A method for joint deployment of four water resources in an open-pit mine area based on an improved genetic algorithm

Abstract

The application provides an open-pit mine four-water resource joint allocation method based on an improved genetic algorithm, which comprises the following steps: predicting the total water supply amount of each type of water source continuously generated in a target prediction period; predicting the total water demand amount in the target prediction period; constructing a water resource allocation model of joint water supply of various water sources in the target open-pit mine; solving the water resource allocation model of joint water supply of various water sources in the target open-pit mine to obtain each selected allocation scheme of water supply of each type of water source to each target water consumption department; and determining an optimal allocation scheme to realize water supply scheduling of each type of water source to each target water consumption department in the target prediction period.

Description

TECHNICAL FIELD

[0001] The present application relates to a kind of open pit area multiple water source joint water supply water resource optimization allocation method, belong to water resource optimization configuration technical field. BACKGROUND

[0002] Open pit area drainage groundwater is the typical consumption type groundwater dynamic mode, in this process, inevitably cause water resources loss in varying degrees, affect the dynamic stability of the conversion of multiple water resources in mining area.Meanwhile, open pit needs a large amount of water resources in the process of normal production, mining area life, surrounding environment ecological protection.

[0003] In actual production process, it is impossible to efficiently utilize pit water.And in the research of open pit area water resource allocation, there are few cases of open pit area pit water as water resource allocation, which is contradictory to the current situation of water resource shortage around mining area.

[0004] Therefore, artificial intervention is needed for joint allocation of multiple water resources, by constructing limited unconventional water resources and its allocation and application model in mining area life, industry and other fields, discussing the optimal allocation of water resources in mining area, realizing the maximum development and utilization of water resources in open pit area, solving the problem of water resource load balancing in mining area while meeting the fundamental goal of economic, ecological environment and social benefit. SUMMARY

[0005] The present application is based on the availability evaluation of water quality and water quantity of mining area water source, optimally allocates open pit area water resources, constructs water resource allocation model of multiple water source joint water supply in open pit area, and provides efficient solution method.

[0006] An open pit area four water resource joint allocation method based on improved genetic algorithm, characterized in that the method is used to schedule the preset each type of water source of target open pit area, realize the distribution of each type of water source between each target water department, comprising the following steps:

[0007] Step S1, according to the meteorological data and hydrological data of target open pit area in target historical period, predict the total water supply of each type of water source in target prediction period, i.e. available water, then execute step S2;

[0008] Step S2, according to the actual water consumption of target open pit area in target historical period, predict the total water demand of each target water department of target open pit area in target prediction period, i.e. water demand, then execute step S3;

[0009] Step S3, based on the meteorological data and hydrological data of target open pit area in target historical period, and actual water consumption, construct water resource allocation model of multiple water source joint water supply of target open pit area, then execute step S4;

[0010] Step S4, based on the available water amount and water demand amount of the target open-pit mine area in the target prediction period, solve the water resource allocation model of the target open-pit mine area multi-source water supply, obtain each selected water supply distribution scheme about water supply of each type of water source to each target water use department, and then execute step S5;

[0011] Step S5, based on each selected water supply distribution scheme, determine the optimal water supply allocation scheme for water supply scheduling of each type of water source to each target water use department in the target prediction period.

[0012] Further, in step S1, the total water supply amount of each type of water source in the target prediction period is predicted according to the rich and dry level year method.

[0013] Further, in step S2, the total water demand amount of each target water use department in the target prediction period is predicted according to the average value method.

[0014] Further, in step S3, the water resource allocation model of the target open-pit mine area multi-source water supply has an objective function, which includes an economic objective function f s (x) expressed by water supply cost; a social objective function f e (x) expressed by water supply satisfaction rate; and an ecological environment objective function f k (x) expressed by total pollutant amount, and 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] Wherein, ρ s , ρ e , ρ k respectively represent the weight coefficients of the objective functions considering economic benefit, social benefit and ecological environment benefit; is the unit water taking cost of water source i; represents the unit cost of conveying from water source i to water distribution department j; is the unit treatment cost of water source i; x ijxij represents the water quantity allocated from water source i to sector j; μ j is the weight coefficient of sector j; x j and D j are the actual water supply quantity and demand quantity respectively; p i represents the pollution intensity of water source i; x i represents the water quantity taken from water source i.

