Return
Multi-objective evolutionary algorithms for a reliability location problem
DOI:10.1016/j.ejor.2019.10.043.png)
Abstract
En 中文
Some location problems with unreliable facilities present two different objectives, one consisting of minimizing the opening and transportation costs if none of the facilities fail and another consisting of minimizing the expected transportation costs. Usually, these different targets are combined in a single objective function and the decision maker can obtain some different solutions weighting both objectives. However, if the decision maker prefers to obtain a diverse set of non-dominated optimal solutions, then such procedure would not be effective. We have designed and implemented two multi-objective evolutionary algorithms for the realibility fixed-charge location problem by exploiting the peculiarities of this problem in order to obtain sets of solutions that are properly distributed along the Pareto-optimal frontier. The computational results demonstrate the outstanding efficiency of the proposed algorithms, although they present clear differences. (C) 2019 Elsevier B.V. All rights reserved.
Keywords:
Location
Multi-objective location problems
Reliability models
Pareto frontier
Multi-objective evolutionary algorithms
Metaheuristics
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
6
Papers:
2.2W
Citations:
6.4W

