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Evaluating approximate solution models for the stochastic periodic inventory routing problem

Ehsan Yadollahi (UGent) , El-Houssaine Aghezzaf (UGent) , Joris Walraevens (UGent) , Birger Raa (UGent) and Dieter Claeys (UGent)
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Abstract
This paper considers the stochastic periodic inventory routing problem (SPIRP) when the variability of the retailers' demands are vague. Two solution approaches to minimize transportation and inventory costs, while guaranteeing that each retailer's demand is satisfied up to a pre-set service level, are investigated and compared. The first approach uses a safety stock-based deterministic model, where extra amounts of stock are kept at the retailers on top of the cycle inventory to cope with their demands' variability. The second approach uses the sample average approximation (SAA). The key question that this paper addresses is how to set the parameters of the safety-stock based model so that it can generate good quality solutions (compared to the SAA benchmark) while it is also effective in terms of computation time and estimated costs. To address this question we compare the performance of two versions of the safety-stock based approach and of the benchmark SAA, for a set of appropriately generated instances. We develop an experimental design to generate relevant instances, use simulation to evaluate the behaviour of the models in different cases, and verify their effects on a selected set of performance indicators.
Keywords
Control and Systems Engineering, Hardware and Architecture, Industrial and Manufacturing Engineering, Software, Safety stock, Sample average approximation, Stochastic demands, Inventory routing problem, Planning horizon, SUPPLY-CHAIN, LEAD-TIME, SERVICE LEVEL, HEURISTICS, ALGORITHM, INSIGHTS

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MLA
Yadollahi, Ehsan, et al. “Evaluating Approximate Solution Models for the Stochastic Periodic Inventory Routing Problem.” JOURNAL OF MANUFACTURING SYSTEMS, vol. 50, 2019, pp. 25–35.
APA
Yadollahi, E., Aghezzaf, E.-H., Walraevens, J., Raa, B., & Claeys, D. (2019). Evaluating approximate solution models for the stochastic periodic inventory routing problem. JOURNAL OF MANUFACTURING SYSTEMS, 50, 25–35.
Chicago author-date
Yadollahi, Ehsan, El-Houssaine Aghezzaf, Joris Walraevens, Birger Raa, and Dieter Claeys. 2019. “Evaluating Approximate Solution Models for the Stochastic Periodic Inventory Routing Problem.” JOURNAL OF MANUFACTURING SYSTEMS 50: 25–35.
Chicago author-date (all authors)
Yadollahi, Ehsan, El-Houssaine Aghezzaf, Joris Walraevens, Birger Raa, and Dieter Claeys. 2019. “Evaluating Approximate Solution Models for the Stochastic Periodic Inventory Routing Problem.” JOURNAL OF MANUFACTURING SYSTEMS 50: 25–35.
Vancouver
1.
Yadollahi E, Aghezzaf E-H, Walraevens J, Raa B, Claeys D. Evaluating approximate solution models for the stochastic periodic inventory routing problem. JOURNAL OF MANUFACTURING SYSTEMS. 2019;50:25–35.
IEEE
[1]
E. Yadollahi, E.-H. Aghezzaf, J. Walraevens, B. Raa, and D. Claeys, “Evaluating approximate solution models for the stochastic periodic inventory routing problem,” JOURNAL OF MANUFACTURING SYSTEMS, vol. 50, pp. 25–35, 2019.
@article{8583186,
  abstract     = {This paper considers the stochastic periodic inventory routing problem (SPIRP) when the variability of the retailers' demands are vague. Two solution approaches to minimize transportation and inventory costs, while guaranteeing that each retailer's demand is satisfied up to a pre-set service level, are investigated and compared. The first approach uses a safety stock-based deterministic model, where extra amounts of stock are kept at the retailers on top of the cycle inventory to cope with their demands' variability. The second approach uses the sample average approximation (SAA). The key question that this paper addresses is how to set the parameters of the safety-stock based model so that it can generate good quality solutions (compared to the SAA benchmark) while it is also effective in terms of computation time and estimated costs. To address this question we compare the performance of two versions of the safety-stock based approach and of the benchmark SAA, for a set of appropriately generated instances. We develop an experimental design to generate relevant instances, use simulation to evaluate the behaviour of the models in different cases, and verify their effects on a selected set of performance indicators.},
  author       = {Yadollahi, Ehsan and Aghezzaf, El-Houssaine and Walraevens, Joris and Raa, Birger and Claeys, Dieter},
  issn         = {0278-6125},
  journal      = {JOURNAL OF MANUFACTURING SYSTEMS},
  keywords     = {Control and Systems Engineering,Hardware and Architecture,Industrial and Manufacturing Engineering,Software,Safety stock,Sample average approximation,Stochastic demands,Inventory routing problem,Planning horizon,SUPPLY-CHAIN,LEAD-TIME,SERVICE LEVEL,HEURISTICS,ALGORITHM,INSIGHTS},
  language     = {eng},
  pages        = {25--35},
  title        = {Evaluating approximate solution models for the stochastic periodic inventory routing problem},
  url          = {http://dx.doi.org/10.1016/j.jmsy.2018.11.001},
  volume       = {50},
  year         = {2019},
}

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