CN110516821A - A kind of maintenance of the vessel method for optimizing resource allocation and device - Google Patents
A kind of maintenance of the vessel method for optimizing resource allocation and device Download PDFInfo
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Abstract
The present invention relates to a kind of maintenance of the vessel method for optimizing resource allocation and devices, based on Fuzzy AHP, ship status assessment indicator system is established, includes indicator layer and sub- indicator layer in the index system, and parameter system neutron indicator layer each element is for the synthesis different degree of ship status；Using the current data and each element of the sub- indicator layer each element in the assessment indicator system for the synthesis different degree of ship status, the coefficient of the maintenance of the vessel resource requirement prediction model pre-established is optimized.The present invention utilizes principles of fuzzy mathematics, describes qualitative or uncertain factor with accurate mathematical linguistics, evaluates its state of repairing, the allocation models optimized.
Description
Technical field
The present invention relates to maintenance of the vessel fields, and in particular to a kind of maintenance of the vessel method for optimizing resource allocation and device.
Background technique
Maintenance of the vessel resource refers to the other conditions that goods and materials and maintenance work necessary to implementing maintenance work are completed, mainly
Including personnel, goods and materials, environment, regulation etc..Maintenance of the vessel most optimum distribution of resources problem is a complicated and the mathematical problem of system, it
It is related to the optimization integral dispensing of Maintenance Resource and shiprepair unit is seen as whole resource allocation optimization and single resource
Optimum distribution and multi dimensional resource the various problems such as optimum distribution.
Maintenance of the vessel resource distribution at this stage is based on single analysis method mostly, i.e., only with single Maintenance Resource is optimization mesh
Mark, which is carried out, distributes rationally, and in configuration to ship state of the art parameter itself, shipping kilometre, dock integrated repair ability etc.
Important factor in order does not have abundant system to consider, Maintenance Resource configuration number cannot be dynamically adjusted according to the practical repairing demand of ship
According to, cause Maintenance Resource configuration it is not scientific, unreasonable, generate should not waste.
Summary of the invention
The present invention for the technical problems in the prior art, provide a kind of maintenance of the vessel method for optimizing resource allocation and
Device.
The technical scheme to solve the above technical problems is that
In a first aspect, the present invention provides a kind of maintenance of the vessel method for optimizing resource allocation, comprising the following steps:
Based on Fuzzy AHP, ship status assessment indicator system is established, includes indicator layer in the index system
With sub- indicator layer, and parameter system neutron indicator layer each element is for the synthesis different degree of ship status；
Using the current data and each element of the sub- indicator layer each element in the assessment indicator system for ship status
Synthesis different degree, the coefficient of the maintenance of the vessel resource requirement prediction model pre-established is optimized；
The maintenance of the vessel resource requirement prediction model is shown below,
ZYSLi=α JIBIE1SLi+βJIBIE2SLi+γJIBIE3SLi
In formula, ZYSLiIndicate the quantity required of the i-th class resource in maintenance process；
JIBIE1SLi、JIBIE2SLi、JIBIE3SLiIt then respectively indicates the i-th class resource and corresponds to dock repair rank generally, relatively sternly
Weight, serious historical statistics average value；α, β, γ are weighting coefficient.
Based on the above technical solution, this method further includes coefficient optimum results evaluation method, comprising:
It calculates sub- indicator layer each element and angle value is subordinate to for ship status；
It is subordinate to angle value using synthesis different degree and each element of each element for ship status, design factor optimization knot
Fruit evaluation of estimate.
Further, the sub- indicator layer each element of calculating is subordinate to angle value for ship status, comprising:
Degree of membership coefficient is defined according to expertise；
Sub- indicator layer each element pair is calculated using the current data of the sub- indicator layer each element in the assessment indicator system
The correction factor for the maintenance of the vessel resource requirement prediction model answered；
According to the degree of membership coefficient and the corresponding correction factor of sub- indicator layer each element, sub- indicator layer each element pair is calculated
It is subordinate to angle value in ship status.
