Method for optimizing energy consumption of aluminum section workshop based on ant colony algorithm and in view of time difference electricity price

Abstract

The invention discloses a method for optimizing energy consumption of an aluminum section workshop based on an ant colony algorithm and in view of time difference electricity price. According to the method, a production scheduling process of the aluminum section workshop is abstracted as a nonequivalent parallel machine scheduling problem in view of time difference electricity price and energy consumption; the ant colony optimization algorithm based on iterative computation is proposed on the basis of analysis on the scheduling problem, and ants realize scheduling of a machine and a workpiece through an iterative mode of machine-workpiece-machine, so that solution errors caused by independent scheduling of the machine and the workpiece in a conventional ant colony algorithm are reduced; in addition, a right-shift local search method is proposed according to the characteristics of time difference electricity price, so that the precision of a solution can be improved, the cycle frequency of ant colony computation can be greatly reduced, and the energy consumption of scheme solving is reduced.

Description

technical field [0001] The invention relates to workshop energy consumption optimization scheduling technology, in particular to an aluminum profile workshop energy consumption optimization method based on ant colony algorithm and considering time difference electricity price. Background technique [0002] In actual production and manufacturing, machines with different efficiencies (non-equivalent parallel machines) often run at the same time, which brings great difficulties to the formulation of production plans. Therefore, under the condition of ensuring the normal survival of enterprises, reducing energy consumption and production costs in the production process of non-equivalent parallel machines is one of the core issues concerned by the manufacturing industry. Especially in the aluminum profile extrusion workshop, the production of aluminum profile extrusion requires a large amount of natural gas and electricity, which is a high energy consumption manufacturing process...

AI Technical Summary

Problems solved by technology

[0006] The scheduling problem of workpiece arrival time is NP-hard. According to complexity theory, Rm|( M1 ,M2,…Mm) ,STsd|EminThe problem is also NP-hard. For NP-hard problems, the ant colony optimization algorithm is currently one of the most effective scheduling algorithms. In order to reduce the complexity of the solution, the construction of the solution is generally divided into two stages: in the first stage, the ants select a certain machine as the processing Machine, in the second stage, ants select a certain workpiece to process on the machine. A two-stage routing of ants means that a machine selects a workpiece for processing. Ants repeat two-stage routing until all workpieces are scheduled. This two-stage The assumption of the construction scheme of the solution is that the delay cost of the workpiece and the energy consumption cost of the machine are independent

However, as shown in Figure 2, the late cost sub-goal The sub-goal of machine energy consumption cost is not independent, but interrelated. Minimizing the delay cost is often aimed at sacrificing machine energy consumption (see Figure 2 Scheme 1, Scheme 2). Simply performing pheromone search on two sub-targets alone will lead to a decrease in algorithm performance.

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