A review on evolution of production scheduling with neural networks

Using CBR as Design Methodology for Developing Adaptable Decision Support Systems

“…As a consequence, in recent decades various methods have been proposed for the modelling and solution of particular scheduling problems (Akyol & Bayhan, 2007). In the particular case of cooperative poultry farms, the accurate coordination of centralized feed supply (production and distribution) between scattered farms is of utmost importance for both the main feed manufacturer and participating farmers.…”

Nash game model for optimizing market strategies, configuration of platform products in a Vendor Managed Inventory (VMI) supply chain for a product family

“…Fortunately, these difficulties can be overcome by GA (genetic algorithm). We therefore adopt it as it is almost mature and widely used by other researchers (see Akyol and Bayhan, 2007;Liu, 1998;Solnon et al, 2008).The roulette wheel selection approach (Yang et al, 2007) and the elitist strategy (Onwubolu and Muting, 2001) are integrated to ensure that the best chromosomes can survive in the evolution.…”

An adaptive SVM-based real-time scheduling mechanism and simulation for multiple-load carriers in automobile assembly lines

“…Artificial neural network (ANN), a typical ML approach, is widely used in real applications including prediction and forecasting, clustering, pattern recognition, classification, function approximation. 22 Min and 30 proposed a dynamic scheduling rule selection method combing with a feature selection algorithm and dispatching rule classification algorithm. SVM is sometimes combined with GAs, ANNs, DTs or other optimization algorithms to tackle real-time scheduling problems.…”