CN109325721A - A kind of undercarriage method on goods and materials based on intelligent analysis process - Google Patents
A kind of undercarriage method on goods and materials based on intelligent analysis process Download PDFInfo
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- CN109325721A CN109325721A CN201811178772.9A CN201811178772A CN109325721A CN 109325721 A CN109325721 A CN 109325721A CN 201811178772 A CN201811178772 A CN 201811178772A CN 109325721 A CN109325721 A CN 109325721A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/087—Inventory or stock management, e.g. order filling, procurement or balancing against orders
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/004—Artificial life, i.e. computing arrangements simulating life
- G06N3/006—Artificial life, i.e. computing arrangements simulating life based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO]
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/12—Computing arrangements based on biological models using genetic models
- G06N3/126—Evolutionary algorithms, e.g. genetic algorithms or genetic programming
Abstract
The invention discloses a kind of undercarriage methods on goods and materials based on intelligent analysis process, based on ant colony and genetic algorithm, Pheromone update based on similarity of paths is applied to the applicability function of genetic algorithm, according to outbound, estimated in library time situation again after same goods and materials in history undercarriage, dump, it combines and avoids backlog of material, construct non-linear sequence in the library time preferential undercarriage of longer goods and materials with type goods and materials with batch, and Controlling UEP is carried out, recommend restocking position in storehouse.Fusion ant colony of the present invention and genetic algorithm, " pheromones " based on similarity of paths are updated to the applicability function for being applied to genetic algorithm, the convergence rate of cluster can not only be improved, additionally it is possible to improve the accuracy of cluster, to improve the accuracy of position in storehouse recommendation, improves and recommend efficiency.
Description
Technical field
The invention belongs to power domain, it is related to a kind of undercarriage method on goods and materials, it is specifically a kind of to be calculated based on intellectual analysis
Undercarriage method on the goods and materials of method.
Background technique
In conjunction with the features such as position in storehouse distribution, size, load-bearing, the data such as undercarriage record, position in storehouse turnover rate on analysis of history inventory,
Formulate position in storehouse intelligent recommendation strategy.The intelligent algorithm being commonly used in position in storehouse intelligent recommendation at present has ant group algorithm, heredity to calculate
Method, neural network, particle swarm algorithm etc..For traditional ant group algorithm, at position in storehouse recommendation initial stage, there are blindness, search spaces
Greatly, efficiency is lower, and the ability in terms of genetic algorithm global search is stronger, but lacks in search later period heuristic information underutilization etc.
It falls into.
Summary of the invention
The object of the present invention is to provide undercarriage method, fusion ant colony and heredity on a kind of goods and materials based on intelligent analysis process
" pheromones " based on similarity of paths are updated the applicability function for being applied to genetic algorithm, can not only improved poly- by algorithm
The convergence rate of class, additionally it is possible to improve the accuracy of cluster, to improve the accuracy of position in storehouse recommendation, improve and recommend efficiency.
The purpose of the present invention is achieved through the following technical solutions:
A kind of undercarriage method on goods and materials based on intelligent analysis process, it is characterised in that: be based on ant colony and genetic algorithm, will be based on
The Pheromone update of similarity of paths is applied to the applicability function of genetic algorithm, according to same goods and materials undercarriage, dump in history
Outbound, estimated in library time situation again afterwards, combines and avoids backlog of material, with batch with type goods and materials in the library time compared with surplus
Preferential undercarriage is provided, constructs non-linear sequence, and carry out Controlling UEP, recommends restocking position in storehouse.
