.png){kind=icon}
Return
Generalized robust goal programming model
.png){kind=icon}
PRE
AI
DOI：10.1016/j.ejor.2024.06.037.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
This study proposes a concise and generalized robust goal programming (RGP) model that simultaneously considers three types of goal functions - right-side penalties, left-side penalties, and both-side penalties - under uncertainties on both the left-hand side and right-hand side. It integrates common uncertainty sets for a comprehensive goal programming model. Experimental results reveal that our model consistently outperforms existing RGP models by incurring fewer penalties, demonstrating enhanced resilience and robustness. This advantage becomes evident when problem coefficients such as costs, profits, and human resource requirements deviate significantly from their default target levels due to real-world conditions. The proposed model not only extends the robustness of traditional goal programming and weighted fuzzy goal programming but also offers improved risk management across various practical scenarios.
Keywords:
Goal programming
Robust optimization
Generalized robust goal programming
Multi-objective decision problems
Journal
IF:
6
Papers:
2.2W
Citations:
6.4W
Organization
Cited Papers
ShareSave
ShareSaveUnderstanding the Effect of Side Reactions on the Recyclability of Furan–Maleimide Resins Based on Thermoreversible Diels–Alder Network.png)
Polymers
OAAI
PolymersIF0
OAAIShareSaveEvaluation of Impedance-Based Label-Free Technology as a Tool for Pharmacology and Toxicology InvestigationsBiosensorsOAAI
BiosensorsIF0
OAAIShareSave
View more