders, batch shipping with multiple shipments of different customer orders and individual shipping of each customer order immediately after its completion. The stochastic combinatorial optimization problem is formulated as a time-indexed mixed integer program with the weighted-sum aggregation of the two objective functions. The supply portfolio is determined by binary selection and fractional allocation variables while time-indexed assignment variables determine the production and distribution schedules. The problem formulation incorporates supply-production, production-distribution and supply-distribution coordinating constraints to efficiently coordinate supply, production and distribution schedules. Numerical examples modelled after an electronics supply chain and computational results are presented and some managerial insights are reported. The findings indicate that for all shipping methods, the service-oriented supply portfolio is more diversified than the cost-oriented portfolio and the more cost-oriented decision-making, the more delayed the expected supply, production and distribution schedules. This paper presents a bi-objective stochastic mixed integer programming approach for a joint selection of suppliers and scheduling of production and distribution in a multi-echelon supply chain subject to local and regional disruption risks. Two conflicting problem objectives are minimization of cost and maximization of service level. The three shipping methods are considered for distribution of products: batch shipping with a single shipment of different customer orders, batch shipping with multiple shipments of different customer orders and individual shipping of each customer order immediately after its completion. The stochastic combinatorial optimization problem is formulated as a time-indexed mixed integer program with the weighted-sum aggregation of the two objective functions. The supply portfolio is determined by binary selection and fractional allocation variables while time-indexed assignment variables determine the production and distribution schedules. The problem formulation incorporates supply–production, production–distribution and supply–distribution coordinating constraints to efficiently coordinate supply, production and distribution schedules. Numerical examples modelled after an electronics supply chain and computational results are presented and some managerial insights are reported. The findings indicate that for all shipping methods, the service-oriented supply portfolio is more diversified than the cost-oriented portfolio and the more cost-oriented decision-making, the more delayed the expected supply, production and distribution schedules. •Joint supply, production and distribution scheduling under disruptions is studied.•Cost and service level for batch or individual shipping are optimized by MIP.•Supply–production, production–distribution and supply–distribution coordinating constraints are developed.•The more service-oriented decision-making, the more diversified supply portfolio.•The more cost-oriented decision-making, the more delayed expected schedules. |
| Author | Sawik, Tadeusz |
| Author_xml | – sequence: 1 givenname: Tadeusz surname: Sawik fullname: Sawik, Tadeusz email: ghsawik@cyf-kr.edu.pl organization: AGH University of Science & Technology, Department of Operations Research and Information Technology, Al.Mickiewicza 30, 30-059 Kraków, Poland |
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| SubjectTerms | Distribution Integer programming Integrated scheduling Production scheduling Stochastic mixed integer programming Stochastic models Studies Supply chain management Supply chain risk management Supply chains Supply disruptions |
| Title | Integrated supply, production and distribution scheduling under disruption risks |
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