AI-generated Key Takeaways
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The Operations Research API enables users to solve complex optimization problems, such as linear programming and constraint programming, through an API.
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It offers solutions for specific operational research problems like shipping network design, shift generation, and shift scheduling.
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Users can interact with the API using the service name
optimization.googleapis.com
to create client stubs for making requests. -
The API provides methods to manage long-running operations, including cancellation, deletion, retrieval of status, listing operations, and waiting for completion.
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Specific methods like
DesignShippingNetwork
,SolveMathOptModel
,SolveShiftGeneration
, andSolveShiftScheduling
address distinct optimization challenges.
The Operations Research API aims to solve high-level operations research problems using linear programming, mixed integer programming, constraint programming and more. It provides optimization solutions for specific problems to external users through an API call.
Service: optimization.googleapis.com
The Service name optimization.googleapis.com
is needed to create RPC client stubs.
google.longrunning.Operations
Methods | |
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Starts asynchronous cancellation on a long-running operation. |
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Deletes a long-running operation. |
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Gets the latest state of a long-running operation. |
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Lists operations that match the specified filter in the request. |
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Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. |
google.research.optimization.v1.Optimization
Methods | |
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Solves the liner shipping network design and scheduling problem (LSNDSP) from the given DesignShippingNetworkRequest . |
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Solves the input model and returns the result at once. |
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Solves a shift generation problem from the given SolveShiftGenerationRequest by generating shifts from given shift templates in order to cover the employee demand. |
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Solves a fixed shift scheduling problem from the given SolveShiftSchedulingRequest by assigning employees to shifts such that employees' scheduling preferences are maximized and scheduling constraint violations are minimized. |