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 9):
A computer-readable storage medium that stores at least one instruction to be loaded and executed by a processor to implement the method of  claim 1 .

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): 0.1209085592299648
- 35 USC 102 Novelty (BERT): 0.5193661662302098
- Combined Prediction Score: 0.1607543199299893
- Mean Citation Score: 228.83944599999995
- Max Citation Score: 338.37384
- Similarity Product: 307.53427610795967

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

Dataset: test