An Energy Saving Scheduling Control Method Considering Equipment Maintenance for Mixed Flow Workshop

Abstract

The invention relates to an energy-saving scheduling control method for a mixed flow workshop considering equipment maintenance. The method includes the following steps: Step 1: Obtain production constraints and solve an objective function according to the production characteristics of a mixed flow workshop, and introduce energy consumption targets to establish Multi-objective programming model; Step 2: Analyze the impact of equipment maintenance on production scheduling according to equipment maintenance data, and add equipment maintenance as corresponding constraints to the multi-objective programming model to form a complete multi-objective programming model; Step 3: Use GA algorithm to The actual mixed flow workshop performs coding genetic operations to obtain offspring individuals; Step 4: Use the hybrid algorithm of NSGA-II algorithm and heuristic algorithm to combine the offspring individuals to optimize and solve the complete multi-objective programming model, and according to the final obtained The optimal solution results are used to schedule and control the mixed flow workshop. Compared with the prior art, the present invention has the advantages of fast computing speed, good robustness and the like.

Description

technical field [0001] The invention relates to the technical field of production scheduling control considering equipment maintenance, in particular to an energy-saving scheduling control method for a mixed flow workshop considering equipment maintenance. Background technique [0002] The mixed flow shop problem can generally be described as: a batch of workpieces to be processed are processed through multiple processes in a certain order. The processing process of each workpiece is the same, and each equipment corresponds to a process, but the workpiece can be selected in each process. Different available devices. Under the condition of satisfying the production constraints, some performance indicators can be optimized by rationally arranging the processing sequence of workpieces and equipment selection. This is a class of NP-hard problems. [0003] In the existing research, in the Chinese patent "A hybrid fruit fly algorithm based on dual-objective job shop scheduling" ...

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Problems solved by technology

However, although the above literatures have solved the problem of workpiece scheduling in the flow shop and added the energy consumption target into the production scheduling, in actual production, the performance of the machine will gradually decline as the service time increases, which will not only lead to production delays and energy consumption. Loss will bring potential safety hazards, so the operating state of the equipment has to be considered. However, there are few researches on energy-saving production scheduling methods considering the operating state of the equipment in the literature.

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