Tractor head and battery platform scheduling method

Abstract

The present invention discloses a method for dispatching a tractor head and a battery platform, comprising the following steps: Step 1, a moored ship sends a power supply request and a battery recycling request to a port service platform, and the service platform receives the requests and enters the corresponding information; Step 2, establish a situation model of moored ships at sea; Step 3, the port service platform groups the moored ships, and determines the required number of tractor heads and battery platforms within the group according to the grouping situation and the number of ships in the group that need power supply and battery recycling; Step 4, use the Dijkstra algorithm to calculate the optimal navigation path of the tractor head corresponding to each group, and construct the optimal path and constraint conditions when the tractor heads to be dispatched complete the power supply and recycling of all moored ships in the groups; Step 5, the tractor heads tow the battery platforms according to the optimal navigation path constructed by the Dijkstra algorithm to execute the tasks assigned by the port service platform.

Description

Technical Field

[0001] The present invention relates to the technical field of artificial intelligence, and more particularly to a method for dispatching a tractor head and a battery platform. Background Art

[0002] In recent years, with the rapid development of technologies such as the Internet of Things, big data, and cloud computing, power supply to and battery recycling of intelligent moored ships have received extensive attention. In the face of the complex marine navigation environment, on the premise of ensuring maritime navigation safety and economy, how to quickly plan an optimal route from the starting point to the end point that can supply power and recycle batteries to all moored ships for the tractor head to drive the battery platform in the navigation sea area in a short time has become a hot research issue for scholars.

[0003] Currently, many researchers have proposed various optimal route plans from various aspects. For example, invention application CN202111424412.4 proposes a method for dispatching port ships, invention application CN202110285951.8 proposes a ship dispatching method based on port berth resources, invention application CN201910151047.0 proposes a method for planning a ship navigation route, etc. All of them can find the optimal route for the ship from the starting point to the end point, but relying on human resources and the total waiting time of the ship is still too long, resulting in low efficiency. Therefore, the dispatching method needs to be optimized. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide an efficient method for dispatching a tractor head and a battery platform.

[0005] To solve the above technical problem, the technical solution adopted by the present invention is: a method for dispatching a tractor head and a battery platform, comprising the following steps:

[0006] Step 1, the moored ship sends a power supply request and a battery recycling request to the port service platform, and the service platform receives the request and enters the corresponding information.

[0007] Step 2, establish a model of the situation of moored ships at sea: take the intersection point of the horizontal extension line of the port service platform and the vertical extension line of the charging pile as the origin O, the connection line between the origin O and the port service platform as the Ox axis, and the connection line between the origin O and the charging pile as the Oy axis to establish a plane rectangular coordinate system O-xy, and determine the specific position coordinates of each moored ship.

[0008] Step 3, the port service platform groups the moored ships, and determines the number of tractor heads and battery platforms required in the group according to the grouping situation and the number of ships in the group that need power supply and battery recycling.

[0009] Step 4: Use the Dijkstra algorithm to calculate the optimal sailing path of the tugboat corresponding to each group, and construct the optimal path and constraints for the tugboats to be scheduled when supplying power to and recycling the berthed ships in all groups.

[0010] 1) Constraints: Battery platform quantity limit condition: The number of tugboats dispatched at one time is 1, and the number of battery platforms towed by 1 tugboat is 5.

[0011] Sailing path condition of the tugboat: First, the tugboat tows the battery platform to the positions of all the ships in the group that need power supply, then sails to the positions of all the ships that need battery recycling, and then sails to the charging pile position.

