Research On Green Workshop Scheduling Method Of Photovoltaic Assisted Energy Supply Based On Shuffled Frog Leaping Algorithm

Manufacturing plays an important role in economic development,but it also causes environmental pollution.In order to achieve sustainable development,it becomes particularly important to reduce carbon emissions and improve production efficiency.In order to reduce carbon emissions,reduce dependence on fossil energy and respond to the national carbon neutralization strategy,it is particularly critical to introduce clean energy into production activities.Photovoltaic power generation system is a clean,safe and renewable energy source that is derived from inexhaustible solar energy.The principle of photovoltaic power generation system is to use the photovoltaic effect of semiconductor materials to convert solar radiation energy into electric energy.It is a new trend to alternate photovoltaic and traditional energy sources.In addition,improving production efficiency and reducing energy consumption in production activities are also effective ways to reduce carbon emissions.Scheduling is one of the most important subsystems in manufacturing system.The task of scheduling is to arrange the processing order of all workpiece reasonably and satisfy the priority relationship in the processing plan.Traditional process research mainly focuses on productivity and cost,with little attention to other aspects,especially environmental issues.Scheduling can significantly affect the energy consumption of the entire manufacturing system.Therefore,reasonable scheduling can not only improve productivity,but also reduce energy consumption and carbon emissions.At present,"green scheduling",as a new scheduling mode,has become a hot topic in the field of scheduling because it reduces the cost of energy consumption and environmental pollution.Based on the concept of green scheduling,this thesis introduces photovoltaic auxiliary power supply,that is,the factory adds solar energy storage devices and gives priority to using solar energy for workshop production.This thesis mainly studied the photovoltaic auxiliary power reentrant hybrid flow shop scheduling problem and photovoltaic auxiliary power flexible job-shop scheduling problem,according to the characteristics of the problems the leapfrog algorithm is improved and the maximum completion time and carbon emissions at the same time as the optimization goal,simulation experiments with a large number of examples,the effectiveness of the proposed algorithm.The main contents of this thesis are as follows:(1)Introduced the background and significance of the problem.The research status of photovoltaic assisted power supply,shop scheduling and scheduling methods are described,the existing problems are analyzed,and the basic leapfrog algorithm principle is introduced.(2)For photovoltaic assisted energy supply reentrant mixed flow shop scheduling and PV assisted energy supply flexible job shop scheduling,the general description of the problem is given,and the constraint conditions and objective function to be solved are introduced.(3)Considering carbon emissions and maximum completion time,an improved leapfrog algorithm is designed to solve the dual-objective shop scheduling problem for reentry hybrid flow shop scheduling problem with photovoltaic assisted energy supply.A large number of examples are used to verify that the improved leapfrog algorithm is an effective method to solve the problem.(4)For the photovoltaic assisted flexible job-shop scheduling problem considering carbon emissions and maximum completion time,a frog jump algorithm with multiple learning objects is designed to solve the problem.The algorithm adopts a new learning object selection method,and a series of examples are used to verify the feasibility of the frog jump algorithm with multiple learning objects.