Study Of Optimalwater Resources Allocation Of Irrigation District Based On Multi-objective Genetic Algorithm Evolution

As an integral part of the material basis of human survival and economic andsocial development，water resources is one of the irreplaceable natural resources. Withthe rapid population growth and socio-economic development, human beings areextremely limited water resources at an unprecedented pace and scale of development,and trigger a series of water issues. Therefore, it is necessary to optimize thescheduling of limited water resources, to achieve the sustainable use of waterresources, and promote the virtuous circle of ecological environment to ensuresustainable social and economic development.The paper first discusses the concept of the Water Resources Optimal and mainresearch contents of the research status at home and abroad, summarized and analyzedthe allocation of water resources development trend.The paper selects an irrigation scheme as a study area, and introduced theirrigation area and area weather, socio-economic profiles.Based on the specific circumstances of the irrigation area, the paper calculatesthe various parts of the irrigation district water demand, and a preliminary waterbalance.Then the paper gets the conclusion that at75%guarantee rate the irrigationwill face water shortage November to May,and need water resource optimizationscheduling. On this basis, the paper determines the objective function and selects themulti-objective genetic algorithm as the algorithm.The paper studies the genetic algorithm principles, characteristics, step，choosesmatlab as the programing environment，and calculates with the GOAT.On the base of conditions of water balance and capacity constraints, the paperuses matlab to calculate the model.and gets the results of different single-objectiveoptimization and multi-objective optimization results. With analysis and comparisonof the results，the paper gets the conclusion that the proportion of irrigated area,irrigation production of the multi-objective optimization are closed tothea singletarget the optimal value of the case，and at the same time the secondary objectivesincreased by10.78%and10.32%than the single-objective optimization.The programovercomes the contradictions of the unoptimal secondary objective in single-objectiveoptimization.