[0012] 2) In each group, by calculating the distance between the starting tugboat and the ships that need power supply, select the ship that needs power supply and is the closest to the starting tugboat and denote it as p 11 , and continue to select the ship that needs power supply and is the closest to p 11 and denote it as p 12 , and continue to select the ship that needs power supply and is the closest to p 12 and denote it as p 13 , … Repeat this process until all the ships that need power supply in the p i group are found, and denote the last ship that needs power supply found as p 1n ;

[0013] Then, find the ship that needs battery recycling and is the closest to the ship that needs power supply p 1n and denote it as p 21 , and then select the ship that needs battery recycling and is the closest to p 21 and denote it as p 22 , … Repeat this process until all the ships that need battery recycling in the p i group are found, and denote the last ship that needs battery recycling found as p 2m , and then calculate the straight-line distance from the ship that needs battery recycling p 2m to the end charging pile.

[0014] 3) Take the starting tugboat, each berthed ship, and the end charging pile position as nodes. In the first-round iteration process, find and mark the first-level node in the p i group that is the closest to the starting tugboat. In the second-round iteration process, find and mark the corresponding second-level node in the p i group that is the closest to each first-level node for the remaining unmarked nodes, … And so on. These nodes found in each round of iteration process and the starting tugboat are collectively called the solved nodes, and the rest are called the unsolved nodes. Calculate the connection distances between each solved node and one or more unsolved nodes, and denote the point with the shortest connection distance as the candidate point.

[0015] 4) Accumulate the distance between each solved node and its candidate points to the distance of the optimal path between the solved node and the starting tractor head, and finally obtain the path with the shortest overall distance, which is the optimal navigation path;

[0016] Step 5: The tractor head tow the battery platform according to the optimal navigation path constructed by the Dijkstra algorithm to execute the tasks assigned by the port service platform.

[0017] As a preferred solution, the specific operation of step 3 is as follows: Consider three non-collinear moored ships as three non-collinear points, thus forming a triangle. Use the method of drawing a circumcircle to group the ships. In the plane rectangular coordinate system O-xy, let the coordinates of these three points be (x1, y1), (x2, y2), and (x3, y3) respectively, the center of the circle is denoted as O1, the coordinates are set as (x4, y4), and the radius is denoted as r1. The equation of this circle is (x - x4) 2 +(y - y4) 2 = r1 2 ,

[0018] where a1 = x1 - x2, b1 = y1 - y2, c1 = x1 - x3, d1 = y1 - y3, Count the moored ships within the circle with O1 as the center and r1 as the radius. If the minimum value of the number of ships requiring power supply and the number of ships requiring battery recycling in the group is not less than 4 / 5 times the upper limit of the number of battery platforms to be dispatched, that is, not less than 4 / 5 * 5k, and the maximum value of the number of ships requiring power supply and the number of ships requiring battery recycling in the group does not exceed the upper limit of 5k of the number of battery platforms to be dispatched, it is denoted as group p1;

[0019] Then consider another three non-collinear moored ships as three non-collinear points, thus forming a triangle. Let the coordinates of these three points be (x5, y5), (x6, y6), and (x7, y7) respectively, the center of the circle is denoted as O2, the coordinates are set as (x8, y8), and the radius is denoted as r2. Then the equation of this circle is (x - x8) 2 +(y - y8) 2 = r2 2 , and calculate the position of the center of the circle and the size of the radius. where a2 = x5 - x6, b2 = y5 - y6, c2 = x5 - x7, d2 = y5 - y7, Count the berthing ships within the circle with O2 as the center and r2 as the radius. If the minimum of the number of ships requiring power supply and the number of ships requiring battery recycling in the group is not less than 4 / 5 times the upper limit of the number of battery platforms to be dispatched, that is, not less than 4 / 5 * 5k, and the maximum of the number of ships requiring power supply and the number of ships requiring battery recycling in the group does not exceed the upper limit of 5k of the battery platforms to be dispatched, it is recorded as group p2;

[0020] Group in this way by analogy. If there are overlapping berthing ships between groups, according to the principle of proximity, the berthing ship is counted into the group whose center the berthing ship is closest to; until all berthing ships are counted, a total of p h groups are obtained;

