Some NP-complete problems in quadratic and nonlinear programming
Mathematical Programming: Series A and B
Stock Positioning and Performance Estimation in Serial Production-Transportation Systems
Manufacturing & Service Operations Management
Optimizing Strategic Safety Stock Placement in Supply Chains
Manufacturing & Service Operations Management
Correspondence: Erratum: Optimizing Strategic Safety Stock Placement in Supply Chains
Manufacturing & Service Operations Management
Inventory placement in acyclic supply chain networks
Operations Research Letters
New model and heuristics for safety stock placement in general acyclic supply chain networks
Computers and Operations Research
The hill detouring method for minimizing hinging hyperplanes functions
Computers and Operations Research
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The strategic safety stock placement problem is cast as a constrained separable concave minimization problem. Some network-specific algorithms do exist in the literature, but their utility is limited to small, sparse, and special supply chain network structures. In this paper, we present two efficient, easy-to-implement heuristic algorithms for placing strategic safety stock in general acyclic supply chain networks. The computational study demonstrates that the algorithms are able to obtain near-optimal (within 4% and 7% in average) solutions efficiently by solving a finite series of LPs (7%) or fixed-sized MIPs (4%). More importantly, their performance in terms of solution quality is nearly independent of the network size (for simulated instances with up to 100 stages). For general acyclic supply chain networks with 8000 nodes and 32,000 arcs, the LP-based algorithm typically finds solutions in under 5 minutes.