Research Progress and Prospects of Job Shop Scheduling Algorithms

Against the backdrop of exponential growth in the global manufacturing industry and continued strengthening of the industry's competitive landscape, related companies are caught in the dilemma of surging demand for customer customisation and high production and operating costs. To cope with this trend, enterprises are gradually transforming from the traditional mass production mode to the small-lot, customised production mode. In this context, intelligent scheduling technology, as a core enabling tool to break through the bottleneck of production efficiency and realise flexible production response, has attracted the attention of a large number of scholars. In this paper, the classical job shop scheduling problem (JSSP) is selected as the research object, and systematic knowledge restructuring and multidimensional deconstruction analyses are carried out through literature tracing. Firstly, this paper comprehensively comprehends the classification and model construction of JSSP; secondly, it scientifically classifies the existing solution algorithms and deeply discusses the advantages and limitations of various algorithms; finally, based on the synthesis of the latest research developments at home and abroad, the potential development paths of JSSP in future research and application areas are discussed in depth, aiming to provide theoretical reference and practical guidance for researchers and practitioners in related fields.