Interactive Test Schedule Adjustment for Multi-Sector Agreement
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Solution Overview
Problem
Conventional scheduling methods are inadequate in optimizing test schedules to satisfy requirements from multiple test sectors, as they struggle to represent objective functions and constraint conditions effectively, leading to difficulties in creating and presenting a test schedule plan that meets the needs of all users.
Innovation Solution
An interactive test-schedule adjustment method using a computer that displays initial and revised optimum schedules based on mathematical programming and neighborhood solutions, allowing users to adjust importance values and facilitating agreement through iterative display of schedules, including highlighting bottleneck items and facilities, and simulating investments in bottleneck facilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional scheduling methods using mathematical programming are used to assign items to manufacturing resources, then the assignment efficiency is improved, but the ability to satisfy requirements from multiple test sectors deteriorates
Solution Approach 1:
The system dynamically adjusts the objective function and constraint conditions based on input from multiple test sectors. The scheduling model transitions from a static mathematical programming approach to a dynamic interactive process where parameters can be modified during execution to reflect changing requirements from different users.
Solution Approach 2:
The invention adds a new dimension to conventional scheduling by incorporating multiple objective functions and constraint conditions that represent different test sector requirements. This transforms the problem from a single-objective optimization to a multi-dimensional decision-making framework that can simultaneously consider diverse priorities.
2Speed
If a single optimum schedule is calculated using mathematical programming, then the optimization speed is improved, but the ability to obtain agreement among multiple users deteriorates
Solution Approach 1:
The system implements a feedback mechanism where multiple schedules are presented to users, who can provide input on their preferences and requirements. The system then uses this feedback to generate revised schedules, creating an iterative process that continues until user agreement is reached.
Solution Approach 2:
The scheduling system acts as an intermediary between multiple test sectors with conflicting requirements. It mediates the negotiation process by generating multiple candidate schedules and facilitating comparison, allowing users to reach mutual agreement without direct confrontation of their conflicting needs.
3Device complexity
If conventional methods are used to represent objective functions and constraint conditions, then the calculation simplicity is improved, but the ability to create satisfactory test schedule plans for multiple users deteriorates
Solution Approach 1:
The complex scheduling problem is segmented into multiple manageable components, each representing a specific test sector's requirements. The objective function and constraint conditions are divided into separate modules that can be independently configured and adjusted for different users, making the overall system more adaptable.
Solution Approach 2:
The system enables flexible parameter changes in the objective function and constraint conditions based on input from different test sectors. Users can modify parameters such as priorities, time windows, and resource constraints to reflect their specific requirements, transforming the rigid conventional approach into a flexible adaptive system.
Data Source
AI summary
A method for interactive test-schedule adjustment is provided. The steps include: displaying a table including the importance and period of each test item; displaying a first optimum schedule obtained from an optimal solution based on values entered by a user into the table, the schedule including a use schedule of each test facilities used for each of the multiple test items; displaying a second optimum schedule obtained from an optimal solution recalculated by mathematical programming after a use schedule of a test item the importance of which is changed on the first optimum schedule is changed; and displaying a third optimum schedule based on neighborhood solutions obtained by a search method using a history of optimal solutions if no agreement between the users is obtained on the second schedule.