.png){kind=icon}
Return
An interactive algorithm to find the most preferred solution of multi-objective integer programs
.png){kind=icon}
PRE
AI
DOI：10.1007/s10479-014-1545-2.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In this paper, we develop an interactive algorithm that finds the most preferred solution of a decision maker (DM) for multi-objective integer programming problems. We assume that the DM's preferences are consistent with a quasiconcave value function unknown to us. Based on the properties of quasiconcave value functions and pairwise preference information obtained from the DM, we generate constraints to restrict the implied inferior regions. The algorithm continues iteratively and guarantees to find the most preferred solution for integer programs. We test the performance of the algorithm on multi-objective assignment, knapsack, and shortest path problems and show that it works well.
Keywords:
Multi-objective optimization
Integer programming
Linear programming
Convex cones
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
4.5
Papers:
8.1K
Citations:
2.1W
Organization
Cited Papers
ShareSaveA CLASS OF PRACTICAL INTERACTIVE BRANCH AND BOUND ALGORITHMS FOR MULTICRITERIA INTEGER PROGRAMMING
PREAI
ShareSavePortable, consumer‐grade pulse oximeters are accurate for home and medical use: Implications for use in the COVID‐19 pandemic and other resource‐limited environments.png)
JACEP Open
OAAI
JACEP OpenIF0
OAAIShareSave
ShareSave
View more