[0019] Further, based on the water supply and demand data relationship in the target historical period, the objective function contains the following constraint conditions:

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

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

[0022]

[0023] wherein x ij is the water quantity allocated from water source i to sector j; S i is the maximum water supply capacity of water source i;

[0024] The demand satisfaction constraint is:

[0025]

[0026] wherein x ij is the water quantity allocated from water source i to sector j; D j is the minimum water demand of sector j;

[0027] The water quality requirement constraint is:

[0028]

[0029] wherein q i is the water quality index of water source i; Q j is the water quality requirement of sector j;

[0030] The water supply structure constraint is:

[0031]

[0032] wherein x ij is the water quantity allocated from water source i to sector j; and respectively represent the minimum and maximum proportion of sector j obtained from water source i;

[0033] The non-negativity factor is:

[0034]

[0035] wherein x ij is the amount of water allocated from water source i to department j.

[0036] Further, the step S4 comprises:

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

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

[0039] Step S43, based on each candidate water supply allocation scheme of each type of water source to each target water consumption department, outputting the specific value of the objective function corresponding to each candidate water supply allocation scheme.

[0040] Further, the step S41 comprises:

[0041] Step S411, randomly generating an initial parent population with a size of N, each individual in the population representing a feasible solution, each feasible solution corresponding to a water supply scheme of allocating each type of water source to each target water consumption department, and then executing step S412;

[0042] Step S412, according to the objective function and the constraint condition of the water resources allocation model of the target open-pit mine area joint water supply of multiple water sources, performing non-dominated sorting on the initial parent population; then, performing crowding degree calculation on the individuals in the determined non-dominated layer, and then executing step S413;

[0043] Step S413, selecting individuals for performing 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 with a size of N, and then executing step S414;

[0044] Step S414, merging the initial parent population and the child population to generate a population with a size of 2N, performing non-dominated sorting on the merged population, and calculating the crowding degree of each individual in the merged population, selecting the first N individuals in the merged population according to the non-dominated sorting priority and the crowding degree, to constitute the next generation population, and then executing step S415;

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

[0046] Further, the step S42 comprises:

[0047] Step S421, based on the objective function and constraint condition of the water resource allocation model of the target open pit area multi-source water supply, taking the Pareto frontier solution set as the initial solution set, each solution in the initial solution set corresponds to a water supply scheme of allocating each type of water source to each target water consumption department, calculating the objective function value f(ω) corresponding to each solution, and then executing step S422;

[0048] Step S422, based on the initial solution set, randomly perturbing the initial solution and generating a corresponding new solution, and calculating the objective function value f(ω') corresponding to the new solution, and then executing step S423;

[0049] Step S423, based on f(ω') and f(ω), obtaining the change of the objective function value, i.e. calculating the difference between f(ω') and f(ω), determining whether to accept the new solution according to the acceptance criterion, and then executing S424;

[0050] Step S424, judge whether to meet the iteration number and termination condition, yes, output each type of water source to each target water consumption department each selected water supply allocation scheme, execute step S43;Otherwise, gradually reduce the temperature and reduce the probability of large-scale disturbance, repeat steps S422 to S424.

[0051] Further, in the step S5, the optimal water supply allocation scheme is determined according to the minimum proportion of groundwater, which is used to realize the water supply scheduling of each type of water source to each target water consumption department in the target prediction period.

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

[0053] The open pit area four water resource joint allocation method based on the improved genetic algorithm constructed by the present application can better integrate a large amount of water resources required in the process of normal industrial production, mining area life and surrounding environment ecological protection in open pit area, and combine the requirements of society, ecology, environment and other aspects generated by water resource allocation to jointly allocate multiple water resources, determine the optimal scheme of water quantity allocation comprehensive benefit of each water supply department to each water consumption department by using the improved genetic algorithm, and provide theoretical support for open pit area water resource optimization allocation work. BRIEF DESCRIPTION OF DRAWINGS

[0054] Figure 1 The present application proposes a specific process flow diagram of an open pit area four water resource joint allocation method based on an improved genetic algorithm.

[0055] Figure 2 The model optimization flowchart of the simulated annealing improved genetic algorithm.

