Robust inventory management in multi-stage inventory networks with demand shocks
AssigneeInternational Business Machines Corporation
InventorsMarkus R. Ettl, Marco Laumanns, Marek Petrik, Rajesh Kumar Ravi, Stefan Woerner
Life of this patent
Estimating the term…
Abstract
Robust inventory management for a supply chain network with multiple nodes may include generating a time-phased inventory deployment plan based on extreme samples and dynamic supply chain structure. The extreme samples of demand and supply chain scenarios, and dynamic supply chain structure including one or more resource constraints associated with one or more nodes in the supply chain network may be received from a user.
Claims21
A method for inventory management for a supply chain network with multiple nodes, comprising:
- receiving extreme samples of demand and supply chain scenarios;
- receiving dynamic supply chain structure including one or more resource constraints associated with one or more nodes in the supply chain network;
- generating, by a processor, a time-phased inventory deployment plan based on said extreme samples and said dynamic supply chain structure;
- and
- outputting said time-phased inventory deployment plan.
A computer readable storage medium storing a program of instructions executable by a machine to perform a method of inventory management for a supply chain network with multiple nodes, comprising:
- receiving extreme samples of demand and supply chain scenarios;
- receiving dynamic supply chain structure including one or more resource constraints associated with one or more nodes in the supply chain network;
- generating, by a processor, a time-phased inventory deployment plan based on said extreme samples and said dynamic supply chain structure;
- and
- outputting said time-phased inventory deployment plan.
A system for inventory management for a supply chain network with multiple nodes, comprising:
- a processor operable to receive extreme samples of demand and supply chain scenarios, and dynamic supply chain structure including one or more resource constraints associated with one or more nodes in the supply chain network, the processor further operable to generate a time-phased inventory deployment plan based on said extreme samples and said dynamic supply chain structure, and output said time-phased inventory deployment plan.
Dependencies are inferred from the claim text.