Fitness Function in ABC Algorithm for Uncapacitated Facility Location Problem

By Yusuke Watanabe, Mayumi Takaya, Akihiro Yamamura. ICT-EurAsia/CONFENIS, 2015

297 citations recorded by the source corpus.

We study the fitness function of the artificial bee colony algorithm applying to solve the uncapacitated facility location problem. Our hypothesis is that the fitness function in the artificial bee colony algorithm is not necessarily suitable for specific optimization problems. We carry out experiments to examine several fitness functions for the artificial bee colony algorithm to solve the uncapacitated facility location problem and show the conventional fitness function is not necessarily suitable.

Subfields: Computer Networks and Communications, Computer Vision and Pattern Recognition, Industrial and Manufacturing Engineering

View Paper: https://www.semanticscholar.org/paper/19262b728237a7e4bd1b9848718dd852c85c3e4c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Ling Shao

In Computer Vision and Pattern Recognition

1. Fan Zhu
2. Mengyang Yu
3. Ling Shao
4. Jianbing Shen
5. Wenguan Wang
6. Dacheng Tao
7. Luc Van Gool
8. Wanqing Li

Citations in the corpus

• Cross-Modality Submodular Dictionary Learning for Information Retrieval (2014, result): “In order to determine the number of selected elements in the subset B , previous work [ 6 ] , [ 18 ] , [ 13 ] , [ 14 ] introduced a penalty term to control the growth of B .”
• The recoverable robust facility location problem (2015, background): “Despite its simple definition, the UFL is known to be NP-Hard [18]; however, the current advances in MIP solvers, computing machinery and the development of sophisticated preprocessing techniques allow to find optimal or nearly optimal solutions for large instances of the UFL within reasonable time.”