A rescheduling method for flow shop

Abstract

The invention provides a flow workshop rescheduling method, which belongs to the field of workshop scheduling technology and includes real-time acquisition of emergencies of the current flow workshop, rescheduling workpieces, machine availability time and completion time of the main processing process; and analyzing the started processes according to different emergencies. Group the flow shop with unstarted processes; determine the flow shop rescheduling objectives and constraints; use the migratory bird flock optimization method to generate the flow shop rescheduling plan; send the flow shop rescheduling plan to each process in the flow shop for rescheduling. The present invention applies the migratory bird flock algorithm to the rescheduling problem of the flow workshop, taking into account multiple emergencies to ensure rapid response between emergencies; using a neighborhood search mechanism of insertion or exchange, it effectively ensures that the rescheduling plan is in two Timely handling of emergencies; continuous transmission of search information to subsequent migrating birds, and continuous replacement of the leading bird can ensure the diversity and stability of the scheduling plan.

Description

technical field [0001] The invention belongs to the technical field of workshop scheduling, and in particular relates to a method for rescheduling a flow workshop. Background technique [0002] Flow shop scheduling problem is a kind of shop scheduling problem, which widely exists in various production processes, such as steelmaking and continuous casting, textile processing and so on. At present, scholars at home and abroad have carried out a lot of research on the static scheduling problem of assembly line scheduling, and obtained extensive research results and applied them in actual production. However, the actual production environment is often uncertain, and there are many unexpected events, such as random arrival of workpieces, random withdrawal of workpieces, changes in workpiece processing time, and random failures of equipment. Therefore, the flow shop rescheduling problem is more in line with the actual production process than the static scheduling problem. It has ...

AI Technical Summary

Problems solved by technology

The characteristics of these methods are that the rules are clear and easy to implement, but due to the uncertainty in the actual production process and too many random factors, the above methods cannot comprehensively consider various emergencies, and there is a big gap between them and the actual application

In recent years, with the development of computational intelligence methods, many intelligent optimization methods have been applied to solve flow shop scheduling problems, such as tabu search, simulated annealing, particle swarm optimization, genetic algorithm, neural network, meta-heuristic algorithm, expert system and For methods such as multi-agent technology, the above-mentioned algorithms are often unable to be applied to solve the flow shop rescheduling problem that comprehensively considers multiple emergencies due to insufficient convergence ability, or inability to solve large-scale problems, or inability to jump out of local optimum.

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