[0021] As another preferred solution, step 3 is specifically as follows: Group the ships by using the arc-drawing method. Take the intersection of the horizontal extension line of the port service platform and the vertical extension line of the charging pile as the origin O. Take the origin O as the center, and first draw an arc with a radius of r1'. The size of r1' is (1 + 0.5i / 2 Mi ) times the distance between the center and the closest berthing ship to the center. i is the serial number of the arc to be determined, and Mi is the number of times of re-grouping to obtain the i-th arc that meets the conditions. Count the number of berthing ships within the arc with a radius of r1'. If the maximum of the number of ships requiring power supply and the number of ships requiring battery recycling in the group exceeds the upper limit of 5k of the battery platforms to be dispatched, then abandon this group and adjust the size of r1' and re-group until the maximum of the number of ships requiring power supply and the number of ships requiring battery recycling in the group does not exceed the upper limit of 5k of the battery platforms to be dispatched, and it is recorded as group p1;

[0022] Then take the origin O as the center and draw an arc with a radius of r2'. The size of r2' is (1 + 0.5i / 2 Mi ) times the distance between the center and the closest berthing ship to the center. i is the serial number of the arc to be determined, and Mi is the number of times of re-grouping to obtain the i-th arc that meets the conditions. Count the number of berthing ships within the arc segment between the arc with a radius of r1' and the arc with a radius of r2'. If the maximum of the number of ships requiring power supply and the number of ships requiring battery recycling in the group exceeds the upper limit of 5k of the battery platforms to be dispatched, then abandon this group and adjust the size of r2' and re-group until the maximum of the number of ships requiring power supply and the number of ships requiring battery recycling in the group does not exceed the upper limit of 5k of the battery platforms to be dispatched, and it is recorded as group p2;

[0023] Group in this way by analogy until all berthing ships are counted, and a total of p h groups are obtained.

[0024] The beneficial effects of the present invention are:

[0025] This method establishes a model of the situation of ships at anchor at sea. The port service platform groups the anchored ships, and determines the number of tugboats and battery platforms required within the group according to the grouping situation and the number of ships in the group that need power supply and battery recycling. The Dijkstra algorithm is used to calculate the optimal navigation path of the tugboat. In cooperation with the grouping method, it helps to reduce the navigation path and time, enabling the tugboat to sail to the anchored ship more quickly and return to the terminal charging pile rapidly.

[0026] The method of grouping ships by drawing circles or arcs is different from the traditional mode without grouping, which is more targeted and convenient for management, making the tugboats dispatched by the service platform serve the anchored ships in need more purposefully; it shortens the waiting time of the ships in need, improving the efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a flow chart of the tugboat and battery platform scheduling method of the present invention.

[0028] Figure 2 It is a schematic diagram of the principle of circle grouping of the present invention.

[0029] Figure 3 It is a schematic diagram of the principle of arc grouping of the present invention.

[0030] Figure 4 It is a schematic diagram of the principle of the Dijkstra algorithm of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0031] The following combines the drawings to describe the specific implementation of the present invention in detail.

[0032] A tugboat and battery platform scheduling method includes the following steps:

[0033] Step 1, as Figure 1 shown, the anchored ship sends a power supply request and a battery recycling request to the port service platform, and the service platform receives the request and enters the corresponding information;

[0034] Step 2, establish a model of the situation of ships at anchor at sea: Take the intersection of the horizontal extension line of the port service platform and the vertical extension line of the charging pile as the origin O, the connection line between the origin O and the port service platform as the Ox axis, and the connection line between the origin O and the charging pile as the Oy axis to establish a plane rectangular coordinate system O-xy, and determine the specific position coordinates of each anchored ship;

[0035] Step 3, the port service platform groups the anchored ships, and determines the number of tugboats and battery platforms required within the group according to the grouping situation and the number of ships in the group that need power supply and battery recycling;

