NDD Solve RequestSolve Request

Overview

The solve request houses the model and the action that should be performed on it. The NDD solve request supports an additional ExperimentalSolve type beyond the standard Optimise, Evaluate, and ReOptimise options.

Applicable models

• NDD ndd-cmibu6krtqja

Endpoint

• POST: https://api.icepack.ai/vehicle-router/solve/

Solve Request

Schema definition

message SolveRequest {
  optional Model model = 1;
  optional string modelID = 2;
  repeated TaskSequence routes = 3;
  optional SolveType solveType = 4 [default = Optimise];
}

Fields

model

The target model which should be solved (commonly specified). If not specified, the modelID field should be provided with a valid reference to an existing model.

modelID

A GUID which refers to a valid model which has recently been solved. Model data are stored in a hot cache for 24 hours after which they are deleted. If a modelID references a model which no longer exists, an error is returned.

routes

An optional list of task sequences specifying predefined routes. Used in conjunction with the modelID and the solve types Evaluate and ReOptimise. The task sequences specified here will override any task sequences defined within the model.

solveType

The solve type defining the target solver behaviour.

Notes

• Either a complete model or a valid modelID should be specified.
• Predefined routes are ignored for the Optimise solve type.
• The typical NDD workflow involves two API calls: first an Optimise request which returns a Pareto frontier of compact solutions, then an Evaluate request using the task sequences from a chosen frontier point to recover the full solution detail.

Solve Request Solve Type

Schema definition

enum SolveType {
  Optimise = 0;
  Evaluate = 1;
  ReOptimise = 2;
  ExperimentalSolve = 3;
}

Fields

Optimise

Issues an Optimise request which finds a set of solutions forming a Pareto frontier. The solution response will contain a collection of compact solutions representing the tradeoff between competing objectives. Provided task sequences are ignored.

Evaluate

Issues an Evaluate request which evaluates the provided task sequences against the model. Returns a single solution instance with full route detail, stops, and dimensional evaluations. This is typically used to recover the detail of a point selected from the Pareto frontier.

ReOptimise

Issues a ReOptimise request which uses the provided task sequences as a starting solution and continues to optimise. If the provided solution is feasible, the result is guaranteed to be equal or better in cost.

ExperimentalSolve

Uses an experimental decomposition code-path. This may provide improved performance on certain problem structures but behaviour may change between API versions.