Hyper-heuristic algorithm based ZDT flow shop job scheduling method

Abstract

The invention discloses a hyper-heuristic algorithm based ZDT (Zero Dead Time) flow shop job scheduling method. According to the invention, an objective function of a ZDT flow shop job scheduling problem is set firstly and a corresponding scheduling optimization model is established. On the above basis, a hyper-heuristic algorithm frame is combined, a harmony search algorithm applied widely is adopted as an HLH (High Level Heuristic) strategy of the hyper-heuristic algorithm, and a simple heuristic rule is designed aiming at the characteristics of the ZDT flow shop job scheduling problem for constructing an LLH (Low Level Heuristic) method set, so that the optimization solution of the ZDT flow shop job scheduling problem is realized. According to the invention, good global optimization performance of a meta-heuristic algorithm is remained and uncertainty caused by algorithm parameter adjustment depending on artificial experience in the meta-heuristic algorithm is avoided, so that the algorithm design efficiency is improved effectively and the method is significant to the improvement of flow shop job scheduling efficiency.

Description

technical field [0001] The invention belongs to the technical field of workshop job scheduling, and in particular relates to a zero-idle flow workshop job scheduling method based on a super-heuristic algorithm. Background technique [0002] As an important branch of production scheduling, Flow-shop Scheduling Problem (FSP) is an NP-hard complex combinatorial optimization problem in essence. The zero-idle flow shop job scheduling problem is a further extension of FSP, which requires that the machine does not idle during the production process, that is, no idle time is allowed between adjacent workpieces processed on the machine. For example, in the manufacturing process of glass fiber, the heating furnace needs to maintain a constant high temperature of 2800℉ in a production cycle. Due to the large amount of thermal inertia in the furnace, it takes several days to stop and start, and it takes a lot of time to use the equipment. Therefore, once it is running, it is not expect...

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Problems solved by technology

[0004] (2) Heuristic algorithms, such as NEH method, Johnson heuristic rules, KK method, etc. The implementation of this type of algorithm is relatively simple, but the quality of the scheduling solution obtained is not high, and it is often difficult to obtain the optimal solution;

In fact, this approach has shortcomings. Due to the large differences in problem definitions, constraints, and optimization objectives under different scheduling indicators, a single meta-heuristic algorithm cannot guarantee that it is always optimal on all problems (instances). than other algorithms

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