Replacement flow shop energy efficiency optimization scheduling method integrating delivery date configuration

Abstract

The invention discloses a replacement flow shop energy efficiency optimization scheduling method integrating delivery date configuration. The method comprises the steps of collecting production data to generate three energy efficiency optimization and delivery date configuration frameworks; carrying out integrated encoding between the workpiece and the machine by two frameworks; wherein the code of the rejected order in the third framework is spliced after the code of the received order; generating an initial solution by adopting an NEH heuristic algorithm according to a coding mode, and initializing a tabu table; performing tabu search on the later generated initial solution, and updating a local optimal solution and a tabu table; decoding the obtained optimal solution to obtain a scheduling scheme; generating an initial population according to a coding mode; calculating a target fitness value of the generated population and carrying out fitness value distribution; and performing selection, crossover and mutation operations on the later generated population, updating a local optimal solution, performing decoding, and performing integration to obtain a scheduling scheme. Accordingto the method, a scheduling scheme satisfying enterprises and clients is obtained in a reasonable time, energy consumption is reduced, enterprise profits are improved, and production efficiency is improved.

Description

technical field [0001] The invention belongs to the technical field of scheduling of replacement flow workshops, and in particular relates to an energy efficiency optimization scheduling method for replacement flow workshops with integrated delivery date configuration. Background technique [0002] With the globalization of green manufacturing, energy conservation and environmental protection in the manufacturing industry have significant economic and social benefits. Manufacturing companies are facing the dual challenges of continuously increasing energy costs and their own energy saving and emission reduction. In manufacturing companies that are trending towards green production, they are gradually demanding higher product profits, less energy consumption and shorter delivery Time invested with more attention, flow shop energy-saving measures are crucial for maximizing machine processing efficiency and minimizing production costs. Production scheduling is also one of the ...

AI Technical Summary

Problems solved by technology

However, for the replacement flow shop scheduling problem integrating energy efficiency optimization and lead time configuration framework, the existing optimization methods usually optimize energy efficiency under a given lead time, or optimize lead time without considering energy efficiency, and It does not consider the optimization of delivery time and energy efficiency at the same time, and does not analyze the relationship characteristics between the total income of the enterprise in the production link and the enterprise credit in the sales link, which has great limitations.

More importantly, the market competition is becoming increasingly fierce, and the scale of each manufacturing enterprise is uneven. The existing scheduling method does not systematically analyze the complete green flow workshop, resulting in increased energy consumption, increased energy costs, decreased production efficiency, The obtained scheduling plan is difficult to meet the expectations of the manufacturer and customers, and the probability of violating the delivery agreement between the manufacturer and customers increases, which in turn leads to problems such as decline in corporate income and reputation

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