Adaptive Decision Sequencing for Chaotic Event Management
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Solution Overview
Problem
Chaotic events, such as hurricanes or pandemics, pose challenges due to their rarity and unpredictability, leading to difficulties in planning and resource allocation, as well as overwhelming decision-makers with complex data, making it hard to make optimal decisions during such events.
Innovation Solution
A computer-implemented method using a mathematical optimization algorithm to select and sequence decisions based on a decision template, chaotic event information, and user profiles, along with a heuristic algorithm to eliminate unnecessary decisions, facilitating effective resource management and data presentation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If comprehensive data and information are provided to decision makers during chaotic events, then the completeness of information is improved, but the decision maker becomes overwhelmed or confused and cannot make optimal decisions
Solution Approach 1:
The system extracts and presents only the most critical and relevant decisions from the complete set of available decisions. The optimization algorithm identifies and eliminates redundant or less important decisions, presenting a streamlined subset to the decision maker that maintains completeness of essential information while avoiding overload.
Solution Approach 2:
The system applies different levels of detail and presentation to different decisions based on their importance and characteristics. Critical decisions receive prominent presentation with detailed information, while less critical decisions are summarized or grouped, allowing the decision maker to focus on what matters most without missing important details.
2Adaptability or versatility
If multiple decisions are considered simultaneously during chaotic events, then the comprehensiveness of decision coverage is improved, but the complexity of decision sequencing and coordination increases
Solution Approach 1:
The system segments the set of decisions into ordered sequences based on their interdependencies and criticality. The optimization algorithm determines the optimal sequence in which decisions should be considered and executed, breaking down the complex multi-decision problem into manageable sequential steps while maintaining comprehensive coverage of all necessary decisions.
3Adaptability or versatility
If all available decisions are presented to the decision maker, then the completeness of decision options is improved, but the time required to make decisions increases
Solution Approach 1:
The system dynamically adjusts the presentation of decisions based on the chaotic event's characteristics, the decision maker's preferences, and the current situation. The optimization algorithm adapts the decision set in real-time, presenting the most relevant options first and allowing the decision maker to drill down into additional options if needed, thus maintaining completeness while reducing initial presentation time.
Data Source
AI summary
A method for displaying information related to a chaotic event. A mathematical optimization algorithm is used to select a first optimal decision set for a user. The mathematical optimization algorithm takes as input a decision template, chaotic event information, at least one constraint, and a user profile. A heuristic algorithm is used to eliminate a first subset of decisions. The first subset of decisions is in the first optimal decision set. A second optimal decision set is formed. The second optimal decision set comprises the first optimal decision set less the first subset of decisions. The mathematical optimization algorithm is used to select a sequence in which decisions in the second optimal decision set are to be considered. The mathematical optimization algorithm takes as input the second optimal decision set, the decision template, the chaotic event information, the at least one constraint, and the user profile. The sequence is stored.