Affiliation of Author(s):山东大学
Journal:Communications in Computer and Information Science
Key Words:Genetic Algorithm, Multi-objective Optimization, Collaboration Services Scheduling, Self-adaption
Abstract:The optimization problem of collaboration services scheduling is a major bottleneck restricting the efficiency and cost of collaboration services executing. Correct and efficient handling of scheduling problems contributes to reducing costs and increase efficiency. The traditional GA solves this multi-objective problem more comprehensively than the random algorithm such as stochastic greedy algorithm, but it still has some one-sidedness compared with the actual situation. This paper enhances the flexibility and diversity of the algorithm on the basis of traditional genetic algorithm. In the pr
Indexed by:Essay collection
Document Code:20185206312128
Discipline:Engineering
First-Level Discipline:Computer Science and Technology
Document Type:C
Volume:917
Issue:1
Page Number:581-587
ISSN No.:18650929
Translation or Not:no
CN No.:20185206312128
Date of Publication:2019-01-01
Included Journals:EI
Date of Publication:2019-01-01