[0036] As Figure 2As shown, the specific solution that can be adopted in step 3 can be: regarding three non-collinear moored ships as three non-collinear points, thus forming a triangle, and using the method of drawing a circumcircle to group the ships. In the plane rectangular coordinate system O-xy, let the coordinates of these three points be (x1, y1), (x2, y2), and (x3, y3) respectively. Denote the center of the circle as O1, the coordinates as (x4, y4), and the radius as r1. The equation of this circle is (x - x4) 2 +(y - y4) 2 = r1 2 , where a1 = x1 - x2, b1 = y1 - y2, c1 = x1 - x3, d1 = y1 - y3, Count the moored ships within the circle with O1 as the center and r1 as the radius. If the minimum of the number of ships requiring power supply and the number of ships requiring battery recycling within the group is not less than 4 / 5 times the upper limit of the number of battery platforms to be dispatched, that is, not less than 4 / 5 * 5k, and the maximum of the number of ships requiring power supply and the number of ships requiring battery recycling within the group does not exceed the upper limit of the number of battery platforms to be dispatched, which is 5k, it is denoted as group p1;

[0037] Then regard another three non-collinear moored ships as three non-collinear points, thus forming a triangle. Let the coordinates of these three points be (x5, y5), (x6, y6), and (x7, y7) respectively. Denote the center of the circle as O2, the coordinates as (x8, y8), and the radius as r2. Then the equation of this circle is (x - x8) 2 +(y - y8) 2 = r2 2 , and calculate the position of the center of the circle and the size of the radius through calculation,

[0038] where a2 = x5 - x6, b2 = y5 - y6, c2 = x5 - x7, d2 = y5 - y7, Count the moored ships within the circle with O2 as the center and r2 as the radius. If the minimum of the number of ships requiring power supply and the number of ships requiring battery recycling within the group is not less than 4 / 5 times the upper limit of the number of battery platforms to be dispatched, that is, not less than 4 / 5 * 5k, and the maximum of the number of ships requiring power supply and the number of ships requiring battery recycling within the group does not exceed the upper limit of the number of battery platforms to be dispatched, which is 5k, then it is denoted as group p2;

[0039] And so on for grouping. If there are overlapping moored ships between groups, then according to the principle of proximity, the moored ship is counted into the group to which the moored ship is closest to the center of the circle; until all moored ships are counted, a total of p h groups are obtained;

[0040] For exampleFigure 3 As shown in the figure, the specific solution that can be adopted in step 3 is as follows: Group the ships by using the arc-drawing method. Take the intersection point of the horizontal extension line of the port service platform and the vertical extension line of the charging pile as the origin O. Take the origin O as the center of the circle. First, draw an arc with a radius of r1'. The size of r1' is (1 + 0.5i / 2 Mi ) times the distance between the center of the circle and the nearest moored ship to the center of the circle. i is the serial number of the arc to be determined, and Mi is the number of times of re-grouping to obtain the i-th arc that meets the conditions. Count the number of moored ships within the arc with a radius of r1'. If the maximum number of ships requiring power supply and the number of ships requiring battery recycling in the group exceeds the upper limit 5k of the battery platforms to be dispatched, then abandon this group and adjust the size of r1' and re-group until the maximum number of ships requiring power supply and the number of ships requiring battery recycling in the group does not exceed the upper limit 5k of the battery platforms to be dispatched, and record it as group p1;

[0041] Then, take the origin O as the center of the circle and draw an arc with a radius of r2'. The size of r2' is (1 + 0.5i / 2 Mi ) times the distance between the center of the circle and the nearest moored ship to the center of the circle. I is the serial number of the arc to be determined, and Mi is the number of times of re-grouping to obtain the i-th arc that meets the conditions. Count the number of moored ships within the arc segment between the arc with a radius of r1' and the arc with a radius of r2'. If the maximum number of ships requiring power supply and the number of ships requiring battery recycling in the group exceeds the upper limit 5k of the battery platforms to be dispatched, then abandon this group and adjust the size of r2' and re-group until the maximum number of ships requiring power supply and the number of ships requiring battery recycling in the group does not exceed the upper limit 5k of the battery platforms to be dispatched, and record it as group p2;

[0042] And so on for grouping until all moored ships are counted, and a total of p h groups are obtained.

