.png){kind=icon}
.png){kind=icon}
Return
A multi-objective programming model for fire station location under incomplete information environment
.png){kind=icon}
OA
AI
DOI：10.1016/j.orp.2026.100388.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
• A novel multi-objective location model integrating goal programming, stochastic programming, and uncertain programming is presented. • The proposed model incorporates two types of incomplete information: randomness with ambiguous probability distributions and human uncertainty. • Four conflicting objectives are optimized simultaneously to balance efficiency and costs. • A case study employing a Genetic Algorithm (GA) validates the model’s effectiveness and practicality.
Keywords:
Multi-objective programming
Chance constrained programming
Multi-objective chance constrained programming
Fire station location
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
3.7
Papers:
282
Citations:
951