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- W3003425327 abstract "Abstract In the context of a supply chain for the animal‐feed industry, this paper focuses on optimizing replenishment strategies for silos in multiple farms. Assuming that a supply chain is essentially a value chain, our work aims at narrowing this chasm and putting analytics into practice by identifying and quantifying improvements on specific stages of an animal‐feed supply chain. Motivated by a real‐life case, the paper analyses a rich multi‐period inventory routing problem with homogeneous fleet, stochastic demands, and maximum route length. After describing the problem and reviewing the related literature, we introduce a reactive heuristic, which is then extended into a biased‐randomized simheuristic. Our reactive approach is validated and tested using a series of adapted instances to explore the gap between the solutions it provides and the ones generated by existing nonreactive approaches." @default.
- W3003425327 created "2020-02-07" @default.
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- W3003425327 date "2020-01-30" @default.
- W3003425327 modified "2023-09-26" @default.
- W3003425327 title "A reactive simheuristic using online data for a real‐life inventory routing problem with stochastic demands" @default.
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- W3003425327 doi "https://doi.org/10.1111/itor.12776" @default.
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