Second aspect, the present invention also provides a kind of maintenance of the vessel optimizing resource allocation devices, comprising:
Assessment indicator system establishes module, for establishing ship status assessment indicator system based on Fuzzy AHP,
It include indicator layer and sub- indicator layer in the index system, and parameter system neutron indicator layer each element is for ship status
Synthesis different degree；
Coefficient optimization module, for the current data using the sub- indicator layer each element in the assessment indicator system and respectively
Element carries out excellent the synthesis different degree of ship status to the coefficient of the maintenance of the vessel resource requirement prediction model pre-established
Change.
The beneficial effects of the present invention are: the weighting coefficient that maintenance of the vessel most optimum distribution of resources generallys use is definite value, but real
Border marine technology state is dynamically, so must assess ship status, more accurate ship status weight system certainly
Number, can preferably reflect ship state to be repaired, more targeted to instruct dock repair resource distribution.For this purpose, this Maintenance Resource is excellent
Change Research on configuration to optimize mainly for ship status weighting coefficient, be configured using the weight based on fuzzy hierarchy analysis
Method determines ship status weighting coefficient [α, beta, gamma], and the ship status weighting coefficient after making optimization more accurately reflects ship
Service mode.
The present invention uses the marine technology status assessment system based on fuzzy hierarchy analysis, to marine technology shape
On the basis of the parameters such as state, shipping kilometre carry out comprehensive analysis, the recursive hierarchy structure of object to be evaluated is established, according to evaluation index
Attribute, the model weighted using coefficient of dynamics described qualitative or not with accurate mathematical linguistics using principles of fuzzy mathematics
It determines factor, its state of repairing is evaluated, the allocation models optimized.
Detailed description of the invention
Fig. 1 is a kind of maintenance of the vessel method for optimizing resource allocation flow chart that the embodiment of the present invention one provides；
Fig. 2 is a kind of maintenance of the vessel optimizing resource allocation structure drawing of device provided by Embodiment 2 of the present invention.
Specific embodiment
The principle and features of the present invention will be described below with reference to the accompanying drawings, and the given examples are served only to explain the present invention, and
It is non-to be used to limit the scope of the invention.
The weighting coefficient that maintenance of the vessel most optimum distribution of resources generallys use is definite value, but practical marine technology state is certainly
Dynamically, so must assess ship status, more accurate boat state weight coefficient can preferably reflect that ship waits for
State is repaired, it is more targeted to instruct dock repair resource distribution.For this purpose, this Maintenance Resource distributes research rationally mainly for ship shape
State weighting coefficient optimizes, and determines ship status weighting coefficient using the weight configuration method based on fuzzy hierarchy analysis
[α, beta, gamma], the ship status weighting coefficient after making optimization more accurately reflect maintenance of the vessel state.
The present invention uses the marine technology status assessment system based on fuzzy hierarchy analysis, to marine technology shape
On the basis of the parameters such as state, shipping kilometre carry out comprehensive analysis, the recursive hierarchy structure of object to be evaluated is established, according to evaluation index
Attribute, the model weighted using coefficient of dynamics described qualitative or not with accurate mathematical linguistics using principles of fuzzy mathematics
It determines factor, its state of repairing is evaluated, the allocation models optimized.
Embodiment one
As shown in Figure 1, a kind of maintenance of the vessel method for optimizing resource allocation provided in an embodiment of the present invention, including it is following interior
Hold:
Step 100, it is based on Fuzzy AHP, ship status assessment indicator system is established, is wrapped in the index system
Indicator layer and sub- indicator layer are included, and parameter system neutron indicator layer each element is for the synthesis different degree of ship status.
The maintenance of the vessel resource requirement prediction model is shown below,
ZYSLi=α JIBIE1SLi+βJIBIE2SLi+γJIBIE3SLi
In formula, ZYSLiIndicate the quantity required of the i-th class resource in maintenance process；
JIBIE1SLi、JIBIE2SLi、JIBIE3SLiIt then respectively indicates the i-th class resource and corresponds to dock repair rank generally, relatively sternly
Weight, serious historical statistics average value；α, β, γ are weighting coefficient.
According to each affiliated type of factor in appraisement system, distinguishing hierarchy is carried out to it, form ship status evaluation passs rank
Hierarchy Model.Ship status assessment structural model is a completely self-contained hierarchical structure, its main feature is that index at the same level is all
Be it is independent, it is entirely different with next stage index.