[0043] Step 4, as Figure 4 shown, use the Dijkstra algorithm to calculate the optimal navigation path of the tugboat corresponding to each group, and construct the optimal path and constraint conditions when the tugboats to be dispatched complete the power supply and recycling of all moored ships in the groups;

[0044] 1) Constraint conditions: Battery platform quantity limit condition: The number of tugboats dispatched at one time is 1, and the number of battery platforms towed by 1 tugboat is 5;

[0045] Navigation path condition of the tugboat: First, the tugboat tows the battery platform and sails to the positions of all ships requiring power supply in the group, then sails to the positions of all ships requiring battery recycling, and then sails to the charging pile position;

[0046] 2) In each group, by calculating the distance between the starting tugboat and the ships to be powered, select the ship to be powered that is closest to the starting tugboat and denote it as p 11 , and continue to select, by calculation, the ship to be powered that is closest to p 11 and denote it as p 12 , and continue to select, by calculation, the ship to be powered that is closest to p 12 and denote it as p 13 , … Repeat this process until all the ships to be powered in the p i group are found, and denote the last ship to be powered found as p 1n ;

[0047] Next, find the ship for battery recycling that is closest to the ship to be powered p 1n and denote it as p 21 , and then select, by calculation, the ship for battery recycling that is closest to p 21 and denote it as p 22 , … Repeat this process until all the ships for battery recycling in the p i group are found, and denote the last ship for battery recycling found as p 2m , and then calculate the straight-line distance from the ship for battery recycling p 2m to the end charging pile;

[0048] 3) Take the position of the starting tugboat, each moored ship, and the end charging pile as nodes. In the first-round iteration process, find and mark the first-level node in the p i group that is closest to the starting tugboat. For the remaining unmarked nodes, find and mark the corresponding second-level nodes in the p i group that are closest to each first-level node in the second-round iteration process, … And so on. These nodes found in each round of iteration process and the starting tugboat are collectively called the solved nodes, and the rest are called the unsolved nodes. Calculate the connection distance between each solved node and one or more unsolved nodes. The point with the shortest connection distance is denoted as the candidate point;

[0049] 4) Add the distance between each solved node and its candidate point to the distance of the optimal path between the solved node and the starting tugboat. Finally, obtain the path with the shortest overall distance, which is the optimal navigation path;

[0050] Step 5, the tugboat tow the battery platform according to the optimal navigation path constructed by the Dijkstra algorithm to execute the tasks assigned by the port service platform.

[0051] The above embodiments are only illustrative of the principles and effects of the present invention and some of the embodiments in which they are applied, and are not intended to limit the present invention. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can be made, and these all fall within the protection scope of the present invention.

