Strip mine area four-water-resource combined allocation method based on improved genetic algorithm

Abstract

The invention provides an improved genetic algorithm-based joint allocation method for four water resources in a strip mine area. The method comprises the following steps of: predicting the sum of water supply amounts continuously generated by various types of water sources in a target speculation time period; predicting the sum of water demand in the target speculation time period; constructing a water resource allocation model for combined water supply of multiple water sources in the target strip mine area; solving a water resource allocation model for combined water supply of multiple water sources in the target strip mine area to obtain each candidate allocation scheme for water supply of each type of water sources to each target water use department; and determining an optimal allocation scheme, and realizing water supply scheduling of each type of water source to each target water use department in the target speculation time period.

Description

Technical Field

[0001] The invention relates to a water resource optimization and allocation method for joint water supply from multiple water sources in an open-pit mine area, belonging to the technical field of water resource optimization allocation. Background Art

[0002] The drainage of groundwater in open-pit mines is a typical consumption-type groundwater dynamic mode. In this process, it is inevitable that water resources will be lost to varying degrees, affecting the dynamic stability of the conversion of various water resources in the mining area. At the same time, open-pit mines require a large amount of water resources in the process of normal production, mining area life, and surrounding environmental ecological protection.

[0003] In the actual production process, mine water cannot be used efficiently. In addition, in the research on water resource allocation in open-pit mines, there are few cases of using mine water in open-pit mines as water resource allocation, which contradicts the current situation of water shortage around the mining area.

[0004] Therefore, human intervention is needed to jointly allocate multiple water resources. By constructing a limited unconventional water resource and its configuration and application model in mining area life, industry and other fields, we discuss the optimal allocation of mining area water resources, achieve the maximum development and utilization of open-pit mining area water resources, solve the problem of water resource load balance in mining area, and meet the fundamental goals of economic, ecological environment and social benefits. Summary of the invention

[0005] The present invention optimizes the allocation of water resources in open-pit mines based on the evaluation of the availability of water quality and water quantity of water sources in mining areas, constructs a water resource allocation model for joint water supply from multiple water sources in open-pit mines, and provides an efficient solution method.

[0006] A method for jointly allocating four water resources in an open-pit mine area based on an improved genetic algorithm, characterized in that the method is used to dispatch preset water sources of various types in a target open-pit mine area to achieve allocation of various types of water sources among target water-using departments, including the following steps:

[0007] Step S1, predicting the total water supply generated by various types of water sources in the target estimation period, i.e., the available water volume, based on the meteorological data and hydrological data of the target open-pit mine area in the target historical period, and then executing step S2;

[0008] Step S2, predicting the total water demand of each target water-using department in the target open-pit mine area in the target speculation period, i.e., the water demand, based on the actual water consumption of the target open-pit mine area in the target historical period, and then executing step S3;

[0009] Step S3, based on the meteorological data and hydrological data of the target open-pit mine area in the target historical period, as well as the actual water consumption, a water resource allocation model for joint water supply of multiple water sources in the target open-pit mine area is constructed, and then step S4 is executed;

[0010] Step S4, based on the available water volume and water demand of the target open-pit mine area within the target estimation period, solve the water resource allocation model of multiple water sources for joint water supply of the target open-pit mine area, obtain various water supply allocation plans for each type of water source to supply water to each target water-using department, and then execute step S5;

[0011] Step S5, based on the various water supply allocation plans to be selected, determine the optimal water supply allocation plan to achieve water supply scheduling of various types of water sources to various target water-using departments during the target estimation period.

[0012] Furthermore, in the step S1, the total water supply generated by each type of water source within the target estimation period is predicted based on the wet and dry year method.

[0013] Furthermore, in step S2, the total water demand of each target water-using department within the target estimation period is predicted based on the average value method.

[0014] Furthermore, in step S3, the water resource allocation model for the target open-pit mine area with multiple water sources for joint water supply has an objective function, and the objective function includes an economic objective function f s (x), expressed as water supply cost; social objective function f e (x), expressed as water supply satisfaction rate; ecological environment objective function f k (x), expressed as the total amount of pollutants, the specific objective function is:

[0015] F = opt[ρ s f s (x)+ρ e f e (x)+ρ k f k (x)]

[0016]

[0017] min f k (x) = ∑ i p i x i

[0018] Among them, ρ s , e , k They represent the weight coefficients of the objective functions that consider economic benefits, social benefits, and ecological and environmental benefits respectively; is the unit water extraction cost of water source i; represents the unit cost of delivering water from source i to distribution agency j; is the unit treatment cost of water source i; x ijrepresents the amount of water allocated from water source i to department j; μ j is the weight coefficient of department j; x j and D j are the actual water supply and demand respectively; p i represents the pollution intensity of water source i; x i It represents the amount of water taken from water source i.

