Job Assignment Apparatus Using Hungarian Algorithm for Global Optimum
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Solution Overview
Problem
Existing automatic material-handling systems face challenges in optimally assigning a plurality of jobs to a plurality of vehicles, often resulting in local optimum solutions rather than global optimum solutions due to the NP-hard nature of the problem, limiting their effectiveness in complex equipment fabrication processes.
Innovation Solution
A job assignment apparatus using a cost-table composer to configure a cost table and an optimum solution calculator applying the Hungarian algorithm, with additional tools for statistical data calculation and conversion to ensure a single optimum solution is achieved, even when multiple initial solutions exist.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional assignment methods (priority-based, heuristic, etc.) are used, then the assignment process is simple and fast, but only local optimum solutions are achieved instead of global optimum solutions
Solution Approach 1:
The patent transforms the job assignment problem into a matrix form with cost parameters, where rows represent vehicles and columns represent jobs. By applying the Hungarian algorithm to this parameterized matrix, the system achieves global optimum solutions through systematic parameter optimization rather than heuristic approximations.
Solution Approach 2:
The patent replaces conventional heuristic assignment methods with a mathematical optimization approach (Hungarian algorithm). This substitution transitions from rule-based mechanical assignment to algorithmic optimization, enabling global optimum detection while maintaining computational efficiency through specialized matrix operations.
2Manufacturing precision
If the Hungarian algorithm is applied to find global optimum solutions, then solution optimality is improved, but the calculation complexity and time increase
Solution Approach 1:
The patent segments the job assignment problem into discrete matrix operations that can be processed systematically. By dividing the problem into matrix construction, algorithmic optimization, and solution extraction phases, the system achieves global optimality through structured computation rather than brute-force enumeration of all possible assignments.
Solution Approach 2:
The patent applies the Hungarian algorithm which performs more computation than necessary for local optima but guarantees global optimality. The algorithm intentionally exceeds minimal computational requirements by systematically evaluating all possible assignments through matrix operations, ensuring the best possible solution is found.
3Productivity
If multiple vehicles are assigned to multiple jobs, then system capacity is increased, but interference between vehicles increases making optimization more difficult
Solution Approach 1:
The patent introduces a cost matrix as an intermediary representation between vehicles and jobs. This matrix serves as a mediator that captures all assignment relationships and constraints in a structured format, allowing the Hungarian algorithm to systematically optimize assignments across multiple vehicles and jobs while managing complexity through mathematical abstraction.
Data Source
AI summary
A job assignment apparatus of an automatic material-handling apparatus to calculate an initial optimum solution based on a cost table configured by the job assignment, and to calculate a single optimum solution based on the cost table converted by statistical data. The Hungarian algorithm is stored in a tool storage unit to calculate the optimum solution. A statistical-data calculator calculates statistical data to convert costs of the initial cost table into other costs. The cost-table converter converts the costs of the initial cost table based on the calculated statistical data.