Abstract
Many real-life problems in Supply Chain (SC) are over-constrained. Insufficient resources and time requirements result in an inability to all constraints. In some cases, their fulfillment requires very intensive computing. One way to overcome these difficulties is to soften some of the constraints. Natural environment for the modeling and solving of problems with constraints is constraint programming (CP), which is, however, ineffective on optimization problems and constraints containing a sum of many decision variables. This is when the idea to hybridize CP and other environments originated. The article presents the concept of modeling and solving soft constraints in SC problems using the hybrid approach. The illustrative example provided in the paper illustrates effectiveness and possibilities of this approach.
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Sitek, P. (2016). Modeling and Solving the Soft Constraints for Supply Chain Problems Using the Hybrid Approach. In: Omatu, S., et al. Distributed Computing and Artificial Intelligence, 13th International Conference. Advances in Intelligent Systems and Computing, vol 474. Springer, Cham. https://doi.org/10.1007/978-3-319-40162-1_53
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DOI: https://doi.org/10.1007/978-3-319-40162-1_53
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