An improved intelligent optimization algorithm for small-batch order production scheduling

Area of Science:

• Operations Research
• Manufacturing Systems Engineering
• Industrial Engineering

Background:

• The Critical Path Method (CPM) is widely used for integrated scheduling of small-batch orders.
• CPM's focus on vertical processes limits its effectiveness by neglecting horizontal parallel relationships.
• This neglect can lead to suboptimal total product completion times.

Purpose of the Study:

• To introduce an innovative algorithm that overcomes CPM limitations.
• To optimize the total processing time of products by considering horizontal parallel relationships.
• To enhance scheduling strategies for small-batch manufacturing.

Main Methods:

• Developed a novel algorithm based on CPM scheduling results.
• Implemented a strategy of "exchanging adjacent processes on the same device".
• Generated multiple scheduling schemes by swapping interchangeable processes to expand the solution space.

Main Results:

• The proposed algorithm effectively expands the solution space for scheduling.
• Optimized solutions leveraging horizontal parallel relationships were discovered.
• Experimental verification confirmed the algorithm's effectiveness in reducing total processing time.

Conclusions:

• The novel algorithm successfully addresses limitations of the CPM.
• The strategy of exchanging adjacent processes enhances scheduling efficiency.
• This approach leads to reduced total product processing times.