Claims

1. A method for dispatching a tractor head and a battery platform, comprising the following steps: Step 1, the berthed ship sends a power supply request and a battery recycling request to the port service platform, and the service platform receives the requests and enters the corresponding information; Step 2, establish a model of the situation of berthed ships at sea: take the intersection of the horizontal extension line of the port service platform and the vertical extension line of the charging pile as the origin O, the connection line between the origin O and the port service platform as the Ox axis, and the connection line between the origin O and the charging pile as the Oy axis, establish a plane rectangular coordinate system O-xy, and determine the specific position coordinates of each berthed ship; Step 3, the port service platform groups the berthed ships, and determines the number of tractor heads and battery platforms required in the group according to the grouping situation and the number of ships in the group that need power supply and battery recycling; Step 4, use the Dijkstra algorithm to calculate the optimal navigation path of the tractor head corresponding to each group, and construct the optimal path and constraint conditions when the tractor head to be dispatched completes the power supply and recycling of all berthed ships in all groups; 1) Constraint conditions: Battery platform quantity limit condition: The number of tractor heads dispatched at one time is 1, and the number of battery platforms towed by 1 tractor head is 5; Navigation path condition of the tractor head: First, the tractor head tows the battery platform and sails to the positions of all ships in the group that need power supply, and then sails to the positions of all ships that need battery recycling, and then sails to the position of the charging pile; 2) In each group, by calculating the distance between the starting tugboat and the vessel to be powered, select the vessel to be powered that is closest to the starting tugboat and denote it as p 11 , and continue to select, by calculation, the vessel to be powered that is closest to p 11 and denote it as p 12 , and continue to select, by calculation, the vessel to be powered that is closest to p 12 and denote it as p 13 , … Repeat this process until all the vessels to be powered in the p i group are found, and denote the last vessel to be powered found as p 1n ; Next, find the ship that needs battery recycling among them and is the closest to the ship p that needs to be powered 1n The ship that needs battery recycling and is the closest is denoted as p 21 , and then select the ship that needs battery recycling and is the closest to p 21 The ship that needs battery recycling and is the closest is denoted as p 22 , … Repeat this process until all the ships that need battery recycling within the p i group are found. Denote the last ship that needs battery recycling as p 2m , and then calculate the straight-line distance from the ship p 2m that needs battery recycling to the end charging pile; 3) Take the starting tractor head, each berthed ship, and the position of the end charging pile as nodes, and find and label the p nodes within the first round of iteration that are the first-level nodes closest to the starting tractor head within the group. For the remaining unlabeled nodes, find and label the corresponding second-level nodes closest to each first-level node within the second round of iteration, and so on. These nodes found in each round of iteration and the starting tractor head are collectively called the solved nodes, and the rest are called the unsolved nodes. Calculate the connection distances between each solved node and one or more unsolved nodes directly, and the point with the shortest connection distance is recorded as the candidate point; i The first-level nodes closest to the starting tractor head within the group. For the remaining unlabeled nodes, find and label the p nodes within the second round of iteration that are the corresponding second-level nodes closest to each first-level node within the group, and so on. These nodes found in each round of iteration and the starting tractor head are collectively called the solved nodes, and the rest are called the unsolved nodes. Calculate the connection distances between each solved node and one or more unsolved nodes directly, and the point with the shortest connection distance is recorded as the candidate point; i The first-level nodes closest to the starting tractor head within the group. For the remaining unlabeled nodes, find and label the corresponding second-level nodes closest to each first-level node within the second round of iteration, and so on. These nodes found in each round of iteration and the starting tractor head are collectively called the solved nodes, and the rest are called the unsolved nodes. Calculate the connection distances between each solved node and one or more unsolved nodes directly, and the point with the shortest connection distance is recorded as the candidate point; 4) Accumulate the distance between each solved node and its candidate point to the distance of the optimal path between the solved node and the starting tractor head, and finally obtain the path with the shortest overall distance, that is, the optimal navigation path; Step 5, the tractor head tows the battery platform and executes the tasks assigned by the port service platform according to the optimal navigation path constructed by the Dijkstra algorithm.

