CN106844986B

CN106844986B - Deck layout calculation method based on improved genetic algorithm

Info

Publication number: CN106844986B
Application number: CN201710066422.2A
Authority: CN
Inventors: 丁立; 张玉梅; 谢军伟; 张文博; 迟迎
Original assignee: NO 701 INST CHINA SHIPPING HEA; Beihang University
Current assignee: NO 701 INST CHINA SHIPPING HEA; Beihang University
Priority date: 2017-01-24
Filing date: 2017-01-24
Publication date: 2020-06-05
Anticipated expiration: 2037-01-24
Also published as: CN106844986A

Abstract

The invention relates to an algorithm for optimizing deck layout based on ship characteristics and considering multi-person cooperative operation flow and deck occupation area. The deck layout optimization comprises 3 components: equipment and obstacles on the deck, a plurality of operations and operation sequence flows, wherein each operation involves an operator. And setting corresponding centroids, placing intervals, operation time sequences and optimization targets through mathematical description of equipment and obstacles in the layout, and performing deck layout optimization calculation containing human body operation characteristics to obtain the optimized deck layout based on the ship characteristics.

Description

Deck layout calculation method based on improved genetic algorithm

Technical Field

The invention belongs to the field of man-machine interaction, and particularly relates to a calculation method for optimizing the layout of deck equipment in a ship basic workflow.

Background

The deck is a platform for bearing a plurality of operations on the ship, different operations can be carried out on the deck at different times, and the content and the number of people in the operations are various. However, the deck area is limited, the operation requirements of all tasks are difficult to meet, how to optimize the ship deck layout and improve the deck utilization rate are very concerned by the existing ship designers. And the existing deck layout or space layout method does not consider the optimization of the working capacity of the containing person. The invention aims to provide a deck layout calculation method considering multi-person cooperative operation and an operation process based on ship characteristics, which is used for optimizing deck equipment layout.

Disclosure of Invention

The invention aims to provide a deck layout calculation method based on ship characteristics and considering multi-person cooperative operation and an operation process, and the deck layout calculation method is used for optimizing the deck equipment layout of a ship.

A deck layout calculation method is disclosed, wherein the deck layout optimization comprises the following components: equipment and obstacles on the deck, a plurality of operations and operation sequence flows, wherein each operation involves an operator. And performing deck layout optimization calculation on the elements.

The calculation steps are as follows:

1) the mathematical description of the equipment and the obstacles in the layout comprises the steps of mapping all the equipment and the obstacles on a deck plane with a given shape, manually drawing the equipment and the obstacles into a closed polygon in a manual drawing mode, and representing the complete equipment plane shape by using the minimum points as much as possible.

2) And (3) calculating the centroid: and calculating the gravity center of the polygon by using the principle of calculating the gravity center of the graph by using geometric integration, wherein the gravity center is taken as the centroid of the equipment or the obstacle.

3) And (3) setting coordinates: and numbering each device and each obstacle, and forming a sequence of relative coordinates of vertexes and centroids of each device and each obstacle clockwise by taking the centroids of the devices and the obstacles as coordinate origins.

4) Setting a device placement interval: and setting the position interval of each device allowed to be placed on the deck according to the actual requirements of the ship operation tasks.

5) Obstacle position setting: and setting the position of the obstacle influencing the walking path of the operator according to the actual requirements of the ship operation task.

6) Setting the time sequence: the sequence of activity, duration and number of workers for any particular task are represented visually by a task element list and time scale based on a time ordered matrix, taking into account the sequence of task flow and the workers involved, according to the job requirements. Referring to fig. 1, the sequence and duration of any particular task activity is represented visually by a list of task elements and a time scale, based on a time-ordered matrix a, essentially a graph of line segments, with the abscissa representing time and the ordinate representing activity (task elements), which visually indicates when the task elements are performing. The mathematical model is as follows:

arranging the task units A1 and A2 … in a task module A into a column vector according to the time sequence:

where 1, 2, and 3 … are the order in which sequential tasks occur, and each Ai represents a row vector containing elements indicating the parallel tasks that are allowed to occur during the period in which the ith task occurs, then for matrix a, the order from top to bottom represents the sequential relationship of the sequential tasks, and the elements in each row represent the parallel tasks corresponding to that period. Specifying that if a parallel task exists in Ai, the parallel task is Aij; if there are no parallel tasks, it is represented by 0. Therefore, the number of columns of A is determined by the row with the most parallel tasks.

