Methods and Algorithms for Flexible Job Shop Scheduling − A State of the Art

Guliashki, Vassil; Kirilov, Leoneed; Marinova, Galia

doi:10.2478/cait-2025-0009

Abstract

The Job Shop Scheduling Problem (JSSP) attracts many researchers due to its combinatorial nature and its discovery in numerous practical applications. This type of problem is characterized by high computational complexity; therefore, solving large-sized problems is not accessible with exact optimization methods. Very often, real JSSP problems can be presented as Flexible Job Shop Scheduling Problems (FJSSP). For these problems, there are single-criterion and multi-criteria mathematical models. On the other hand, the ways to solve this type of problems include exact methods and heuristic or metaheuristic algorithms. This paper the aim to review the progress of research in the field of solving FJSSP over the last 10 years, as well as to show current trends for future scientific developments in this area.

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Methods and Algorithms for Flexible Job Shop Scheduling − A State of the Art

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