2. The trailer head and battery platform scheduling method according to claim 1, characterized in that: The specific content of step 3 is as follows: Regarding three non-collinear moored ships as three non-collinear points, thus forming a triangle, and using the method of drawing a circumcircle to group the ships. In the plane rectangular coordinate system O-xy, assume the coordinates of these three points are (x1, y1), (x2, y2), and (x3, y3) respectively, the center of the circle is denoted as O1, the coordinates are set as (x4, y4), and the radius is denoted as r1. The equation of this circle is (x - x4) 2 +(y - y4) 2 = r1 2 , where a1 = x1 - x2, b1 = y1 - y2, c1 = x1 - x3, d1 = y1 - y3, Count the moored ships within the circle with O1 as the center and r1 as the radius. If the minimum of the number of ships requiring power supply and the number of ships requiring battery recycling in the group is not less than 4 / 5 times the upper limit of the number of battery platforms to be dispatched, that is, not less than 4 / 5 * 5k, and the maximum of the number of ships requiring power supply and the number of ships requiring battery recycling in the group does not exceed the upper limit of 5k of the number of battery platforms to be dispatched, it is denoted as group p1; Regarding the other three non - collinear moored ships as three non - collinear points, a triangle is thus formed. Let the coordinates of these three points be \((x_5,y_5)\), \((x_6,y_6)\), \((x_7,y_7)\) respectively. Denote the center of the circle as \(O_2\), with coordinates set as \((x_8,y_8)\) and the radius as \(r_2\). Then the equation of this circle is \((x - x_8) 2 +(y - y_8) 2 =r_2 2 . By calculation, the position of the center of the circle and the magnitude of the radius are obtained. where \(a_2=x_5 - x_6\), \(b_2=y_5 - y_6\), \(c_2=x_5 - x_7\), \(d_2=y_5 - y_7\). Count the moored ships within the circle with \(O_2\) as the center and \(r_2\) as the radius. If the minimum of the number of ships requiring power supply and the number of ships requiring battery recycling within the group is not less than 4 / 5 times the upper limit of the number of battery platforms for scheduling, that is, not less than 4 / 5 * 5k, and the maximum of the number of ships requiring power supply and the number of ships requiring battery recycling within the group does not exceed the upper limit of the number of battery platforms for scheduling, 5k, then it is recorded as group \(p_2\). Grouping is carried out in this way. If there are overlapping moored ships between groups, then according to the principle of proximity, the moored ship is counted into the group whose center of the circle is the closest to the moored ship; until all moored ships are counted, a total of p h groups are obtained.

3. The trailer head and battery platform scheduling method according to claim 1, characterized in that: The specific steps of step 3 are as follows: Group the ships by using the arc-drawing method. Take the intersection point of the horizontal extension line of the port service platform and the vertical extension line of the charging pile as the origin O. With the origin O as the center, first draw an arc with a radius of r1'. The size of r1' is (1 + 0.5i / 2 Mi ) times the distance between the center and the nearest moored ship to the center. Here, i is the serial number of the arc to be determined, and Mi is the number of times of re-grouping to obtain the i-th arc that meets the conditions. Count the number of moored ships within the arc with a radius of r1'. If the maximum value among the number of ships requiring power supply and the number of ships requiring battery recycling in the group exceeds the upper limit 5k of the number of battery platforms for scheduling, then abandon this group, adjust the size of r1' and re-group until the maximum value among the number of ships requiring power supply and the number of ships requiring battery recycling in the group does not exceed the upper limit 5k of the number of battery platforms for scheduling, and then record it as group p1; Then, taking the origin O as the center, draw an arc with a radius of r2'. The size of r2' is (1 + 0.5i / 2) times the distance from the center to the nearest moored ship, where i is the serial number of the arc to be determined, and Mi is the number of regroupings for obtaining the i-th arc that meets the conditions. Count the number of moored ships within the arc segment between the arc with a radius of r1' and the arc with a radius of r2'. If the maximum value among the number of ships requiring power supply and the number of ships requiring battery recycling within the group exceeds the upper limit 5k of the battery platforms for scheduling, then after abandoning this group, adjust the size of r2' and regroup until the maximum value among the number of ships requiring power supply and the number of ships requiring battery recycling within the group does not exceed the upper limit 5k of the battery platforms for scheduling, which is denoted as group p2; Mi ) times, where i is the serial number of the arc to be determined, Mi is the number of regroupings for obtaining the i-th arc that meets the conditions. Count the number of moored ships within the arc segment between the arc with a radius of r1' and the arc with a radius of r2'. If the maximum value among the number of ships requiring power supply and the number of ships requiring battery recycling within the group exceeds the upper limit 5k of the battery platforms for scheduling, then after abandoning this group, adjust the size of r2' and regroup until the maximum value among the number of ships requiring power supply and the number of ships requiring battery recycling within the group does not exceed the upper limit 5k of the battery platforms for scheduling, which is denoted as group p2; Group in this way until all the berthed ships are counted, and a total of p h groups are obtained.

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