Route Planning With Benefit Accumulation
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Solution Overview
Problem
Existing route planning systems do not effectively maximize benefit while adhering to a limited resource constraint, such as time, in determining optimal routes for traversing networks like transportation systems.
Innovation Solution
A method and system that define a routing graph with cost and benefit values for each element, perform a route planning procedure to maintain candidate routes, update accumulated costs and benefits, and select the route with the highest benefit without exceeding a cost budget, incorporating modifiers for previous visits and time-dependent benefits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If known route planning techniques minimize travel time or distance, then the route efficiency is improved, but the system cannot maximize benefit accumulation while adhering to resource constraints
Solution Approach 1:
The route planning problem is segmented into discrete graph elements (nodes and edges) with individual cost and benefit attributes. This segmentation allows the system to evaluate and accumulate benefits at each element level while maintaining overall route optimization, resolving the contradiction by making complex benefit accumulation tractable through structured decomposition
Solution Approach 2:
The routing system dynamically adjusts route selection based on accumulated benefits and remaining cost budget at each step. Rather than static optimization, the system adapts its path choices to maximize benefit accumulation while respecting resource constraints, enabling productivity improvement without proportional complexity increase
2Productivity
If the route planning procedure evaluates multiple candidate routes with accumulated costs and benefits, then the benefit maximization is improved, but the computational complexity increases
Solution Approach 1:
The system pre-calculates minimum return costs from each graph element to the ending location before executing the route planning procedure. This preliminary action enables efficient pruning of candidate routes during execution, as routes exceeding the cost budget can be eliminated immediately without full exploration, thus maximizing benefit while controlling computation time
Solution Approach 2:
The system evaluates multiple candidate routes beyond what simple shortest-path algorithms would consider, maintaining a set of promising candidates with accumulated benefits tracked. This partial exploration of the solution space allows benefit maximization while avoiding exhaustive search through all possible routes, balancing computation time with optimization quality
3Productivity
If the system eliminates candidate routes based on cost budget constraints, then the resource efficiency is improved, but the solution space is reduced
Solution Approach 1:
The system changes the evaluation parameters from simple cost minimization to dual consideration of accumulated benefit and cost budget. By introducing benefit as a primary optimization criterion alongside cost constraints, the system maintains route option flexibility while improving resource efficiency, as routes are eliminated based on combined benefit-cost-ratio rather than cost alone
Data Source
AI summary
A method includes performing multiple steps of a route planning procedure based on starting and ending locations. Each of multiple steps of the route planning procedure includes maintaining information that identifies candidate routes by which graph elements can be reached or occupied during a current step, updating an accumulated cost for each of the candidate routes, updating an accumulated benefit for each of the candidate routes, determining a minimum return cost to the ending location for each candidate route, and eliminating candidate routes that cannot reach the ending location within a cost budget. A highest-benefit route from the candidate routes is selected.