Publication:
An inventory-routing problem with stochastic demand and stock-out: a solution and risk analysis using simheuristics

Date

2019

Authors

Onggo, Bhakti Stephan
Juan Pérez, Ángel Alejandro
Panadero, Javier
Corlu, Canan Gunes

Director

Publisher

IEEE
Acceso abierto / Sarbide irekia
Contribución a congreso / Biltzarrerako ekarpena
Versión aceptada / Onetsi den bertsioa

Project identifier

European Commission/Horizon 2020 Framework Programme/731884openaire
European Commission/ERASMUS+/2018-1-ES01-KA103-049767openaire
Métricas Alternativas
OpenAlexGoogle Scholar
cited by count

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 an incorrect 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 simheuristics can produce a good result, and ignoring the uncertainty in the model input may lead to sub-optimal results.

Description

Keywords

Stochastic processes, Supply chains, Routing, Optimization, Uncertainty, Planning, Robustness

Department

Estadística, Informática y Matemáticas / Estatistika, Informatika eta Matematika

Faculty/School

Degree

Doctorate program

item.page.cita

B. S. Onggo, A. A. Juan, J. Panadero, C. G. Corlu and A. Agustin, 'An Inventory-Routing Problem with Stochastic Demand and Stock-Out: A Solution and Risk Analysis Using Simheuristics,' 2019 Winter Simulation Conference (WSC), National Harbor, MD, USA, 2019, pp. 1977-1988, doi: 10.1109/WSC40007.2019.9004897

item.page.rights

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