Optimizing service selection using hybrid multi-objective genetic algorithms

2015 ◽  
pp. 355-360
Keyword(s):  
Genetic Algorithms ◽  
Service Selection ◽  
Multi Objective

Multi-objective seismic design of BRBs-reinforced concrete buildings using genetic algorithms

2021 ◽  
Author(s):  
Herian Leyva ◽  
Juan Bojórquez ◽  
Edén Bojórquez ◽  
Alfredo Reyes-Salazar ◽  
Julián Carrillo ◽  
...  
Keyword(s):  
Genetic Algorithms ◽  
Reinforced Concrete ◽  
Seismic Design ◽  
Reinforced Concrete Buildings ◽  
Concrete Buildings ◽  
Multi Objective

scholarly journals Multi-Objective Service Selection and Scheduling with Linguistic Preference in Cloud Manufacturing

2019 ◽  
Vol 11 (9) ◽  
pp. 2619 ◽  
Author(s):  
Wei He ◽  
Guozhu Jia ◽  
Hengshan Zong ◽  
Jili Kong
Keyword(s):  
Service Management ◽  
Service Selection ◽  
Cloud Manufacturing ◽  
Multiple Objectives ◽  
Second Phase ◽  
Time Cost ◽  
Two Phase ◽  
Preference Information ◽  
Multi Objective ◽  
Service Selection And Scheduling

Service management in cloud manufacturing (CMfg), especially the service selection and scheduling (SSS) problem has aroused general attention due to its broad industrial application prospects. Due to the diversity of CMfg services, SSS usually need to take into account multiple objectives in terms of time, cost, quality, and environment. As one of the keys to solving multi-objective problems, the preference information of decision maker (DM) is less considered in current research. In this paper, linguistic preference is considered, and a novel two-phase model based on a desirable satisfying degree is proposed for solving the multi-objective SSS problem with linguistic preference. In the first phase, the maximum comprehensive satisfying degree is calculated. In the second phase, the satisfying solution is obtained by repeatedly solving the model and interaction with DM. Compared with the traditional model, the two-phase is more effective, which is verified in the calculation experiment. The proposed method could offer useful insights which help DM balance multiple objectives with linguistic preference and promote sustainable development of CMfg.

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