By repairing unit investigation to certain dock, maintenance of the vessel state evaluation index system and Recurison order hierarchy relationship knot are determined
" sailing condition " and " hull situation " two indices parameter is arranged in structure, first layer, and " sailing condition " junior's index is " last time maintenance
Hours underway afterwards ", " shipping kilometre after last time maintenance " and " interval time after last time maintenance "；" hull state " is set as herein
Evaluation of the ship captain to the ship state of the art.Recurison order hierarchy relational structure is shown in Table 1.The hierarchical relationship is subsequent can to carry out constantly
Amendment and supplement are perfect.
Certain the ship service mode assessment indicator system hierarchical relationship structure of table 1
After completing recursive hierarchy structure foundation, the element membership between upper and lower layer is determined that, here, can by table 1
Know that index system has been divided into two layers:
Indicator layer only lists two elements of conduct of a vessel and hull state here；But be not excluded for, according to ship
Oceangoing ship type is different and increases the possibility of other class elements.
Sub- indicator layer, equally only list here last time maintenance after hours underway, last time maintenance after navigation process, on
Interval time and hull state captain four elements of evaluation of estimate after secondary maintenance；
The navigation process after hours underway, last time maintenance after the last time maintenance, the interval time after last time maintenance are subordinate to
Belong to the ship course situation, hull state captain's evaluation of estimate is under the jurisdiction of the hull state.
After recursive hierarchy structure is established, the influence different degree according to lower layer's index to upper layer interpretational criteria calculates fingers at different levels
Target integrates different degree wj,
wj=ai*bj
Wherein, aiIndicate the value of indicator layer element i, bjIndicate the value of sub- indicator layer element j.
The sum of each level index weight is " 1 ".Herein, it will be assumed that " sailing condition " and " hull situation " two
One layer of index weight is respectively (0.6,0.4) (the different degree value is generally by repairing expert evaluation), " sailing condition " three
Sub- index " hours underway after last time maintenance ", " shipping kilometre after last time maintenance " and " interval time after last time maintenance " index weight
Spend respectively (0.4,0.4,0.2) (the different degree value is generally by repairing expert evaluation).The synthesis different degree of indexs at different levels
wjCalculated result is as shown in table 2.
Certain the ship service mode evaluation index of table 2 integrates different degree
Step 200, using the current data of the sub- indicator layer each element in the assessment indicator system and each element for
The synthesis different degree of ship status optimizes the coefficient of the maintenance of the vessel resource requirement prediction model pre-established.
Firstly, the current data using the sub- indicator layer each element in the assessment indicator system calculates sub- each member of indicator layer
The correction factor of the corresponding maintenance of the vessel resource requirement prediction model of element；
Specifically, it is each to calculate sub- indicator layer using the current data of the sub- indicator layer each element in the assessment indicator system
The correction factor of the corresponding maintenance of the vessel resource requirement prediction model of element, including following sub-step:
Step 201, the relationship between maintenance of the vessel resource requirement prediction model weight coefficient [α, beta, gamma] is discussed, is built first
Vertical constraint condition: alpha+beta+γ=1 initializes the maintenance of the vessel resource requirement prediction model coefficient, enables the equal weighting weight of α, β, γ
The average value 0.33 of the sum of coefficient.
Step 202, the current data of sub- indicator layer each element is normalized, then the value of α, γ is discussed.
1, it is first normalized for " hours underway after last time maintenance ",
Indicate normalization " hours underway after last time maintenance "；
ThtIndicate " hours underway after last time maintenance "；
ThtmaxIt indicates " longest hours underway after maintenance ".
In [α, beta, gamma] coefficient, it is serious state that γ, which characterizes ship dock repair rank to be repaired, so sub- indicator layer
The practical value of each element should be directly proportional to γ.
WhenWhen,
WhenWhen,
Due to initializing β=0.33, it is determined that after amendment when weight coefficient, α, γ must be multiplied by 2/3, i.e., after last time maintenance
The corresponding correction factor of hours underway is
2, it is first normalized for " shipping kilometre after last time maintenance ",
Indicate normalization " shipping kilometre after last time maintenance "；
ThlIndicate " shipping kilometre after last time maintenance "；
ThlmaxIt indicates " longest shipping kilometre after maintenance ".