Assuming that there are 6 sequential tasks, denoted as a1, a2, A3, a4, a5, a6, and no parallel tasks, the timing permutation matrix is as follows:

7) design of optimization objectives: (a) after all the operation tasks are completed, the sum of the distances that all the operators successively pass to different devices is the minimum; (b) the occupied area of all equipment placed on the deck is the smallest.

8) Deck layout calculation: randomly generating a population of equipment arrangement on a deck by adopting a genetic algorithm, requiring the distance between all the equipment to accord with the human body operation range, and calculating all operation paths and the equipment occupation area according to the operation flow; generating a new operator according to a genetic variation method of a genetic algorithm on the basis to obtain a new population, calculating a new operation path and an equipment occupation area of the new population, and judging whether constraint conditions are met according to a set target; through repeated variation until new individuals meeting the constraint condition are generated.

9) Termination conditions of the algorithm: in general, the algorithm has a mutation probability of 0.01 and the number of iterations is 5000, and the number of iterations may be increased according to the actual calculation accuracy requirement.

The invention has the following effects:

1. through the combination of the traditional genetic algorithm and the operation task flow, the calculated deck layout is more in line with the actual operation rule on the deck.

2. The traditional genetic algorithm is combined with the walking path of a person to calculate, the deck layout is obtained, the design level of the deck layout of the ship can be obviously improved, and a designer can quantitatively know the design effect.

Drawings

FIG. 1 is a task flow Gantt chart showing the sequence and duration of activity for any particular task provided by the present invention;

FIG. 2 is a diagram illustrating exemplary results of an algorithm for locating devices according to the present invention;

1. a device 1; 2. a device 2; 3. a device 3; 4. a device 4; 5. a device 5; 6. a device 6; 7. an obstacle 7;

FIG. 3 is an iterative graph of the algorithm evolution process, which is the change of the fitness function value in the population evolution process provided by the present invention.

Detailed Description

The deck layout calculation method comprises the following components: equipment and obstacles on the deck, a plurality of operations and operation sequence flows, wherein each operation involves an operator. And performing deck layout optimization calculation on the elements. Comprises the following calculation steps:

1) the mathematical description of the equipment and the obstacles in the layout comprises the steps of mapping all the equipment and the obstacles on a deck plane with a given shape, manually drawing the equipment and the obstacles into a closed polygon in a manual drawing mode, and representing the complete equipment plane shape by using the minimum points as much as possible. The devices 1-6 and the obstacles 7 as in fig. 2 are simplified polygons.

3) Setting device coordinates: each device is numbered with the device and obstacle centroids as the origin of coordinates and the relative coordinates of the device and obstacle vertices and centroids are numbered clockwise such as S1 { (1.5 ), (1.5, -1.5), (-1.5 ), (-1.5,1.5) }, where (1.5 ), (1.5, -1.5), (-1.5 ) and (-1.5,1.5) are the coordinates of each vertex relative to the centroid.

4) Setting a device placement interval: and setting the position interval of each device allowed to be placed on the deck according to the actual requirements of the ship operation tasks. Such as the square areas where the devices 1-6 of fig. 2 are located.

5) Obstacle position setting: and setting the placing position of the barrier influencing the walking path of the operating personnel according to the actual requirement of the ship operation task. Such as the polygonal area of the obstacle 7 in fig. 2.

6) Setting the time sequence: according to the requirements of the task flows, considering the sequence of the task flows and the related operators, and based on the time sequence array matrix, the activity sequence, the duration and the number of the operators of any specific task are visually represented through the task unit list and the time scale. Referring to fig. 1, the sequence and duration of any particular task activity is represented visually by a list of task elements and a time scale based on a time-ordered matrix a. In fig. 1, the abscissa represents time and the ordinate represents activities (task units), which intuitively indicate when a task unit is performed. The mathematical model is as follows:

As shown in fig. 1, there are 6 sequential tasks, each task uses one device, the number is 1-6, and if there are no parallel tasks, the time sequence array matrix is as follows:

therefore, the device order matrix is;

7) design of optimization objectives: (a) after the equipment and the barriers are placed, according to the operation tasks, the sum of the distances of all the operation personnel to successively reach different equipment is calculated to be minimum; (b) the occupied area of all equipment placed on the deck is the smallest. Such as

8) Deck layout calculation: randomly generating a population of equipment arrangement on a deck by adopting a genetic algorithm, requiring the distance between all the equipment to accord with the human body operation range, and calculating all operation paths and the equipment occupation area according to the operation flow; generating a new operator according to a genetic variation method of a genetic algorithm on the basis to obtain a new population, calculating a new operation path and an equipment occupation area of the new population, and judging whether constraint conditions are met according to a set target; through repeated selection, crossover and mutation, until new individuals meeting the constraint condition are generated. As shown in the devices 1-6 and the obstacle 7 of FIG. 2, the number of individuals in the initial population is set to be 30, the cross probability is 0.5, the mutation probability is 0.01, and the iteration number is 5000. By estimation, the sum of the maximum distances does not exceed 200, so the minimum optimization problem can be converted into the fitness evaluation function setting for solving the maximum value shown in the following formula.