Specific step is as follows:
Step 1: basic data processing
For undercarriage position in storehouse data on goods and materials over the years, restocking is uniformly distributed according to position in storehouse utilization rate, with the same depth of batch, tunnel,
Layer after antecedent, five kinds of screening empty pallet tunnel strategy carry out position in storehouse recommendation, undercarriage according to first in first out or first-in last-out strategy into
Firm position position is recommended, and is recommended position in storehouse out to record all policies, is entered step two；
Step 2: position in storehouse recommends analysis
Based on the position in storehouse obtained in step 1, recycles Genetic Algorithm Model, goes out storage efficiency principle model and shelf stabilities
Model carries out position in storehouse and recommends analysis, in conjunction with the result in step 1, obtains the optimal solution that undercarriage position in storehouse is recommended；
Step 3: position in storehouse recommendation results output
After system operation clearing, recommend optimal upper undercarriage position in storehouse out and candidate position in storehouse list according to specified format；
Step 4: upper undercarriage position in storehouse information is collected
The position in storehouse information of undercarriage on this goods and materials is collected, is added to goods and materials and goes out to be put in storage in position in storehouse database, as next
The basic data of secondary upper undercarriage is handled.
The present invention goes out to be put in storage position in storehouse data by the goods and materials of analysis of history 4-5, in conjunction with goods and materials, position in storehouse basic information and object
Money constructs goods and materials outbound position in storehouse and the data sequence in the library time, using the material requirements time as reference prediction goods and materials in the library time
The outbound time is inserted into variable, and carries out sequence Controlling UEP, proposes suitable position in storehouse recommendation list combination, recommends out on this
The position in storehouse of undercarriage goods and materials improves to improve the accuracy of position in storehouse recommendation and recommends efficiency, improves warehousing and storage activities efficiency, warehouse benefit
With rate.
Detailed description of the invention
Fig. 1 is flow chart of the present invention.
Fig. 2 is Genetic Algorithm Model figure of the present invention.
Specific embodiment
A kind of undercarriage method on goods and materials based on intelligent analysis process is based on ant colony and genetic algorithm, will be based on path phase
It is applied to the applicability function of genetic algorithm like the Pheromone update of degree, according to going out again after same goods and materials in history undercarriage, dump
Library expects to combine in library time situation and avoid backlog of material, preferential in library time longer goods and materials with type goods and materials with batch
Undercarriage constructs non-linear sequence, and carries out Controlling UEP, recommends restocking position in storehouse.
To improve the accuracy that position in storehouse is recommended, improves and recommend efficiency, recommend research method according to upper undercarriage position in storehouse, establish phase
The information processing function is answered, position in storehouse recommendation function includes basic data processing, position in storehouse recommendation analysis, the output of position in storehouse recommendation results, tool
Body is as follows:
Step 1: basic data processing
For undercarriage position in storehouse data on goods and materials over the years, restocking is uniformly distributed according to position in storehouse utilization rate, with the same depth of batch, tunnel,
Layer after antecedent, five kinds of screening empty pallet tunnel strategy carry out position in storehouse recommendation, undercarriage according to first in first out or first-in last-out strategy into
Firm position position is recommended, and is recommended position in storehouse out to record all policies, is entered step two.
Step 2: position in storehouse recommends analysis
Based on the position in storehouse obtained in step 1, recycles Genetic Algorithm Model, goes out storage efficiency principle model and shelf stabilities
Model carries out position in storehouse and recommends analysis, in conjunction with the result in step 1, obtains the optimal solution that undercarriage position in storehouse is recommended, concrete analysis
Method is as follows:
1) intersection two-by-two is carried out according to the position in storehouse that upper undercarriage type respectively goes out each policy recommendation to solve；
2) by position in storehouse in intersection according to frequency of occurrence permutation with positive order；
3) goods yard distribution is carried out by genetic algorithm according to upper undercarriage material, carries out global search and parallelization processing, obtains 10
A recommendation position in storehouse；
4) 10 recommendation positions in storehouse are calculated by going out storage efficiency principle model according to upper undercarriage material；
5) 10 recommendation positions in storehouse are calculated by shelf stabilities principles models according to upper undercarriage material；
6) by 3), 4), 5) it is calculated as a result, in sequence with 2) in calculated result carry out intersection solution；
7) 6) the intersection solution in is subjected to intersection solution again, the position in storehouse obtained is as last recommendation position in storehouse；
If 8) 7) obtain Xie Weikong, successively reduced by sequence 5), 4), 3) and participate in the number that intersection solves, until obtaining
Solution；
If 9) 8) obtain Xie Weikong, position in storehouse recommendation is carried out by sequence 2).
