A review of applications of genetic algorithms in operations management. (November 2018)

• Record Type: Journal Article
• Authors: Lee, C.K.H.
• Is Part Of: Engineering applications of artificial intelligence. Volume 76(2018)
• Page Start: 1
• Page End: 12
• Publication Date: 2018-11
• Subjects: Operations management -- Genetic algorithms -- Review; 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.2018.08.011
• Languages: English
• ISSNs: 0952-1976

Abstract

Abstract: Many decisions in operations management (OM) belong to the class of Non-deterministic Polynomial hard problems and thus heuristic search methods have been applied to improve OM decisions. While genetic algorithms (GAs) are promising tools for searching fast and good solutions in diverse OM areas, future research will benefit from a review of the OM problems solved by GAs. The purpose of this paper is to review the literature on OM with GA-based solutions and to suggest possible gaps from the point of view of researchers and practitioners. A total of 119 peer reviewed journal papers published from 2007 to 2017 are reviewed and analysed methodologically. The applications of GAs in OM are categorized into process and product design, operations planning and control, and operations improvement. Observations from the existing literature are presented and future research directions are suggested. Although GAs have been one of the most popular heuristic approaches for optimization, there are OM problems that are yet to be investigated. The findings of this review pave the path for future research to apply GAs to solve OM problems. Highlights: Review literature on applications of genetic algorithms in operations management. Categorize applications in operations management into 3 themes and 9 decision areas. Provide research and application agenda for further work.