A decomposition-based artificial bee colony algorithm for the multi-objective flexible jobshop scheduling problem. Issue 3 (4th March 2022)

• Record Type: Journal Article
• Authors: Sassi, Jamila; Alaya, Ines; Borne, Pierre; Tagina, Moncef
• Is Part Of: Engineering optimization. Volume 54:Issue 3(2022)
• Page Start: 524
• Page End: 538
• Publication Date: 2022-03-04
• Subjects: Multi-objective flexible jobshop scheduling problem -- artificial bee colony (ABC) -- multi-objective optimization -- decomposition-based approach; Engineering design -- Periodicals; Mathematical optimization -- Periodicals; 620.0042
• DOI: 10.1080/0305215X.2021.1884243
• Languages: English
• ISSNs: 0305-215X

Abstract

Abstract : Competition among companies leads to a race in order to improve the management system of their production with respect to the delivery time. In the last few decades, the optimization of production scheduling has attracted the interest of numerous researchers. This article deals with the Flexible Jobshop Scheduling Problem (FJSP) as one of the most challenging combinatorial optimization problems. FJSP is an extension of the classical jobshop scheduling problem, in which an operation can be processed by several different machines. This article presents a new decomposition based artificial bee colony algorithm for the multi-objective FJSP. The proposed algorithm is tested and compared to other algorithms from the literature on benchmarks of the multi-objective FJSP and its superior performance and robust results have been proved.