Heuristics for base-stock levels in multi-echelon distribution networks

Y. Rong, Z. Atan, L.V. Snyder

Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelAcademicpeer review

Uittreksel

We study inventory optimization for locally controlled, continuous-review distribution systems with stochastic customer demands. Each node follows a base-stock policy and a first-come, first-served allocation policy. We develop two heuristics, the recursive optimization (RO) heuristic and the decomposition-aggregation (DA) heuristic, to approximate the optimal base-stock levels of all the locations in the system. The RO heuristic applies a bottom-up approach that sequentially solves single-variable, convex problems for each location. The DA heuristic decomposes the distribution system into multiple serial systems, solves for the base-stock levels of these systems using the newsvendor heuristic of Shang and Song (2003), and then aggregates the serial systems back into the distribution system using a procedure we call “backorder matching.” A key advantage of the DA heuristic is that it does not require any evaluation of the cost function (a computationally costly operation that requires numerical convolution). We show that, for both RO and DA, changing some of the parameters, such as leadtime, unit backordering cost, and demand rate, of a location has an impact only on its own local base-stock level and its upstream locations’ local base-stock levels. An extensive numerical study shows that both heuristics perform well, with the RO heuristic providing more accurate results and the DA heuristic consuming less computation time. We show that both RO and DA are asymptotically optimal along multiple dimensions for two-echelon distribution systems. Finally, we show that, with minor changes, both RO and DA are applicable to the balanced allocation policy.
TaalEngels
Pagina's1760-1777
Aantal pagina's18
TijdschriftProduction and Operations Management
Volume26
Nummer van het tijdschrift9
DOI's
StatusGepubliceerd - 2017

Vingerafdruk

Electric power distribution
Agglomeration
Decomposition
Distribution network
Base stock
Multi-echelon
Heuristics
Convolution
Cost functions
Costs
Distribution system

Citeer dit

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abstract = "We study inventory optimization for locally controlled, continuous-review distribution systems with stochastic customer demands. Each node follows a base-stock policy and a first-come, first-served allocation policy. We develop two heuristics, the recursive optimization (RO) heuristic and the decomposition-aggregation (DA) heuristic, to approximate the optimal base-stock levels of all the locations in the system. The RO heuristic applies a bottom-up approach that sequentially solves single-variable, convex problems for each location. The DA heuristic decomposes the distribution system into multiple serial systems, solves for the base-stock levels of these systems using the newsvendor heuristic of Shang and Song (2003), and then aggregates the serial systems back into the distribution system using a procedure we call “backorder matching.” A key advantage of the DA heuristic is that it does not require any evaluation of the cost function (a computationally costly operation that requires numerical convolution). We show that, for both RO and DA, changing some of the parameters, such as leadtime, unit backordering cost, and demand rate, of a location has an impact only on its own local base-stock level and its upstream locations’ local base-stock levels. An extensive numerical study shows that both heuristics perform well, with the RO heuristic providing more accurate results and the DA heuristic consuming less computation time. We show that both RO and DA are asymptotically optimal along multiple dimensions for two-echelon distribution systems. Finally, we show that, with minor changes, both RO and DA are applicable to the balanced allocation policy.",
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Heuristics for base-stock levels in multi-echelon distribution networks. / Rong, Y.; Atan, Z.; Snyder, L.V.

In: Production and Operations Management, Vol. 26, Nr. 9, 2017, blz. 1760-1777.

Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelAcademicpeer review

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