[0019] Furthermore, based on the relationship between water supply and demand data in the target historical period, the objective function includes the following constraints:

[0020] Water supply capacity constraints, demand satisfaction constraints, water quality requirement constraints, water supply structure constraints, and non-negativity constraints.

[0021] Furthermore, the water supply capacity constraint is:

[0022]

[0023] Among them, x ij is the amount of water allocated from water source i to sector j; S i is the maximum water supply capacity of water source i;

[0024] The requirements satisfy the constraints:

[0025]

[0026] Among them, x ij is the amount of water allocated from water source i to sector j; D j is the minimum water demand of department j;

[0027] The water quality requirements are constrained by:

[0028]

[0029] Among them, q i is the water quality index of water source i; Q j is the water quality requirement of department j;

[0030] The water supply structure constraints are:

[0031]

[0032] Among them, x ij is the amount of water allocated from source i to sector j; and They represent the minimum and maximum proportion of water obtained by department j from source i;

[0033] The non-negative factors are:

[0034]

[0035] Among them, x ij is the amount of water allocated from source i to sector j.

[0036] Furthermore, the step S4 comprises:

[0037] Step S41, using the NSGA-II algorithm to solve the water resource allocation model of the target open-pit mine area with multiple water sources for joint water supply, to obtain a Pareto frontier solution set, and then executing step S42;

[0038] Step S42, locally optimizing the Pareto frontier solution set by using simulated annealing, and then executing step S43;

[0039] Step S43, based on the various water supply allocation schemes for supplying water to the target water-using departments from various types of water sources, output the specific value of the objective function corresponding to each of the water supply allocation schemes for selection.

[0040] Furthermore, the step S41 includes:

[0041] Step S411, randomly generate an initial parent population of size N, each individual in the population represents a feasible solution, each feasible solution corresponds to a water supply plan that allocates various types of water sources to various target water-using departments, and then execute step S412;

[0042] Step S412, according to the objective function and constraint conditions of the water resource allocation model for joint water supply of multiple water sources in the target open-pit mine area, the initial parent population is non-dominated sorted; then, the crowding degree of the individuals in the determined non-dominated layer is calculated, and then step S413 is executed;

[0043] Step S413, selecting individuals to perform crossover and mutation operations from the initial parent population according to the non-dominated sorting priority and the crowding degree; then, performing crossover and mutation operations on the selected individuals according to the defined crossover rate and mutation rate to generate a child population of size N, and then executing step S414;

[0044] Step S414, merge the initial parent population and the child population to generate a population of size 2N, perform non-dominated sorting on the merged population, and calculate the crowding degree of each individual in the merged population, select the first N individuals in the merged population according to the non-dominated sorting priority and crowding degree to form the next generation population, and then execute step S415;

[0045] Step S415, if the termination condition is met, the Pareto frontier solution set of the last generation is output and step S42 is executed; otherwise, steps S411 to S414 are iteratively repeated until the termination condition is met.

[0046] Further, the step S42 includes:

[0047] Step S421, based on the objective function and constraints of the water resource allocation model for joint water supply of multiple water sources in the target open-pit mine area, the Pareto frontier solution set is used as the initial solution set, each solution in the initial solution set corresponds to a water supply plan that allocates each type of water source to each target water-using department, and the objective function value f(ω) corresponding to each solution is calculated, and then step S422 is executed;

[0048] Step S422, based on the initial solution set, randomly perturb the initial solution, generate a corresponding new solution, and calculate the objective function value f(ω') corresponding to the new solution, and then execute step S423;

[0049] Step S423, based on f(ω') and f(ω), obtain the change of the objective function value, that is, calculate the difference between f(ω') and f(ω), determine whether to accept the new solution according to the acceptance criterion, and then execute S424;

[0050] Step S424, determine whether the number of iterations and termination conditions are met. If so, output the candidate water supply allocation plans for each type of water source to each target water-using department and execute step S43; otherwise, gradually lower the temperature to reduce the probability of large disturbances, and repeat steps S422 to S424.

