Title
Differentiated service inventory optimization using nested partitions and MOCBA
Abstract
In this paper, we consider a differentiated service inventory problem with multiple demand classes. Given that the demand from each class is stochastic, we apply a continuous review policy with dynamic threshold curves to provide differentiated services to the demand classes in order to optimize both the cost and the service level. The difficult features associated with the problem are the huge search space, the multi-objective problem which requires finding a non-dominated set of solutions and the accuracy in estimating the parameters. To address the above issues, we propose an approach that uses simulation to estimate the performance, nested partitions (NP) method to search for promising solutions, and multi-objective optimal computing budget allocation (MOCBA) algorithm to identify the non-dominated solutions and to efficiently allocate the simulation budget. Some computational experiments are carried out to test the effectiveness and performance of the proposed solution framework.
Year
DOI
Venue
2009
10.1016/j.cor.2008.04.006
Computers & OR
Keywords
DocType
Volume
non-dominated solution,non-dominated set,Differentiated service inventory optimization,differentiated service inventory problem,service level,multiple demand class,demand class,nested partition,multi-objective optimal computing budget,huge search space,differentiated service,multi-objective problem
Journal
36
Issue
ISSN
Citations 
5
Computers and Operations Research
12
PageRank 
References 
Authors
0.78
8
4
Name
Order
Citations
PageRank
Ek Peng Chew145944.07
Loo Hay Lee2115993.96
Suyan Teng31136.92
Choon Hwee Koh4201.44