PATENT CLAIM ANALYSIS

Application Number: 16127124
Application Type: Utility
Filing Date: 2018-09
Publication Date: 2019-03
Patent Classification: ["705", "007130"]

Abstract:
The present invention disclose a parallel machine batch scheduling method and system based on an improved artificial bee colony algorithm in a deterioration situation. With this method, a near-optimal solution for the parallel machine batch scheduling problem with deteriorating jobs and maintenance consideration can be obtained. The model of the present invention is derived from an actual production process with considerations of machine maintenance and batching as well as additional processing and maintenance time for jobs and machines over time in actual production. According to the present invention, the settlement of this problem is conducive to providing reliable decision support for the production and maintenance of an enterprise in complex real production conditions, thus reducing enterprise operation costs, increasing enterprise productivity, and promoting building of a modern smart factory of the enterprise.

Claim (Index 3):
The method according to  claim 1 , wherein the step S5 comprises:\n step S51, obtaining a nectar source code, and generating a random number rand between 0 and 1; step S52, determining whether rand<R a  is true; if yes, performing step S53; otherwise, performing step S54; step S53, randomly generating two positive integers x and y between 1 and n, and interchanging numerical values corresponding to the xth and yth positions in the nectar source, thereby obtaining a new nectar source position code; and step S54, randomly generating two positive integers x and y between 1 and n, and reversing a sequence between the xth and yth position, thereby obtaining a new nectar source position code.

Metadata:
- Claim Count in Document: 1.0
- Percentile: 97.0
- Lexical Diversity: 1.7625
- Patent Class: 705.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: True
- Related Applications: ['12805363', '15958932', '12334561', '13046346', '10918336']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.0863157022619077
- 35 USC 102 Novelty (BERT): 0.5177756709513788
- Combined Prediction Score: 0.1294616991308548
- Mean Citation Score: 138.43728000000002
- Max Citation Score: 167.02881000000005
- Similarity Product: 84.03379349793079

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

Dataset: test