[0051] Furthermore, in step S5, based on the smallest proportion of groundwater, an optimal water supply allocation plan is determined to achieve water supply scheduling of various types of water sources to various target water-using departments during the target estimation period.

[0052] The present invention has the following beneficial effects:

[0053] The present invention constructs a method for jointly allocating four water resources in an open-pit mine area based on an improved genetic algorithm, which can better integrate the large amount of water resources required in the normal industrial production, mining area life, and surrounding ecological protection of the open-pit mine area, and jointly allocate multiple water resources in combination with the social, ecological, environmental and other requirements generated by the water resource allocation. The improved genetic algorithm is used to determine the optimal solution with the best comprehensive benefit for water allocation by each water supply department to each water user department, providing theoretical support for the optimal allocation of water resources in open-pit mines. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 This is a schematic diagram of a specific process of a method for jointly allocating four water resources in an open-pit mine area based on an improved genetic algorithm proposed in the present invention.

[0055] Figure 2 Model optimization flow chart after improving genetic algorithm with simulated annealing.

[0056] Figure 3A three-dimensional schematic diagram of the annealing optimization Pareto optimal frontier solution set generated after solving the model in an embodiment of the present invention. DETAILED DESCRIPTION

[0057] The following is a typical water supply allocation plan, and the specific data are shown in Table 1-5.

[0058]

[0059] Table 1 shows the water extraction, transportation and treatment costs of various water sources.

[0060] Water source type Pollutant concentration (mg / L) Atmospheric precipitation 0.10 Surface water 0.20 groundwater 0.15 Mine water 0.18

[0061] Table 2 shows the pollutant concentrations of various water sources

[0062] Water use sector Water quality requirements (mg / L) Industrial water 0.20 Domestic water 0.14 Ecological water use 0.15 Mine recharge 0.16

[0063] Table 3 shows the water quality requirements of various water-using departments

[0064]

[0065] Table 4 shows the maximum water supply capacity of each water source

[0066] Water use sector Demand (10,000 cubic meters) Industrial water 1200 Domestic water 1800 Ecological water use 1300 Mine recharge 1100

[0067] Table 5 shows the water demand of each water-using department

[0068] The specific implementation process is as follows:

[0069] Step S1, based on the meteorological data and hydrological data of the target open-pit mine area in the target historical period, using the wet and dry year method, or based on the historical average water supply in the target historical period corresponding to the time range of the target estimation period in the same time range, predict the total water supply generated by multiple water sources in the target estimation period, that is, the available water volume;

[0070] Step S2, based on the actual water consumption of the target open-pit mine area in the target historical period, using the historical average water demand of the target historical period corresponding to the time range of the target estimation period in the same time range, predict the total water demand of each target water-using department in the target open-pit mine area in the target estimation period, that is, the water demand;

[0071] Step S3, based on the meteorological data and hydrological data of the target open-pit mine area in the target historical period, and the actual water consumption, that is, based on the actual water supply and actual water consumption of the target open-pit mine area in the target historical period, construct a water resource allocation model for joint water supply of multiple water sources in the target open-pit mine area;

[0072] The water resource allocation model for the joint water supply of multiple water sources in the target open-pit mine area has an objective function, and the objective function includes an economic objective function f s (x), expressed as water supply cost; social objective function f e (x), expressed as water supply satisfaction rate; ecological environment objective function f k (x), expressed as the total amount of pollutants, the specific objective function is:

[0073] F = opt[ρ s f s (x)+ρ e f e (x)+ρ k f k (x)]

[0074]

[0075]

[0076] min f k (x) = ∑ i p i x i

[0077] Among them, ρ s , e , k They represent the weight coefficients of the objective functions that consider economic benefits, social benefits, and ecological and environmental benefits respectively; is the unit water extraction cost of water source i; represents the unit cost of delivering water from source i to distribution agency j; is the unit treatment cost of water source i; x ij represents the amount of water allocated from water source i to department j; μ j is the weight coefficient of department j; x j and D j are the actual water supply and demand respectively; p i represents the pollution intensity of water source i; x i It represents the amount of water taken from water source i.

[0078] The objective function of the water resource allocation model for the target open-pit mine area with multiple water sources for joint water supply has the following constraints:

[0079] Water supply capacity constraints, demand satisfaction constraints, water quality requirement constraints, water supply structure constraints, and non-negativity constraints.