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

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

[0058]

[0059] Table 1 is the water intake, transportation and treatment cost of each water source

[0060] Source of water Concentration of pollutants (mg / l) Atmospheric precipitation 0.10 Surface water 0.20 Groundwater 0.15 Mine water 0.18

[0061] Table 2 is the pollutant concentration of each water source

[0062] Water sector Quality requirements (mg / l) Industrial water 0.20 Domestic water 0.14 Ecological water 0.15 Recharge of mining areas 0.16

[0063] Table 3 is the water quality requirement of each water user department

[0064]

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

[0066] Water sector Demand (10 000 m3) Industrial water 1200 Domestic water 1800 Ecological water 1300 Recharge of mining areas 1100

[0067] Table 5 is the water demand of each water user department

[0068] The specific implementation process is as follows:

[0069] Step S1, according to the meteorological data and hydrological data of the target open-pit mine in the target historical period, using the wet and dry level year method, or according to the historical average water supply in the same time range of the target historical period corresponding to the time range of the target prediction period, the total water supply generated by multiple water sources in the target prediction period, i.e. available water, is predicted;

[0070] Step S2, according to the actual water consumption of the target open-pit mine in the target historical period, using the historical average water demand in the same time range of the target historical period corresponding to the time range of the target prediction period, the total water demand of each target water user department of the target open-pit mine in the target prediction period, i.e. water demand, is predicted;

[0071] Step S3, based on the meteorological data and hydrological data of the target open-pit mine in the target historical period, and the actual water consumption, i.e. based on the actual water supply and the actual water consumption of the target open-pit mine in the target historical period, a water resources allocation model for joint water supply of multiple water sources of the target open-pit mine is constructed;

[0072] A water resource allocation model for the joint water supply of multiple water sources in a target open-pit mine has an objective function, which includes an economic objective function f. s (x), expressed in terms of water supply cost; social objective function f e (x), represented by the water supply satisfaction rate; ecological environment objective function f k Let (x) represent the total amount of pollutants, and 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] Where, ρ s ρ e ρ k These represent the weight coefficients of the objective function that considers economic benefits, social benefits, and ecological and environmental benefits, respectively. Let i be the unit cost of water extraction from water source i; This represents the unit cost of transporting water from water source i to water distribution department j; x represents the unit treatment cost of water source i; ij This represents the amount of water allocated from water source i to department j; μ j x is the weighting coefficient of department j; j and D j These represent the actual water supply and demand, respectively; p i Indicates the pollution intensity of water source i; x i This indicates the amount of water taken from water source i.

[0078] The objective function for constructing a water resource allocation model for a combined water supply system from multiple water sources in a target open-pit mine has the following constraints:

[0079] Constraints include water supply capacity, demand satisfaction, water quality requirements, water supply structure, and non-negativity.

[0080] The water supply capacity constraint is:

[0081]

[0082] wherein x ij is the water amount allocated from water source i to department j; S i is the maximum water supply capacity of water source i;

[0083] The demand satisfaction constraint is:

[0084]

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

[0086] The water quality requirement constraint is:

[0087]

[0088] wherein 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 constraint is:

[0090]

[0091] wherein x ij is the water amount allocated from water source i to department j; and respectively represent the minimum and maximum proportions of department j obtained from water source i;

[0092] The non-negativity factor is:

[0093]

[0094] wherein x ij is the water amount allocated from water source i to department j.

[0095] Step S4, based on the available water amount and water demand of the target open-pit mine area in the target prediction period, solve the water resource allocation model of the joint water supply of the target open-pit mine area from multiple water sources, and obtain each candidate water supply allocation scheme about the water supply of each type of water source to each target water use department;

[0096] Optionally, the S4 comprises:

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

[0098] Specifically comprising:

[0099] Step S411, an initial parent population with a size of N is randomly generated, each individual in the population represents a feasible solution, and each feasible solution corresponds to a water supply scheme of allocating various types of water sources to various target water consumption departments, and then step S412 is executed;

[0100] Step S412, the initial parent population is non-dominantly sorted according to the objective function and the constraint condition of the water resource allocation model of the joint water supply of various water sources in the target open-pit mine; subsequently, the individuals in the determined non-dominant layer are subjected to congestion calculation, and then step S413 is executed;

[0101] Step S413, the individuals subjected to the crossover and mutation operations are selected from the initial parent population according to the non-dominant sorting priority and the congestion; subsequently, the selected individuals are subjected to the crossover and mutation operations according to the defined crossover rate and mutation rate, a child population with a size of N is generated, and then step S414 is executed;

[0102] Step S414, the initial parent population and the child population are merged to generate a population with a size of 2N, the merged population is non-dominantly sorted, and the congestion of each individual in the merged population is calculated, the first N individuals in the merged population are selected according to the non-dominant sorting priority and the congestion to constitute a next generation population, and then step S415 is executed;

[0103] Step S415, if the termination condition is met, the Pareto front 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, the Pareto front solution set is locally optimized by using simulated annealing;

[0105] Specifically includes:

