An Artificial Bee Colony Algorithm for the Set Covering Problem

2014 ◽  
pp. 53-63 ◽  
Author(s):  
Rodrigo Cuesta ◽  
Broderick Crawford ◽  
Ricardo Soto ◽  
Fernando Paredes
Keyword(s):  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Set Covering ◽  
Covering Problem ◽  
Set Covering Problem ◽  
Bee Colony

scholarly journals Application of the Artificial Bee Colony Algorithm for Solving the Set Covering Problem

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Broderick Crawford ◽  
Ricardo Soto ◽  
Rodrigo Cuesta ◽  
Fernando Paredes
Keyword(s):  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Optimization Problems ◽  
Formal Model ◽  
Set Covering ◽  
Covering Problem ◽  
Set Covering Problem ◽  
Solution Quality ◽  
Bee Colony ◽  
Unicost Set Covering Problem

The set covering problem is a formal model for many practical optimization problems. In the set covering problem the goal is to choose a subset of the columns of minimal cost that covers every row. Here, we present a novel application of the artificial bee colony algorithm to solve the non-unicost set covering problem. The artificial bee colony algorithm is a recent swarm metaheuristic technique based on the intelligent foraging behavior of honey bees. Experimental results show that our artificial bee colony algorithm is competitive in terms of solution quality with other recent metaheuristic approaches for the set covering problem.

An effective binary artificial bee colony algorithm for maximum set k-covering problem

2020 ◽  
Vol 161 ◽  
pp. 113717 ◽  
Author(s):  
Geng Lin ◽  
Haiping Xu ◽  
Xiang Chen ◽  
Jian Guan
Keyword(s):  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Covering Problem ◽  
Bee Colony

Self-Adaptive and Adaptive Parameter Control in Improved Artificial Bee Colony Algorithm

Informatica ◽  
2017 ◽  
Vol 28 (3) ◽  
pp. 415-438 ◽  
Author(s):  
Bekir Afşar ◽  
Doğan Aydin ◽  
Aybars Uğur ◽  
Serdar Korukoğlu
Keyword(s):  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Parameter Control ◽  
Adaptive Parameter ◽  
Bee Colony ◽  
Adaptive Parameter Control ◽  
Self Adaptive

A new approach using a Binary Firefly Algorithm for the Set Covering Problem

2014 ◽  
Author(s):  
Broderick Crawford ◽  
Ricardo Soto ◽  
Miguel Olivares-Suárez ◽  
Fernando Paredes
Keyword(s):  
Firefly Algorithm ◽  
Set Covering ◽  
Covering Problem ◽  
Set Covering Problem ◽  
New Approach

Path Planning of Mobile Robot Using Improved Artificial Bee Colony Algorithm

2020 ◽  
Vol 38 (9A) ◽  
pp. 1384-1395
Author(s):  
Rakaa T. Kamil ◽  
Mohamed J. Mohamed ◽  
Bashra K. Oleiwi
Keyword(s):  
Mobile Robot ◽  
Comparative Research ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Dynamic Control ◽  
Computational Time ◽  
Bee Colony ◽  
Shortest Distance ◽  
Minimum Number ◽  
Cubic Polynomial

A modified version of the artificial Bee Colony Algorithm (ABC) was suggested namely Adaptive Dimension Limit- Artificial Bee Colony Algorithm (ADL-ABC). To determine the optimum global path for mobile robot that satisfies the chosen criteria for shortest distance and collision–free with circular shaped static obstacles on robot environment. The cubic polynomial connects the start point to the end point through three via points used, so the generated paths are smooth and achievable by the robot. Two case studies (or scenarios) are presented in this task and comparative research (or study) is adopted between two algorithm’s results in order to evaluate the performance of the suggested algorithm. The results of the simulation showed that modified parameter (dynamic control limit) is avoiding static number of limit which excludes unnecessary Iteration, so it can find solution with minimum number of iterations and less computational time. From tables of result if there is an equal distance along the path such as in case A (14.490, 14.459) unit, there will be a reduction in time approximately to halve at percentage 5%.

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