Optimizing location, routing and inventory decisions in an integrated supply chain network under uncertainty
Authors
Abstract:
This study extends a mathematical model that integrates the location, allocation, inventory replenishment and routing decisions simultaneously. To cope with inherent uncertainty of parameters, we implement a continuous-time Markov process and derive the performance measures of the system. Using the obtained results, the problem is formulated as a mixed integer nonlinear programing model (MINLP), where the total costs of location, transportation and inventory are minimized. In addition,we develop a simulated annealing(SA)-based meta-heuristic algorithm to tackle the computational complexity of the problem. Finally, severalcomputational experimentsare provided to assess effectiveness of the proposed algorithm and the model.
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full textMy Resources
Journal title
volume 9 issue 4
pages 93- 111
publication date 2017-03-16
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