[0106] Step S421, based on the objective function and the constraint condition of the water resource allocation model of the joint water supply of various water sources in the target open-pit mine, the Pareto front solution set is taken as an initial solution set, each solution in the initial solution set corresponds to a water supply scheme of allocating various types of water sources to various target water consumption departments, 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 subjected to random disturbance, the disturbance amplitude decreases with the decrease of temperature, the disturbance is larger in the early stage and gradually converges in the later stage, the search range is ensured to be wide, and the local optimal solution trap is avoided at the same time, a new solution corresponding to the disturbance is generated, the objective function value f(ω') corresponding to the new solution is calculated, and then step S423 is executed;

[0108] Step S423, based on f(w') and f(w), obtain the change of the objective function value, i.e. calculate the difference between f(w') and f(w), determine whether to accept the new solution according to the acceptance criterion, i.e. according to the Metropolis criterion: if the change of the objective function value ≤ 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 the initial solution set no longer changes, based on the termination condition, determine whether the iteration number and the termination condition are met, yes, output each candidate water supply allocation scheme of each type of water source to each target water consumption department, the output of each candidate water supply allocation scheme maintains the multi-objective optimization characteristics of the Pareto front solution set, and the precision and stability are also significantly improved; otherwise, gradually reduce the temperature and reduce the probability of large-scale disturbance, and repeat steps S422 to S424.

[0110] Step S43, based on each candidate water supply allocation scheme of each type of water source to each target water consumption department, output the specific value of the objective function corresponding to each candidate water supply allocation scheme.

[0111] After the model operation, a plurality of candidate water supply allocation schemes meeting the objective function and the constraint condition are generated, and the optimal solution with the best comprehensive benefit can be selected as the optimal allocation scheme according to the actual situation. In this embodiment, a better scheme is selected, the economic target (water supply cost) of which is 2741.56 million yuan, the social target (water supply satisfaction rate) is 88.4%, and the ecological target (pollutant minimization) is 1.3×10 9 mg, and the specific allocation scheme is shown in Table 6.

[0112]

[0113] Table 6

[0114] The final result shows that the total cost of water supply to each department is 2741.56 million yuan, and the cost mainly includes the water intake, transportation and treatment fees of each water source, and the specific allocation depends on the amount of water supply from each water source to different departments. The water supply satisfaction rate is 88.4%, of which the industrial water and domestic water guarantee rate is 100%, the ecological water guarantee rate is 90.5%, and the backfill water guarantee rate is 63.2%. Industrial and domestic water are preferentially guaranteed, while backfill water has a lower guarantee rate than other water. The total amount of pollutants is 1.3×10 9 mg, which is calculated according to the water supply amount and the pollutant concentration of the water source. The pollutant emission is controlled within a reasonable range, indicating that the pollutant emission is relatively optimized under the condition of 88.4% water supply satisfaction rate.

[0115] The above is only the preferred embodiment of the present application, and does not limit the present application, and any simple modification, change and equivalent structure change of the above embodiment according to the technical essence of the present application are still within the protection scope of the technical scheme of the present application.

Claims

1. An open-pit mine area four-water resource joint allocation method based on an improved genetic algorithm, characterized in that, The four water resources include atmospheric precipitation, surface water, underground water and pit water. The method is used for scheduling preset water sources of each type in a target open-pit mine area, and realizing distribution of each type of water source among each target water consumption department, and comprises the following steps: In step S1, the total water supply amount of each type of water source in a target prediction period is predicted according to meteorological data and hydrological data of the target open-pit mine area in a target historical period, i.e. available water amount, and then step S2 is executed; In step S2, the total water demand amount of each target water consumption department in the target prediction period is predicted according to actual water consumption amount of the target open-pit mine area in the target historical period, i.e. water demand amount, and then step S3 is executed; In step S3, a water resource allocation model of joint water supply of multiple water sources of the target open-pit mine area is constructed based on the meteorological data and hydrological data and the actual water consumption amount of the target open-pit mine area in the target historical period, and then step S4 is executed; In step S4, the water resource allocation model of joint water supply of multiple water sources of the target open-pit mine area is solved based on the available water amount and the water demand amount of the target open-pit mine area in the target prediction period, and each selected water supply distribution scheme about water supply of each type of water source to each target water consumption department is obtained, and then step S5 is executed; In step S5, an optimal water supply allocation scheme is determined based on each selected water supply distribution scheme, and is used for water supply scheduling of each type of water source to each target water consumption department in the target prediction period; In the step S3, the water resource allocation model of the target open-pit mine area multi-source water supply has a target function, which includes an economic target function f s (x) expressed by water supply cost; a social target function f e (x) expressed by water supply satisfaction rate; and an ecological environment target function f k (x) expressed by total pollutant amount, and the specific target function is: ； ； ； ； wherein, respectively represent the weight coefficients of the objective functions considering economic benefit, social benefit and ecological environmental benefit; is the unit cost of water source i; represents the unit cost of water delivery from water source i to water distribution department j; is the unit treatment cost of water source i; represents the water quantity allocated from water source i to department j; is the weight coefficient of department j; and respectively represent the actual water supply quantity and demand quantity; represents the pollution intensity of water source i; represents the water quantity taken from water source i; Further, based on the supply-demand water data relationship in the target historical period, the objective function comprises the following constraint conditions: water supply capacity constraint, demand satisfaction constraint, water quality requirement constraint, water supply structure constraint and non-negativity constraint. Specifically, the water supply capacity constraint is: ； wherein, is the maximum water supply capacity of the water source i; The demand satisfaction constraint is: ； wherein, is the minimum water demand for department j; The water quality requirement constraint is: ； wherein, is the water quality index of the water source i; is the water quality requirement of the department j; The water supply structure constraint is: ； where, and min and max represent the minimum and maximum proportion of water source i that department j can obtain, respectively; The non-negativity constraint is: 。 2. The method according to claim 1, wherein, In the step S1, the total water supply amount of each type of water source in the target prediction period is predicted according to the rich and poor level year method.