Where f (x) is an individual fitness evaluation function, M denotes a device, and i is a device number. The operation flow is that the equipment 1-6 are operated in sequence, and then the next equipment is operated.

9) Termination conditions of the algorithm: in general, the cross probability of the algorithm is set to 0.5, the mutation probability is set to 0.01, and the number of iterations is 5000, and the number of iterations may be increased according to the actual calculation accuracy requirement. The placement positions of the devices 1-6 shown in fig. 2 are the deck layouts with the minimum operation distance and the minimum device occupation area calculated by the algorithm; FIG. 3 is an algorithm evolution process diagram, random fluctuation exists in the evolution process, then the population evolution gradually tends to be stable along with the increase of the evolution times, partial fluctuation at the later stage of evolution belongs to the embodiment of crossing and variation in the genetic process to generate new individuals, and the overall convergence trend is not influenced.

Although the present invention has been described with reference to the above embodiments, it should be understood that the present invention is not limited to the above embodiments, but rather, the present invention is not limited to the above embodiments, and those skilled in the art can make various changes and modifications without departing from the scope of the present invention.

Claims

1. A deck layout optimization calculation method based on an improved genetic algorithm is characterized in that a multi-person cooperative operation process and the minimum occupied area of a deck layout are considered, and the deck layout optimization comprises the following components: equipment and obstacles on a deck, a plurality of operations and operation sequence flows, wherein each operation relates to an operator; the calculation method comprises the following steps:

1) mathematical description of devices and obstacles in the layout: mapping all equipment and obstacles on a deck plane with a given shape, manually drawing the equipment and the obstacles into a closed polygon in a manual drawing mode, and representing the complete equipment plane shape by adopting the fewest points as much as possible;

2) and (3) calculating the centroid: calculating the gravity center of the polygon by using the principle of calculating the gravity center of the graph by geometric integration, and taking the gravity center as the centroid of the equipment or the obstacle;

3) and (3) setting coordinates: numbering each device and each obstacle, and forming a sequence of relative coordinates of vertexes and centroids of each device and each obstacle clockwise by taking centroids of the devices and the obstacles as origin of coordinates;

4) setting a device placement interval: setting a position interval of each device allowed to be placed on the deck according to the actual requirement of the ship operation task;

5) obstacle position setting: setting the position of an obstacle affecting the walking path of an operator according to the actual requirements of the ship operation task;

6) setting the time sequence: according to the operation requirement, considering the sequence of the task flow and the related operators, and based on the time sequence arrangement matrix, visually representing the activity sequence, the duration and the number of the operators of any specific task through a task unit list and a time scale;

the sequence of the time sequence array matrix from top to bottom represents the sequence relation of sequential tasks, and the element in each row represents the parallel task corresponding to the time period;

7) design of optimization objectives: (a) after all the operation tasks are completed, the sum of the distances that all the operators successively pass to different devices is the minimum; (b) the occupied area of all equipment placed on the deck is the smallest;

8) deck layout calculation: randomly generating a population of equipment arrangement on a deck by adopting a genetic algorithm, requiring the distance between all the equipment to accord with the human body operation range, and calculating all operation paths and the equipment occupation area according to the operation flow; generating a new operator according to a genetic variation method of a genetic algorithm on the basis to obtain a new population, calculating a new operation path and an equipment occupation area of the new population, and judging whether constraint conditions are met according to a set target; repeatedly carrying out variation until new individuals meeting the constraint condition are generated;

9) termination conditions of the algorithm: the variation probability of the algorithm is set to be 0.01, the iteration times are 5000, and the iteration times can be increased according to the actual calculation precision requirement.

2. The method of claim 1, wherein the algorithm comprises a range of operations characterizing a human.

3. The method of claim 1, wherein the algorithm comprises a job schedule.

4. The method of claim 1, wherein the algorithm comprises optimization goal setting of human characteristics.