Fleet Resource Allocation Heuristics for Plan Change Deviations

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Solution Overview

Problem

Existing resource management systems for large vehicle fleets and facilities are computationally intensive and inefficient, struggling to handle deviations from planned usage and requiring significant computing power, especially when resources can only be used for a single requirement at a time.

Innovation Solution

A heuristic method for resource management that divides resources into classes, assigns them to usage requests with buffer periods, and optimizes distribution using shift steps based on weighted parameters, allowing efficient allocation with minimal computing power.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If existing resource management systems are used for large vehicle fleets, then resource allocation can be achieved, but considerable computing power and time are required

Engineering Contradiction:
Improveresource allocation efficiencyVSAvoidcomputing power requirement
Core Design Contradiction:
ProductivityVSUse of energy by stationary object

Solution Approach 1:

The patent segments the resource management problem by dividing resources into resource classes (e.g., vehicle types) and processing usage requests in a structured sequence. This segmentation allows the system to handle large fleets by breaking down the complex allocation problem into manageable class-based units, reducing overall computational requirements while maintaining allocation effectiveness

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent changes the parameter representation by using optimization parameters based on weights of resource-to-request assignments rather than exhaustive evaluation. By transforming the problem into a weighted optimization framework with buffer periods, the system achieves efficient resource allocation with reduced computational effort compared to traditional approaches

Inventive Principle:
Principle #35Parameter changes

2Reliability

If buffer periods are added to accommodate usage deviations, then reliability of resource allocation is improved, but complexity of the scheduling system increases

Engineering Contradiction:
Improveallocation reliabilityVSAvoidscheduling system complexity
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The patent applies preliminary action by pre-defining buffer periods as part of the usage request structure before actual resource allocation occurs. These buffer periods are incorporated into the optimization parameters in advance, allowing the system to preemptively handle potential usage deviations without requiring complex real-time adjustments, thus improving reliability while maintaining manageable system complexity

Inventive Principle:
Principle #10Preliminary action

3Measurement precision

If optimization parameters with weights are used to determine target distribution, then resource distribution accuracy is improved, but computational effort increases

Engineering Contradiction:
Improvedistribution accuracyVSAvoidcomputational effort
Core Design Contradiction:
Measurement precisionVSUse of energy by moving object

Solution Approach 1:

The patent transforms the resource allocation problem into a weighted optimization parameter framework where accuracy is achieved through mathematical weighting rather than exhaustive computation. By changing the approach from detailed micro-optimization to macro-level weighted parameter optimization, the system achieves accurate target distribution with reduced computational effort

Inventive Principle:
Principle #35Parameter changes

Solution Approach 2:

The patent applies partial action by implementing a limited number of shift steps in the optimization process rather than exhaustive optimization. This partial optimization approach achieves sufficient distribution accuracy for practical purposes while significantly reducing computational effort compared to complete optimization, balancing accuracy requirements with computational constraints

Inventive Principle:
Principle #16Partial or excessive action

Data Source

PatentEP3702981B1Resource management at plan change
Publication Date: 2026.04.01 SIEMENS AG
  • EP3702981B1 patent drawingFigure 1
  • EP3702981B1 patent drawingFigure 2~3
  • EP3702981B1 patent drawingFigure 4

AI summary

The invention relates to approaches for resource management, particularly for fleet management of vehicles, but also for other applications. The aim is to allocate resources (R1,...,Rn) as optimally as possible to fulfill usage requests (RQ1,..., RQq). According to the invention, starting from an initial solution (initial allocation), shifts that result in optimization are sought for each resource. As soon as an optimizing shift is found, the process moves to the next resource. The invention offers a heuristic approach that leads to results faster than a MILP approach and is intended to replace such an approach. Buffer periods are used in the evaluation to accommodate possible deviations from requested activity times.