3. The method according to claim 1, wherein, In the step S2, the total water demand amount of each target water consumption department in the target prediction period is predicted according to the average value method.

4. The method according to any one of claims 1-3, characterized in that, The step S4 comprises: In step S41, the water resource allocation model of joint water supply of multiple water sources of the target open-pit mine area is solved by using the NSGA-II algorithm to obtain a Pareto frontier solution set, and then step S42 is executed; In step S42, the Pareto frontier solution set is locally optimized by using simulated annealing, and then step S43 is executed; In step S43, each selected water supply distribution scheme about water supply of each type of water source to each target water consumption department is outputted, and specific numerical values of the objective function corresponding to each selected water supply distribution scheme are outputted.

5. The method according to claim 4, wherein, The step S41 comprises: In step S411, an initial parent population with a size of N is randomly generated, each individual in the population represents a feasible solution, and each feasible solution corresponds to a water supply scheme of distributing each type of water source to each target water consumption department, and then step S412 is executed; Step S412, according to the objective function and constraint condition of the water resource allocation model of the target open-pit mine area multi-source water supply, non-dominated sorting is performed on the initial parent population; then, the individuals in the determined non-dominated layer are subjected to congestion calculation, and then step S413 is executed; Step S413, according to the non-dominated sorting priority and congestion, individuals subjected to cross and mutation operations are selected from the initial parent population; then, according to the defined cross rate and mutation rate, cross and mutation operations are performed on the selected individuals to generate a child population with a size of N, and then step S414 is executed; Step S414, the initial parent population and the child population are merged to generate a population with a size of 2N, non-dominated sorting is performed on the merged population, the congestion of each individual in the merged population is calculated, the first N individuals in the merged population are selected according to the non-dominated sorting priority and the congestion to constitute the next generation population, and then step S415 is executed; Step S415, if the termination condition is met, the Pareto front 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.

6. The method according to claim 4, wherein, The step S42 comprises: In step S421, based on the objective function and constraint condition of the water resource allocation model of the joint water supply of the multiple water sources of the target open-pit mine area, an initial solution set is calculated by using the Pareto front solution set, each solution in the initial solution set corresponds to a water supply scheme of allocating each type of water source to each target water consumption department, and the objective function value corresponding to each solution is calculated Then, step S422 is performed. Step S422, based on the initial solution set, randomly perturbing the initial solution, and generating a corresponding new solution, and calculating the objective function value corresponding to the new solution Step S423 is then performed; Step S423, based on and To obtain the change in the objective function value, i.e., to calculate and The difference is used to determine whether to accept the new solution based on the acceptance criteria, and then S424 is executed; Step S424, it is judged whether the iteration number and the termination condition are met, if yes, the selected water supply allocation scheme of each type of water source to each target water consumption department is output, and step S43 is executed; otherwise, the temperature is gradually reduced, the large-scale disturbance probability is reduced, and steps S422 to S424 are repeatedly executed.

7. The method according to claim 1, wherein, In the step S5, the optimal water supply allocation scheme is determined according to the minimum proportion of groundwater, which is used for water supply scheduling of each type of water source to each target water consumption department in the target prediction period.

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