[0080] The water supply capacity constraint is:

[0081]

[0082] Among them, x ij is the amount of water allocated from water source i to sector j; S i is the maximum water supply capacity of water source i;

[0083] The requirements satisfy the constraints:

[0084]

[0085] Among them, x ij is the amount of water allocated from water source i to sector j; D j is the minimum water demand of department j;

[0086] The water quality requirements are constrained by:

[0087]

[0088] Among them, q i is the water quality index of water source i; Q j is the water quality requirement of department j;

[0089] The water supply structure constraints are:

[0090]

[0091] Among them, x ij is the amount of water allocated from source i to sector j; and They represent the minimum and maximum proportion of water obtained by department j from source i;

[0092] The non-negative factors are:

[0093]

[0094] Among them, x ij is the amount of water allocated from source i to sector j.

[0095] Step S4, based on the available water volume and water demand of the target open-pit mine area within the target estimation period, solving the water resource allocation model of multiple water sources for joint water supply of the target open-pit mine area, and obtaining various candidate water supply allocation plans for each type of water source to supply water to each target water-using department;

[0096] Optionally, the S4 includes:

[0097] Step S41, using the NSGA-II algorithm to solve the water resource allocation model of the target open-pit mine area with multiple water sources for joint water supply, and obtain a Pareto frontier solution set;

[0098] Specifically include:

[0099] Step S411, randomly generate an initial parent population of size N, each individual in the population represents a feasible solution, each feasible solution corresponds to a water supply plan that allocates various types of water sources to various target water-using departments, and then execute step S412;

[0100] Step S412, according to the objective function and constraint conditions of the water resource allocation model for joint water supply of multiple water sources in the target open-pit mine area, the initial parent population is non-dominated sorted; then, the crowding degree of the individuals in the determined non-dominated layer is calculated, and then step S413 is executed;

[0101] Step S413, selecting individuals to perform crossover and mutation operations from the initial parent population according to the non-dominated sorting priority and the crowding degree; then, performing crossover and mutation operations on the selected individuals according to the defined crossover rate and mutation rate to generate a child population of size N, and then executing step S414;

[0102] Step S414, merge the initial parent population and the child population to generate a population of size 2N, perform non-dominated sorting on the merged population, and calculate the crowding degree of each individual in the merged population, select the first N individuals in the merged population according to the non-dominated sorting priority and crowding degree to form the next generation population, and then execute step S415;

[0103] Step S415, if the termination condition is met, the Pareto frontier solution set of the last generation is output and step S42 is executed; otherwise, steps S411 to S414 are iteratively repeated until the termination condition is met.

[0104] Step S42, locally optimizing the Pareto frontier solution set by using simulated annealing;

[0105] Specifically include:

[0106] Step S421, based on the objective function and constraints of the water resource allocation model for joint water supply of multiple water sources in the target open-pit mine area, the Pareto frontier solution set is used as the initial solution set, each solution in the initial solution set corresponds to a water supply plan that allocates each type of water source to each target water-using department, and the objective function value f(ω) corresponding to each solution is calculated, and then step S422 is executed;

[0107] Step S422, based on the initial solution set, the initial solution is randomly perturbed, the amplitude of the perturbation decreases as the temperature decreases, the initial perturbation is large, and the perturbation gradually converges in the later stage, ensuring a wide search range while avoiding the trap of local optimal solutions, and generating a corresponding new solution, and calculating the objective function value f(ω') corresponding to the new solution, and then executing step S423;

[0108] Step S423, based on f(ω') and f(ω), obtain the change of the objective function value, that is, calculate the difference between f(ω') and f(ω), and judge whether to accept the new solution according to the acceptance criterion, that is, according to the Metropolis criterion: if the objective function value change is ≤0, then accept the new solution, otherwise accept the new solution with a certain probability to jump out of the local optimum, and then execute S424;

[0109] Step S424, set the termination condition as that the initial solution set no longer changes. Based on the termination condition, determine whether the number of iterations and the termination condition are met. If so, output the candidate water supply allocation plans for each type of water source to each target water-using department. The output candidate water supply allocation plans maintain the multi-objective optimization characteristics of the Pareto frontier solution set, and the accuracy and stability are also significantly improved; otherwise, gradually lower the temperature to reduce the probability of large disturbances, and repeat steps S422 to S424.

