Logistics Routing Rules for Multi-Criteria Driver Selection
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Solution Overview
Problem
Historical logistical optimization methods for transporting goods are often ad hoc and based on incomplete information, leading to sub-optimal solutions, and there is a need for more efficient systems that consider multiple criteria such as cost, speed, and package characteristics.
Innovation Solution
A logistical management system that includes an interface and processors to receive shipping requests, query data stores for itineraries, validate against rules, and select itineraries based on criteria like cost, distance, and risk, while considering package characteristics and eliminating incompatible segments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If ad hoc optimization methods are used, then user input and time requirements are reduced, but the quality of optimization deteriorates leading to sub-optimal solutions
Solution Approach 1:
The system automatically queries multiple data stores, validates itineraries against rules, and selects optimal routes without requiring significant user input. The system serves itself by autonomously gathering transportation data, performing validations, and making selection decisions based on predefined criteria.
Solution Approach 2:
The system uses feedback loops where itinerary selections are validated against predefined rules, and results are used to refine future selections. The system continuously improves optimization quality by learning from validation outcomes and adjusting its selection criteria accordingly.
2Reliability
If comprehensive information is gathered for optimization, then solution quality improves, but information processing time and system complexity increase
Solution Approach 1:
The system segments the optimization process into distinct modules: data collection from multiple specialized data stores, validation against rules, scoring based on criteria, and selection. Each module handles a specific aspect of the problem, reducing overall system complexity while maintaining comprehensive information gathering.
Solution Approach 2:
The system introduces intermediary components such as validation rules and scoring mechanisms that mediate between raw data and final decisions. These intermediaries structure the information flow and simplify the decision-making process by breaking down complex evaluations into manageable steps.
3Reliability
If multiple itinerary options are evaluated, then selection quality improves, but processing time increases
Solution Approach 1:
The system evaluates multiple itinerary options using partial evaluation methods, assessing only the most critical criteria first. By performing excessive action in gathering options but selective action in evaluation, the system maintains high selection quality while managing processing time through prioritized assessment.
Solution Approach 2:
The system changes evaluation parameters dynamically, adjusting the weight and importance of different criteria based on the specific shipment requirements. This allows efficient processing by focusing computational resources on the most relevant parameters for each decision context.
Data Source
AI summary
Systems and methods of performing logistical management are provided. The logistical management system may receive a request to ship a package from an electronic device associated with a user. The request can include an initial location and information relating to one or more characteristics of the package. In response to receiving the request, electronic data store may be queried to determine a set of possible itineraries for the package. The set of possible itineraries can then be validated against a set of pre-determined rules to produce a subset of itineraries. One of the subset of itineraries can then be chosen.