Fleet Delivery Routing With Energy Source and Vehicle Path Coupling
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Solution Overview
Problem
Existing delivery solutions for fleets of vehicles are often suboptimal as they do not consider the interaction between vehicle features and delivery paths, leading to inefficient delivery routes and resource utilization.
Innovation Solution
A method that determines a delivery solution by creating an environment graph and considering vehicle and operational constraints, including energy sources, to optimize the path for each vehicle while respecting constraints such as freight capacity and energy levels, using a master and slave problem approach to iteratively refine the solution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If independent optimization problems are solved for each vehicle without considering path-vehicle interaction, then the determination process is simplified, but the delivery solution becomes suboptimal
Solution Approach 1:
The patent segments the delivery problem into two interconnected optimization problems: a master problem that determines vehicle selection and energy source installation, and slave problems that determine delivery paths for each vehicle. This segmentation allows the system to consider vehicle-path interactions comprehensively while maintaining computational tractability through iterative solving.
2Ease of operation
If vehicle features are determined without considering delivery paths, then resource allocation is simplified, but the overall delivery solution becomes suboptimal
Solution Approach 1:
The master problem performs preliminary determination of vehicle features and energy source installations before the slave problems optimize delivery paths. This preliminary action establishes the resource allocation framework that constrains and guides subsequent path optimization, ensuring both aspects are coordinated for overall optimality.
Solution Approach 2:
The patent implements a feedback mechanism where the master problem uses path determination results from slave problems to refine vehicle feature selection and energy source installation decisions. This iterative feedback loop continues until convergence, ensuring that resource allocation and path planning are mutually optimized.
3Device complexity
If energy sources are not strategically considered in delivery routing, then the planning process is simpler, but vehicle energy constraints cannot be satisfied
Solution Approach 1:
The patent merges the energy source installation decision with the vehicle routing problem by including energy source location and vehicle energy consumption in the master and slave optimization problems. This unified approach ensures that energy constraints are satisfied while determining both the physical infrastructure needs and operational routes.
Data Source
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AI summary
A method for determining a delivery solution to pick-up and deliver packs by a fleet of vehicles in a predetermined environment, the delivery solution comprising a set of vehicle features, a set of energy source features, and a set of paths; the method comprising the following steps: - acquiring (110) an environment graph representing pick-up and delivery locations, a set of vehicle constraints and a set of operational constraints; - determining (120) at least one path for at least one slave problem, said slave problem comprising determining at least one path for a vehicle to pick-up and deliver packs while respecting the acquired vehicle constraints; and - determining (130) the delivery solution from a master problem and the determined path(s) for at least one slave problem, said master problem comprising optimizing a predetermined criterion while respecting the acquired operational constraints.