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Solving an inventory-routing problem with stochastic demand using simheuristic

Solving an inventory-routing problem with stochastic demand using simheuristic
Solving an inventory-routing problem with stochastic demand using simheuristic
Supply chain operations have become more complex. Hence, in order to optimise supply chain operations, we often need to simplify the optimisation problem in such a way that it can be solved efficiently using either exact methods or metaheuristics. One common simplification is to assume all model inputs are deterministic. However, for some management decisions, considering the uncertainty in model inputs (e.g. demands, travel times, processing times) is essential. Otherwise, the results may be misleading and might lead to a wrong decision. This paper considers an example of a complex supply chain operation that can be viewed as an Inventory-Routing Problem with stochastic demands. We demonstrate how a simheuristic framework can be employed to solve the problem. Further, we illustrate the risks of not considering input uncertainty. The results show that simheuristic can produce a good result and ignoring the uncertainty in the model input may lead to sub-optimal results.
ACM
Onggo, Bhakti Stephan
8e9a2ea5-140a-44c0-9c17-e9cf93662f80
Juan, Angel A.
727ca41c-da96-40ea-8ea9-b27ab03aee49
Panadero, Javier
2dca23fd-f7e1-491a-a9c0-a72f901c76e1
Corlu, Canan Gunes
ecb0f999-21d4-41e2-8cab-58a33706f09e
Agustin, Alba
c0d53fae-ae54-4cf6-aafd-6931b3afe7fa
Onggo, Bhakti Stephan
8e9a2ea5-140a-44c0-9c17-e9cf93662f80
Juan, Angel A.
727ca41c-da96-40ea-8ea9-b27ab03aee49
Panadero, Javier
2dca23fd-f7e1-491a-a9c0-a72f901c76e1
Corlu, Canan Gunes
ecb0f999-21d4-41e2-8cab-58a33706f09e
Agustin, Alba
c0d53fae-ae54-4cf6-aafd-6931b3afe7fa

Onggo, Bhakti Stephan, Juan, Angel A., Panadero, Javier, Corlu, Canan Gunes and Agustin, Alba (2019) Solving an inventory-routing problem with stochastic demand using simheuristic. In Proceedings of the 2019 Winter Simulation Conference. ACM. 12 pp . (In Press)

Record type: Conference or Workshop Item (Paper)

Abstract

Supply chain operations have become more complex. Hence, in order to optimise supply chain operations, we often need to simplify the optimisation problem in such a way that it can be solved efficiently using either exact methods or metaheuristics. One common simplification is to assume all model inputs are deterministic. However, for some management decisions, considering the uncertainty in model inputs (e.g. demands, travel times, processing times) is essential. Otherwise, the results may be misleading and might lead to a wrong decision. This paper considers an example of a complex supply chain operation that can be viewed as an Inventory-Routing Problem with stochastic demands. We demonstrate how a simheuristic framework can be employed to solve the problem. Further, we illustrate the risks of not considering input uncertainty. The results show that simheuristic can produce a good result and ignoring the uncertainty in the model input may lead to sub-optimal results.

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Accepted/In Press date: 2 June 2019

Identifiers

Local EPrints ID: 433680
URI: https://eprints.soton.ac.uk/id/eprint/433680
PURE UUID: 89ddc9ed-5db8-4a98-a0fc-7102dbebe3fc
ORCID for Bhakti Stephan Onggo: ORCID iD orcid.org/0000-0001-5899-304X

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Date deposited: 30 Aug 2019 16:30
Last modified: 31 Aug 2019 00:21

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