In [α, beta, gamma] coefficient, it is serious state that γ, which characterizes ship dock repair rank to be repaired, so sub- indicator layer
The practical value of each element should be directly proportional to γ.
WhenWhen,
WhenWhen,
Due to initializing β=0.33, it is determined that after amendment when weight coefficient, α, γ must be multiplied by 2/3, i.e., after last time maintenance
The corresponding correction factor of shipping kilometre is
3, it is first normalized for " interval time after last time maintenance ",
Indicate normalization " shipping kilometre after last time maintenance "；
TjtIndicate " shipping kilometre after last time maintenance "；
TjtmaxIt indicates " longest shipping kilometre after maintenance ".
In [α, beta, gamma] coefficient, it is serious state that γ, which characterizes ship dock repair rank to be repaired, so sub- indicator layer
The practical value of each element should be directly proportional to γ.
WhenWhen,
WhenWhen,
Due to initializing β=0.33, it is determined that after amendment when weight coefficient, α, γ must be multiplied by 2/3, i.e., after last time maintenance
Interval time, corresponding correction factor was
4, it is directed to " hull state captain evaluation of estimate ", since " hull state captain evaluation of estimate " value interval is [0,1], therefore
It does not need to be normalized.Assuming that " hull state captain evaluation of estimate " is P, at this time " hull state captain evaluation of estimate " and α
It is directly proportional, that is, it scores higher, indicates that ship status is better, then weight coefficient α is higher.
As P >=0.5,
As P < 0.5,
Due to initializing β=0.33, it is determined that after amendment when weight coefficient, α, γ must be multiplied by 2/3, i.e. hull state warship
The corresponding correction factor of long evaluation of estimate is
After obtaining the corresponding correction factor of the sub- indicator layer each element, in conjunction with each element for ship status
Comprehensive different degree wi, calculate the optimized coefficients of the maintenance of the vessel resource requirement prediction model.
Specifically, the corresponding correction factor of sub- indicator layer each element is formed into coefficient matrix, it is as follows:
Simultaneously according to each element for the synthesis different degree w of ship statusiForm comprehensive different degree vector W=(w1,w2,
w3,w4), utilize the excellent of the comprehensive different degree vector and the coefficient matrix Ship ' Maintenance Resource Demand Forecast Model
Change coefficient, be shown below:
Based on the above method, the embodiment of the invention also includes coefficient optimum results evaluation methods, comprising:
Step 301, it calculates sub- indicator layer each element and angle value is subordinate to for ship status；
Specifically, defining degree of membership coefficient according to expertise；Then each according to the degree of membership coefficient and sub- indicator layer
The corresponding correction factor of element calculates sub- indicator layer each element and is subordinate to angle value for ship status.
Define degree of membership coefficient Z=(z1,z2,z3), z1,z2,z3Respectively correspond maintenance of the vessel resource requirement prediction model
Factor alpha, β, γ.According to expertise, Z=(0.6,0.8,1) then calculates sub- indicator layer each element for ship according to the following formula
State is subordinate to angle value U (bj):
Step 302, it is subordinate to angle value using synthesis different degree and each element of each element for ship status, under
Formula design factor optimum results evaluation of estimate Q.
Q=[U (b1),U(b2),U(b3),U(b4)](w1,w2,w3,w4)T
When describing the matching degree of predicted value and legitimate reading, generally use seven grades: it is fine, good, preferable, in,
It is poor, poor, very poor, 1.0,0.9,0.7,0.5,0.3,0.1,0 is respectively corresponded, the most bad value and optimal value of predicted value are respectively 0
With 1.0.And seven grade points are compared according to coefficient optimum results evaluation of estimate Q, quantitative description is converted by the qualitative representation of index.
Embodiment two
As shown in Fig. 2, a kind of maintenance of the vessel optimizing resource allocation device provided in an embodiment of the present invention, comprising:
Assessment indicator system establishes module, for establishing ship status assessment indicator system based on Fuzzy AHP,
It include indicator layer and sub- indicator layer in the index system, and parameter system neutron indicator layer each element is for ship status
Synthesis different degree；
Coefficient optimization module, for the current data using the sub- indicator layer each element in the assessment indicator system and respectively
Element carries out excellent the synthesis different degree of ship status to the coefficient of the maintenance of the vessel resource requirement prediction model pre-established
Change.
