PATENT CLAIM ANALYSIS

Application Number: 16127350
Application Type: Utility
Filing Date: 2018-09
Publication Date: 2019-03
Patent Classification: ["705", "007130"]

Abstract:
The present invention discloses a coordinated production and transportation scheduling method and system based on an improved tabu search algorithm, and a storage medium. The method includes batching jobs, initializing algorithm parameters, generating an initial solution, generating a neighborhood solution set, performing mutation, crossover and selection on individuals, determining a candidate solution set; calculating a fitness value of an individual, updating the candidate solution set; updating a tabu list, and determining whether an algorithm termination condition is satisfied; if yes, outputting the global optimal solution; otherwise, returning to the step 4. The present invention is mainly aimed at the coordinated production and transportation batch scheduling problem with multiple manufacturers. The whole profit of an enterprise in the production and transportation phases can be maximized, and high quality services can be provided for customers of the enterprise with improved core competitiveness of the enterprise.

Claim (Index 6):
The system according to  claim 5 , wherein in the step S6 implemented through loading and execution of the at least one instruction by the at least one processing unit, the process of generating the neighborhood solution set N(X s ) according to the initial solution X s , updating the individuals in N(X s ) and determining the candidate solution set List(X s ) comprises:\n step S61, generating the neighborhood solution set with consideration of total W individuals in the neighborhood solution, and denoting the solution set as N(X s )={X 1 , . . . , X j , . . . , X W }, wherein X j  represents the jth individual among the neighborhood solutions, and the individual is obtained by randomly swapping the initial solution X s  for I times; step S62, defining variable N\u2032(X s )={X\u2032 1 , . . . , X\u2032 j , . . . , X\u2032 W }, which has the same meaning as N(X s ), and assigning the individuals in N(X s ) to N\u2032 (X s ); and letting variable j=1; step S63, randomly generating random numbers denoted as index1 and index2 in the range of an interval [1, W], with index1, index2 and j differing from one another; step S64, defining variables V j  and U j , with V j  and U j  being in the same dimension with the individual X j ; letting variable d=1; generating a random number random in the range of an interval (0,1], and assigning the random number to variable F; step S65, updating V jd  by equation V jd =X bd +F\u00d7(X index1d \u2212X index2d ), wherein X bd  representing the dth element in the global optimal solution; step S66, randomly generating a random number rand in the range of the interval (0,1], and determining whether rand\u2264CR is true; if yes, assigning V jd  to U jd ; otherwise, assigning X jd  to U jd ; step S67, assigning d+1 to d, and determining whether d\u2264l is true; if yes, returning to the step S65; otherwise, performing step S68; step S68, calculating fitness values F(X\u2032 j ) and F(U j ) of individual X\u2032 j  and intermediate U j , and comparing F(X\u2032 j ) with F(U j ); if F(X\u2032 j )\u2264F(U j ), assigning U j  to the individual X j ; step S69, assigning j+1 to j, and determining whether j\u2264W is true; if yes, returning to the step S63; otherwise, performing step S610; and step S610, considering Q individuals in the candidate solution set which is denoted as List(X s ), sorting the W individuals in N(X s ) in non-decreasing order by fitness value, picking out first Q individuals from the sequence, and assigning the chosen Q to List (X s ).

Metadata:
- Claim Count in Document: 17.0
- Percentile: 97.0
- Lexical Diversity: 1.85227
- Patent Class: 705.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: True
- Related Applications: ['16127337', '15958932', '12558879', '11866484', '11254501']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.121077775816317
- 35 USC 102 Novelty (BERT): 0.5269183697251779
- Combined Prediction Score: 0.1616618352072031
- Mean Citation Score: 228.83944599999995
- Max Citation Score: 338.37384
- Similarity Product: 209.24388079874043

Labels:
- Claim Label 101: 0
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 0
- Combined Label: 0
- Label 101 Adjusted: 0

Dataset: test