Optimize a System Process | Dataford Interview Questions

Write a function that optimizes a given process within a system.

Model the process as a directed weighted graph and return the minimum-cost path from start to target using at most max_steps transitions. The input is a dictionary mapping each node to [next_node, cost] pairs. Return {"cost": number, "path": [nodes]}, or None when the target cannot be reached within the step limit.

Constraints

1 <= max_steps <= 1000
The graph contains at most 200 distinct nodes
Each transition is represented as [next_node, cost]
Transition costs are integers from -10^6 to 10^6
A node may have multiple outgoing transitions to the same destination
If multiple paths have the same minimum cost, returning any one is valid

Function Signature

def optimize_process(transitions, start, target, max_steps):

Your question is Optimize a System Process. Start with the requirements in the Question tab.

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Problem

Write a function that optimizes a given process within a system.

Constraints

1 <= max_steps <= 1000
The graph contains at most 200 distinct nodes
Each transition is represented as [next_node, cost]
Transition costs are integers from -10^6 to 10^6
A node may have multiple outgoing transitions to the same destination
If multiple paths have the same minimum cost, returning any one is valid

Function Signature

def optimize_process(transitions, start, target, max_steps):

Your question is Optimize a System Process. Start with the requirements in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.