The foregoing is merely presently preferred embodiments of the present invention, is not intended to limit the invention, it is all in spirit of the invention and
Within principle, any modification, equivalent replacement, improvement and so on be should all be included in the protection scope of the present invention.
Claims (10)
1. a kind of maintenance of the vessel method for optimizing resource allocation, which comprises the following steps:
Based on Fuzzy AHP, ship status assessment indicator system is established, includes indicator layer and son in the index system
Indicator layer, and parameter system neutron indicator layer each element is for the synthesis different degree of ship status；
Using the current data and each element of the sub- indicator layer each element in the assessment indicator system for the comprehensive of ship status
Different degree is closed, the coefficient of the maintenance of the vessel resource requirement prediction model pre-established is optimized；
The maintenance of the vessel resource requirement prediction model is shown below,
ZYSLi=α JIBIE1SLi+βJIBIE2SLi+γJIBIE3SLi
In formula, ZYSLiIndicate the quantity required of the i-th class resource in maintenance process；
JIBIE1SLi、JIBIE2SLi、JIBIE3SLiThen respectively indicating the i-th class resource, to correspond to dock repair rank general, more serious, tight
The historical statistics average value of weight；α, β, γ are weighting coefficient.
2. the method according to claim 1, wherein the ship status assessment indicator system, comprising:
Indicator layer, the indicator layer include at least two elements of conduct of a vessel and hull state；
Sub- indicator layer, the sub- indicator layer include at least last time maintenance after hours underway, last time maintenance after navigation process, on
Interval time and hull state captain four elements of evaluation of estimate after secondary maintenance；
There are memberships for the indicator layer and the sub- indicator layer, after the hours underway, last time maintenance after the last time maintenance
Navigation process, last time maintenance after interval time be under the jurisdiction of the ship course situation, hull state captain's evaluation of estimate
It is under the jurisdiction of the hull state.
3. according to the method described in claim 2, it is characterized in that, each index is for ship shape in the parameter system
The synthesis different degree of state, comprising:
It is indicator layer each element assignment for the different degree that ship status is evaluated according to indicator layer each element；
It is that each element carries out assignment in sub- indicator layer according to different degree of the sub- indicator layer each element for indicator layer each element；
Synthesis different degree of each element relative to ship status in the sub- indicator layer is calculated using following formula；
wj=ai*bj
Wherein, aiIndicate the value of indicator layer element i, bjIndicate the value of sub- indicator layer element j.
4. the method according to claim 1, wherein the sub- index using in the assessment indicator system
The current data and each element of layer each element need the synthesis different degree of ship status to the maintenance of the vessel resource pre-established
The coefficient of prediction model is asked to optimize, comprising:
It is corresponding that sub- indicator layer each element is calculated using the current data of the sub- indicator layer each element in the assessment indicator system
The correction factor of the maintenance of the vessel resource requirement prediction model；
In conjunction with each element for the synthesis different degree of ship status, it is using the corresponding amendment of the sub- indicator layer each element
Number, calculates the optimized coefficients of the maintenance of the vessel resource requirement prediction model.
5. according to the method described in claim 4, it is characterized in that, the sub- index using in the assessment indicator system
The current data of layer each element calculates the amendment of the corresponding maintenance of the vessel resource requirement prediction model of sub- indicator layer each element
Coefficient, comprising:
Initialize the maintenance of the vessel resource requirement prediction model coefficient；
The current data of sub- indicator layer each element is normalized；
Son is calculated according to each element data value after relationship, each coefficient value and the normalized between each coefficient of prediction model
The correction factor of the corresponding maintenance of the vessel resource requirement prediction model of indicator layer each element.
6. according to the method described in claim 4, it is characterized in that, each element described in the combination is for the comprehensive of ship status
Different degree is closed, using the corresponding correction factor of the sub- indicator layer each element, calculates the maintenance of the vessel resource requirement prediction mould
The optimized coefficients of type, comprising:
In conjunction with each element for the synthesis different degree of ship status, it is using the corresponding amendment of the sub- indicator layer each element
Number, the optimized coefficients of the maintenance of the vessel resource requirement prediction model are calculated by weigthed sums approach.
