Integrated multi-site production-distribution planning in supply chain by hybrid modelling

• Published in: International journal of production research Vol. 48; no. 14; pp. 4043 - 4069
• Main Authors: Safaei, A.S., Moattar Husseini, S.M., Z.-Farahani, R., Jolai, F., Ghodsypour, S.H.
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis Group 01.01.2010; Taylor & Francis; Taylor & Francis LLC
• Subjects: Applied sciences; Channels; Costs; Distribution planning; Dynamical systems; Dynamics; Exact sciences and technology; hybrid model; integrated production-distribution planning; Inventory control, production control. Distribution; Lieferkette; Logistics; Mathematical analysis; Mathematical models; Mehrproduktfertigung; multi-site; Operational research and scientific management; Operational research. Management science; Optimization; Production planning; Queuing theory; Queuing theory. Traffic theory; Reliability theory. Replacement problems; Simulation; Studies; Supply chain management; Supply chains; multi-site; Costs; Integration; simulation; Multiple production; Modeling; Production management; Break up time; Production planning; supply chain management; Breakdown; Inventory control; Hybrid model; Dynamic model; integrated production-distribution planning; Queue; Logistics
• ISSN: 0020-7543; 1366-588X
• DOI: 10.1080/00207540902791777

Allocation of production volumes among multiple manufacturing sites and distribution of products among distribution channels involves many quantitative and qualitative variables and constraints. An integrated multi-product, multi-period, multi-site production-distribution planning subject to the production and distribution constraints, distribution system and local customers demand is considered in this paper. To do this, we took advantage of a hybrid mathematical-simulation model to solve the proposed problem. A mathematical model has been developed to solve the problem, aiming to decrease the costs of set up, production, inventory, distribution and transportation. Because of stochastic factors such as unexpected delays, queuing and machine failure, operation time provided by mathematical model cannot reflect dynamic characteristic of real-world systems and optimal solution of mathematical model is not acceptable in practice. Therefore, we took advantage of a hybrid mathematical-simulation approach to explore the behaviour of the real-world system. Through the computational experiments, we demonstrated that the number of iterations to converge hybrid procedure would lessen when we consider the production-distribution problem in an integrated manner. Also, supply chain overall costs will be reduced through the integration of production and distribution problems. Finally, the solution is a realistically optimal solution for the proposed integrated production-distribution planning problem.