Abstract

Analytic models have been developed to solve the integrated production–distribution problems in supply chain management (SCM). As one of the major constraints in analytic models, operation time has mostly been known or disregarded. However, in the real systems, due to the various kinds of uncertain factors such as unexpected delays, queuing, breakdowns, operation time in the analytic model cannot correctly represent the dynamic behavior of the consumption of real operation time. To solve this problem, in this paper, we propose a hybrid approach combining the analytic and simulation model. Operation time in the analytic model is considered as a dynamic factor and adjusted by the results from independently developed simulation model, which includes general production–distribution characteristics. We obtain the more realistically optimal production–distribution plans for the integrated supply chain system reflecting stochastic natures by performing the iterative hybrid analytic–simulation procedure.

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