[0110] Step S43, based on the various water supply allocation schemes for supplying water to the target water-using departments from various types of water sources, output the specific value of the objective function corresponding to each of the water supply allocation schemes for selection.

[0111] After the model operation, a variety of water supply allocation schemes that meet the objective function and constraint conditions are generated. The optimal solution with comprehensive benefits can be selected as the optimal allocation scheme according to the actual situation. This embodiment selects a better scheme with an economic target (water supply cost) of 27.4156 million yuan, a social target (water supply satisfaction rate) of 88.4%, and an ecological target (minimization of pollutants) of 1.3×10 9 mg, for specific preparation scheme, see Table 6;

[0112]

[0113] Table 6

[0114] The final result shows that the total cost of supplying water to various departments is 27.4156 million yuan. The cost mainly includes the water extraction, transportation and treatment costs of each water source. The specific allocation depends on the amount of water supplied to different departments by each water source. The water supply satisfaction rate is 88.4%, of which the industrial and domestic water guarantee rates are 100%, the ecological water guarantee rate is 90.5%, and the reinjection water guarantee rate is 63.2%. Priority is given to industrial and domestic water, while the reinjection water guarantee rate is lower than that of other water. The total amount of pollutants is 1.3×10 9 Milligrams, this value is calculated based on the water supply and pollutant concentration in the water source. The pollutant emissions are controlled within a reasonable range, indicating that when the water supply satisfaction rate is 88.4%, the pollutant emissions have been relatively optimized.

[0115] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any way. Any simple modification, change and equivalent structural change made to the above embodiment based on the technical essence of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A method for joint allocation of four water resources in open-pit mines based on improved genetic algorithm, characterized in that: The method is used to schedule preset water sources of various types in a target open-pit mine area, and realize the allocation of various types of water sources among target water-using departments, and includes the following steps: Step S1, predicting the total water supply generated by various types of water sources in the target estimation period, i.e., the available water volume, based on the meteorological data and hydrological data of the target open-pit mine area in the target historical period, and then executing step S2; Step S2, predicting the total water demand of each target water-using department in the target open-pit mine area in the target speculation period, i.e., the water demand, based on the actual water consumption of the target open-pit mine area in the target historical period, and then executing step S3; Step S3, based on the meteorological data and hydrological data of the target open-pit mine area in the target historical period, as well as the actual water consumption, a water resource allocation model for joint water supply of multiple water sources in the target open-pit mine area is constructed, and then step S4 is executed; Step S4, based on the available water volume and water demand of the target open-pit mine area within the target estimation period, solve the water resource allocation model of multiple water sources for joint water supply of the target open-pit mine area, obtain various water supply allocation plans for each type of water source to supply water to each target water-using department, and then execute step S5; Step S5, based on the various water supply allocation plans to be selected, determine the optimal water supply allocation plan to achieve water supply scheduling of various types of water sources to various target water-using departments during the target estimation period.

2. The method for jointly allocating four water resources in an open-pit mine area based on an improved genetic algorithm according to claim 1, characterized in that: In step S1, the total water supply generated by each type of water source within the target estimation period is predicted based on the wet and dry year method.

3. The method for jointly allocating four water resources in an open-pit mine area based on an improved genetic algorithm according to claim 1, characterized in that: In step S2, the total water demand of each target water-using department within the target estimation period is predicted based on the average method.

4. The method for jointly allocating four water resources in an open-pit mine area based on an improved genetic algorithm according to claim 1, characterized in that: In step S3, the water resource allocation model for the target open-pit mine area with multiple water sources for joint water supply has an objective function, and the objective function includes an economic objective function f s (x), expressed as the cost of water supply; Social objective function f e (x), expressed as water supply satisfaction rate; ecological environment objective function f k (x), expressed as the total amount of pollutants, the specific objective function is: F=opt[ρ s f s (x)+p e f e (x)+p k f k (x)] Among them, ρ s , e , k They represent the weight coefficients of the objective functions that consider economic benefits, social benefits, and ecological and environmental benefits respectively; is the unit water extraction cost of water source i; represents the unit cost of delivering water from source i to distribution agency j; is the unit treatment cost of water source i; x ij represents the amount of water allocated from water source i to department j; μ j is the weight coefficient of department j; x j and D j are the actual water supply and demand respectively; p i represents the pollution intensity of water source i; x i It represents the amount of water taken from water source i.

