Multi-objective workpiece scheduling algorithm based on ant colony algorithm

Abstract

The invention discloses a workpiece scheduling method based on an ant colony optimization algorithm. The workpiece scheduling method is characterized in that workpieces are effectively selected in the scheduling process through the workpiece characteristics by using a Pareto multi-objective method, and production is performed by preferentially using the low-electricity-price period so that two objectives of optimizing electric power cost A and delay degree B can be realized. A better workpiece scheduling scheme is calculated under the environment of the parallel batch processor of the background of industrial time-of-use electricity price so that the utilization rate of enterprise resources and the energy use efficiency can be maximized, optimization of cost control and the production effect of the enterprise production process can be achieved and the market competitiveness of the enterprise can be enhanced.

Description

technical field [0001] The invention belongs to the field of industrial production scheduling, and is a multi-objective workpiece scheduling algorithm based on an ant colony algorithm. Background technique [0002] In the current market environment, the core competitiveness of manufacturing enterprises is not only simple manufacturing capabilities, but also excellent production scheduling algorithms to rationally utilize resources and equipment and improve the utilization of resources and equipment, so as to reduce costs and increase competition power purpose. Although the existing job scheduling algorithms on the market can also find feasible solutions to a certain extent, the corresponding problem models are often relatively simple, so they cannot be fully applied to problems in the actual production environment. The quality of the solution found is not high enough. Due to the many workpiece constraints in the actual calculation, the energy utilization efficiency under t...

AI Technical Summary

Problems solved by technology

Although the existing job scheduling algorithms on the market can also find feasible solutions to a certain extent, the corresponding problem models are often relatively simple, so they cannot be fully applied to problems in the actual production environment. The quality of the solution found is not high enough

Due to the many workpiece constraints in the actual calculation, the energy utilization efficiency under the dynamic ladder electricity price is weak, and the existing algorithms are often optimized for a single goal, which is difficult to meet the needs of enterprises for simultaneous optimization of multiple goals

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