A review on the studies employing artificial bee colony algorithm to solve combinatorial optimization problems. (October 2022)

• Record Type: Journal Article
• Authors: Kaya, Ebubekir; Gorkemli, Beyza; Akay, Bahriye; Karaboga, Dervis
• Is Part Of: Engineering applications of artificial intelligence. Volume 115(2022)
• Publication Date: 2022-10
• Subjects: Artificial bee colony -- ABC algorithm -- Combinatorial optimization; Engineering -- Data processing -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Ingénierie -- Informatique -- Périodiques; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; Artificial intelligence; Engineering -- Data processing; Expert systems (Computer science); Periodicals; 620.00285
• DOI: 10.1016/j.engappai.2022.105311
• Languages: English
• ISSNs: 0952-1976

Abstract

Abstract: The ABC algorithm is one of the popular optimization algorithms and has been used successfully in solving many real-world problems. Numeric, binary, integer, mixed integer and combinatorial optimization problems are among the areas where ABC algorithm is used. Combinatorial optimization problems appear in many problem groups in real life. Due to the nature of these problems, they are classified as difficult problems. It is seen in the literature that hundreds of studies have been conducted using the ABC algorithm in solving combinatorial optimization problems. In this study, combinatorial optimization approaches based on ABC algorithm are examined in detail, in order to shed light on new studies. Combinatorial optimization problems are analyzed under 12 groups. These are assembly/disassembly, bioinformatic, graph coloring, routing, rule mining, aware web service composition, socially network analysis, team orienteering, timetabling, traveling salesman, vehicle routing and other problems. 251 studies of related problems are examined. Brief summaries of the studies on combinatorial optimization problems are presented and the ABC algorithm-based approaches used are introduced. Tables, images and equations are included for better understanding of the subject. The added mechanisms to improve the local search capability of the ABC algorithm are evaluated. Neighborhood operators used in ABC algorithms are examined. The used selection schemes and initial populations determination approaches are given. It is stated which mechanisms are included in hybrid approaches based on ABC algorithm. The test instances used to evaluate the performances of the ABC algorithms are mentioned.