5. The method for jointly allocating four water resources in an open-pit mine area based on an improved genetic algorithm according to claim 4, characterized in that: Based on the relationship between water supply and demand data in the target historical period, the objective function includes the following constraints: Water supply capacity constraints, demand satisfaction constraints, water quality requirement constraints, water supply structure constraints, and non-negativity constraints.

6. The method for jointly allocating four water resources in an open-pit mine area based on an improved genetic algorithm according to claim 5, characterized in that: The water supply capacity constraint is: Among them, x ij is the amount of water allocated from water source i to sector j; S i is the maximum water supply capacity of water source i; The requirements satisfy the constraints: Among them, x ij is the amount of water allocated from water source i to sector j; D j is the minimum water demand of department j; The water quality requirements are constrained by: Among them, q i is the water quality index of water source i; Q j is the water quality requirement of department j; The water supply structure constraints are: Among them, x ij is the amount of water allocated from source i to sector j; and They represent the minimum and maximum proportion of water obtained by department j from source i; The non-negative factors are: Among them, x ij is the amount of water allocated from source i to sector j.

7. A method for jointly allocating four water resources in an open-pit mine area based on an improved genetic algorithm according to any one of claims 1 to 6, characterized in that: The step S4 comprises: Step S41, using the NSGA-II algorithm to solve the water resource allocation model of the target open-pit mine area with multiple water sources for joint water supply, to obtain a Pareto frontier solution set, and then executing step S42; Step S42, locally optimizing the Pareto frontier solution set by using simulated annealing, and then executing step S43; Step S43, based on the various water supply allocation schemes for supplying water to the target water-using departments from various types of water sources, output the specific value of the objective function corresponding to each of the water supply allocation schemes for selection.

8. The method for jointly allocating four water resources in an open-pit mine area based on an improved genetic algorithm according to claim 7, characterized in that: The step S41 comprises: Step S411, randomly generate an initial parent population of size N, each individual in the population represents a feasible solution, each feasible solution corresponds to a water supply plan that allocates various types of water sources to various target water-using departments, and then execute step S412; Step S412, according to the objective function and constraint conditions of the water resource allocation model for joint water supply of multiple water sources in the target open-pit mine area, the initial parent population is non-dominated sorted; then, the crowding degree of the individuals in the determined non-dominated layer is calculated, and then step S413 is executed; Step S413, selecting individuals to perform crossover and mutation operations from the initial parent population according to the non-dominated sorting priority and the crowding degree; then, performing crossover and mutation operations on the selected individuals according to the defined crossover rate and mutation rate to generate a child population of size N, and then executing step S414; Step S414, merge the initial parent population and the child population to generate a population of size 2N, perform non-dominated sorting on the merged population, and calculate the crowding degree of each individual in the merged population, select the first N individuals in the merged population according to the non-dominated sorting priority and crowding degree to form the next generation population, and then execute step S415; Step S415, if the termination condition is met, the Pareto frontier solution set of the last generation is output and step S42 is executed; otherwise, steps S411 to S414 are iteratively repeated until the termination condition is met.

9. The method for jointly allocating four water resources in an open-pit mine area based on an improved genetic algorithm according to claim 7, characterized in that: The step S42 comprises: Step S421, based on the objective function and constraints of the water resource allocation model for joint water supply of multiple water sources in the target open-pit mine area, the Pareto frontier solution set is used as the initial solution set, each solution in the initial solution set corresponds to a water supply plan that allocates each type of water source to each target water-using department, and the objective function value f(ω) corresponding to each solution is calculated, and then step S422 is executed; Step S422, based on the initial solution set, randomly perturb the initial solution, generate a corresponding new solution, and calculate the objective function value f(ω') corresponding to the new solution, and then execute step S423; Step S423, based on f(ω') and f(ω), obtain the change of the objective function value, that is, calculate the difference between f(ω') and f(ω), determine whether to accept the new solution according to the acceptance criterion, and then execute S424; Step S424, determine whether the number of iterations and termination conditions are met. If so, output the candidate water supply allocation plans for each type of water source to each target water-using department and execute step S43; otherwise, gradually lower the temperature to reduce the probability of large disturbances, and repeat steps S422 to S424.

10. The method for jointly allocating four water resources in an open-pit mine area based on an improved genetic algorithm according to claim 1, characterized in that: In step S5, based on the smallest proportion of groundwater, an optimal water supply allocation plan is determined to achieve water supply scheduling of various types of water sources to various target water-using departments during the target estimation period.

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