An improved intelligent optimization algorithm for small-batch order production scheduling
Xiaohuan Zhang1, Zhen Wang2, Dan Zhang1
1School of Computer Science and Engineering, Huizhou University, Huizhou, 516007, China.
Scientific Reports
|September 13, 2024
Summary
This study introduces an innovative algorithm to optimize product processing times. By exchanging adjacent processes, it enhances scheduling by leveraging horizontal parallel relationships, improving total completion time.
Area of Science:
- Operations Research
- Manufacturing Systems Engineering
Background:
- Critical Path Method (CPM) is effective for small-batch order scheduling.
- CPM's limitations include overemphasis on vertical relationships and neglect of horizontal ones, leading to suboptimal product completion times.
Purpose of the Study:
- To introduce an innovative algorithm to overcome CPM limitations.
- To optimize total product processing time by leveraging horizontal parallel relationships.
Main Methods:
- Proposing a strategy of "exchanging adjacent processes on the same device".
- Generating multiple new scheduling schemes based on CPM results by swapping adjacent, interchangeable processes.
- Expanding the solution space to discover optimized solutions.
Main Results:
- The algorithm effectively expands the solution space.
- Optimized solutions are discovered by leveraging horizontal parallel relationships.
- Experimental verification confirms the algorithm's effectiveness in reducing total processing time.
Conclusions:
- The proposed algorithm successfully optimizes total product processing time.
- Leveraging horizontal parallel relationships is key to improving scheduling efficiency.
- This method offers a significant improvement over traditional CPM for certain scheduling problems.
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