Iteration-Aware Work Item Scheduling for Agile Teams
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing project scheduling systems face challenges in accurately scheduling work items across teams working in agile methodologies, particularly due to the complexities introduced by iterations and resource availability, leading to suboptimal scheduling that does not align with the start of team iterations, resulting in undesirable span across multiple iterations.
Innovation Solution
The implementation of an iteration-aware scheduling process that introduces an additional time abstraction layer for each team, prioritizing the minimization of iteration violations and using a mixed integer linear program to optimize the scheduling of work items, while also considering resource constraints and dependencies, to ensure work items are scheduled to start at the beginning of the next team iteration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional project scheduling systems are used to schedule work items across teams working in agile methodologies, then the scheduling can be performed without considering team iteration structures, but the work items will span across multiple iterations causing suboptimal scheduling that does not align with team iterations
Solution Approach 1:
The patent segments the scheduling problem by introducing an additional time abstraction layer that represents team iterations. This segmentation allows the system to separately model and optimize for iteration boundaries, enabling work items to be scheduled within specific iteration contexts rather than spanning multiple iterations indiscriminately.
Solution Approach 2:
The patent adds a new dimension to the scheduling model by introducing iteration-level time abstraction alongside the traditional resource and task dimensions. This additional temporal dimension allows the optimization to simultaneously consider resource availability, task dependencies, and iteration boundaries, resolving the contradiction between adaptability and complexity.
2Measurement precision
If the scheduling problem considers all constraints including resource availability, capacity, skills, interdependencies, and deadlines, then the scheduling accuracy improves, but the solution space becomes excessively large making optimization difficult
Solution Approach 1:
The patent segments the large solution space by introducing iteration boundaries as natural partitioning points. This segmentation divides the overall scheduling problem into smaller sub-problems constrained within each iteration, making the optimization more tractable while maintaining accuracy by considering all constraints within each segment.
Solution Approach 2:
The patent performs preliminary actions by pre-defining iteration structures and constraints before executing the optimization. By establishing the iteration time abstraction layer and associated constraints in advance, the system reduces the effective solution space that needs to be explored during optimization, while still achieving accurate scheduling that satisfies all constraints.
Data Source
AI summary
Disclosed herein is a computer implemented scheduling method comprising: accessing project data from computer readable storage media. The project data comprises work item data defining a plurality of work items to be scheduled, and release data defining one or more releases into which one or more of the plurality of work items are to be scheduled. The method comprises processing, using a computer processor, the project data to schedule strictly assigned work items by identifying strictly assigned work items, a strictly assigned work item having a particular release into which the strictly assigned work item needs to be scheduled; and for each strictly assigned work item identified, scheduling the strictly assigned work item into the release specified for that strictly assigned work item.