Step 3: position in storehouse recommendation results output
After system operation clearing, recommend optimal upper undercarriage position in storehouse out and candidate position in storehouse list according to specified format.
Step 4: upper undercarriage position in storehouse information is collected
The position in storehouse information of undercarriage on this goods and materials is collected, is added to goods and materials and goes out to be put in storage in position in storehouse database, as next
The basic data of secondary upper undercarriage is handled.
Claims (3)
1. a kind of undercarriage method on goods and materials based on intelligent analysis process, it is characterised in that: ant colony and genetic algorithm are based on, by base
In similarity of paths Pheromone update be applied to genetic algorithm applicability function, according to same goods and materials in history undercarriage, turn
Outbound, estimated in library time situation again, combines and avoids backlog of material after storage, longer in the library time with type goods and materials with batch
The preferential undercarriage of goods and materials constructs non-linear sequence, and carries out Controlling UEP, recommends restocking position in storehouse.
2. undercarriage method on the goods and materials according to claim 1 based on intelligent analysis process, it is characterised in that specific steps
It is as follows:
Step 1: basic data processing
For undercarriage position in storehouse data on goods and materials over the years, restocking is uniformly distributed according to position in storehouse utilization rate, with the same depth of batch, tunnel,
Layer after antecedent, five kinds of screening empty pallet tunnel strategy carry out position in storehouse recommendation, undercarriage according to first in first out or first-in last-out strategy into
Firm position position is recommended, and is recommended position in storehouse out to record all policies, is entered step two；
Step 2: position in storehouse recommends analysis
Based on the position in storehouse obtained in step 1, recycles Genetic Algorithm Model, goes out storage efficiency principle model and shelf stabilities
Model carries out position in storehouse and recommends analysis, in conjunction with the result in step 1, obtains the optimal solution that undercarriage position in storehouse is recommended；
Step 3: position in storehouse recommendation results output
After system operation clearing, recommend optimal upper undercarriage position in storehouse out and candidate position in storehouse list according to specified format；
Step 4: upper undercarriage position in storehouse information is collected
The position in storehouse information of undercarriage on this goods and materials is collected, is added to goods and materials and goes out to be put in storage in position in storehouse database, as next
The basic data of secondary upper undercarriage is handled.
3. undercarriage method on the goods and materials according to claim 2 based on intelligent analysis process, it is characterised in that: step 2
In, position in storehouse recommends analysis method as follows:
1) intersection two-by-two is carried out according to the position in storehouse that upper undercarriage type respectively goes out each policy recommendation to solve；
2) by position in storehouse in intersection according to frequency of occurrence permutation with positive order；
3) goods yard distribution is carried out by genetic algorithm according to upper undercarriage material, carries out global search and parallelization processing, obtains 10
A recommendation position in storehouse；
4) 10 recommendation positions in storehouse are calculated by going out storage efficiency principle model according to upper undercarriage material；
5) 10 recommendation positions in storehouse are calculated by shelf stabilities principles models according to upper undercarriage material；
6) by 3), 4), 5) it is calculated as a result, in sequence with 2) in calculated result carry out intersection solution；
7) 6) the intersection solution in is subjected to intersection solution again, the position in storehouse obtained is as last recommendation position in storehouse；
If 8) 7) obtain Xie Weikong, successively reduced by sequence 5), 4), 3) and participate in the number that intersection solves, until obtaining solution；
If 8) obtain Xie Weikong, position in storehouse recommendation is carried out by sequence 2).
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| CN103559396A (en) * | 2013-10-31 | 2014-02-05 | 华北水利水电大学 | Automatic pharmacy storage location optimizing method based on improved chaos particle swarm algorithm |
| CN104063778A (en) * | 2014-07-08 | 2014-09-24 | 深圳市远望谷信息技术股份有限公司 | Method for allocating cargo positions for cargoes in three-dimensional warehouse |
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