Abstract
Recently, energy scarcity and environmental pollution have become increasingly serious problems, while the scheduling of energy savings is attracting increasing attention from industries to minimize energy consumption. This article deals with the problem of scheduling production and maintenance under energy constraints in the flow shop. Two mixed binary integer programming models are provided to derive optimal scheduling to minimize total energy consumption (TEC). To solve this problem, we use an approximate method as a genetic algorithm (GA).
Highlights
It is certainly indisputable that the climate changes induced by this increase in the concentration of greenhouse gases will have multiple consequences that are still difficult to identify
Excessive emissions of greenhouse gases and in particular carbon dioxide produced by the combustion of fossil fuels
Fossil fuels have been widely used for electricity production, rational use of energy will contribute to a significant reduction in carbon emissions
Summary
It is certainly indisputable that the climate changes induced by this increase in the concentration of greenhouse gases will have multiple consequences that are still difficult to identify. They are expected to cause regional and global changes in temperature, precipitation and other climate variables, which could result in global changes in soil moisture, rising mean sea level and the prospect of more severe episodes of extreme heat, flooding and drought. Excessive emissions of greenhouse gases and in particular carbon dioxide produced by the combustion of fossil fuels. Fossil fuels have been widely used for electricity production, rational use of energy will contribute to a significant reduction in carbon emissions. We use an approximate method as a genetic algorithm (GA)
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