7. the method according to claim 1, wherein the method also includes coefficient optimum results evaluation method,
Include:
It calculates sub- indicator layer each element and angle value is subordinate to for ship status；
It is subordinate to angle value using synthesis different degree and each element of each element for ship status, design factor optimum results comment
Value.
8. the method according to the description of claim 7 is characterized in that the sub- indicator layer each element of the calculating is for ship status
Be subordinate to angle value, comprising:
Degree of membership coefficient is defined according to expertise；
It is corresponding that sub- indicator layer each element is calculated using the current data of the sub- indicator layer each element in the assessment indicator system
The correction factor of the maintenance of the vessel resource requirement prediction model；
According to the degree of membership coefficient and the corresponding correction factor of sub- indicator layer each element, sub- indicator layer each element is calculated for ship
Oceangoing ship state is subordinate to angle value.
9. according to the method described in claim 8, it is characterized in that, the sub- index using in the assessment indicator system
The current data of layer each element calculates the amendment of the corresponding maintenance of the vessel resource requirement prediction model of sub- indicator layer each element
Coefficient, comprising:
Initialize the maintenance of the vessel resource requirement prediction model coefficient；
The current data of sub- indicator layer each element is normalized；
Son is calculated according to each element data value after relationship, each coefficient value and the normalized between each coefficient of prediction model
The correction factor of the corresponding maintenance of the vessel resource requirement prediction model of indicator layer each element.
10. a kind of maintenance of the vessel optimizing resource allocation device characterized by comprising
Assessment indicator system establishes module, described for establishing ship status assessment indicator system based on Fuzzy AHP
It include indicator layer and sub- indicator layer in index system, and parameter system neutron indicator layer each element is for the comprehensive of ship status
Close different degree；
Coefficient optimization module, for the current data and each element using the sub- indicator layer each element in the assessment indicator system
For the synthesis different degree of ship status, the coefficient of the maintenance of the vessel resource requirement prediction model pre-established is optimized.
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| CN112270036A (en) * | 2020-10-14 | 2021-01-26 | 上海交通大学 | Ship design index decomposition and dynamic visualization method based on tree hierarchy |
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| CN114879668A (en) * | 2022-04-25 | 2022-08-09 | 广东逸动科技有限公司 | Control method for electric ship, and computer-readable storage medium |
| CN116976865A (en) * | 2023-09-22 | 2023-10-31 | 中国船舶集团有限公司第七一九研究所 | Ship maintenance device allocation management system based on big data analysis |
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| 侯莉莉 等: "《 基于船舶大修的人力资源优化配置研究》", 《武汉理工大学学报(交通科学与工程版)》 * |
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| CN112053026A (en) * | 2020-07-15 | 2020-12-08 | 中国人民解放军海军工程大学 | Ship maintenance resource configuration verification method and device |
| CN112270036A (en) * | 2020-10-14 | 2021-01-26 | 上海交通大学 | Ship design index decomposition and dynamic visualization method based on tree hierarchy |
| CN112270036B (en) * | 2020-10-14 | 2022-05-17 | 上海交通大学 | Ship design index decomposition and dynamic visualization method based on tree hierarchy |
| CN112668830A (en) * | 2020-11-20 | 2021-04-16 | 国网湖南省电力有限公司 | Multilayer fuzzy assessment method for transformer substation operation risk |
| CN114879668A (en) * | 2022-04-25 | 2022-08-09 | 广东逸动科技有限公司 | Control method for electric ship, and computer-readable storage medium |
| CN114879668B (en) * | 2022-04-25 | 2024-01-26 | 广东逸动科技有限公司 | Control method for electric ship, electric ship and computer-readable storage medium |
| CN116976865A (en) * | 2023-09-22 | 2023-10-31 | 中国船舶集团有限公司第七一九研究所 | Ship maintenance device allocation management system based on big data analysis |
| CN116976865B (en) * | 2023-09-22 | 2023-12-19 | 中国船舶集团有限公司第七一九研究所 | Ship maintenance device allocation management system based on big data analysis |
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