Abstract: A system for optimizing blending for mass production produced products. The system may include a processor configured to aggregate material information, aggregate production information, model consumer liking of the at least one product, and provide plan information for controlling production resources based on the material information, the production information, and the consumer liking. The material information can be associated with a product input of the at least one product. The production information can be associated with the production resources of the at least one product.

Abstract: A system for optimizing blending. The system can include a processor configured to aggregate material information, aggregate production information, model consumer liking of the at least one product, and provide plan information for controlling production resources based on the material information, the production information, and the consumer liking. The material information can be associated with a product input of the at least one product. The production information can be associated with the production resources of the at least one product.

Abstract: A system for optimizing blending. The system can include a processor configured to aggregate material information, aggregate production information, model consumer liking of the at least one product, and provide plan information for controlling production resources based on the material information, the production information, and the consumer liking. The material information can be associated with a product input of the at least one product. The production information can be associated with the production resources of the at least one product.

Abstract: A system for optimizing blending. The system can include a processor configured to aggregate material information, aggregate production information, model consumer liking of the at least one product, and provide plan information for controlling production resources based on the material information, the production information, and the consumer liking. The material information can be associated with a product input of the at least one product. The production information can be associated with the production resources of the at least one product.

Abstract: A blending plan for concentrated consumable products, such as liquid food and beverage products, may be optimized by utilizing a computer device executing a software algorithm. The computing device receives one or more inputs associated with the blending of various components employed in producing quantities of a concentrated consumable product over a predetermined time interval. The computing device may be further utilized to apply constraints to each of the one or more inputs. The constraints may be utilized to enforce quality, raw material and component bounds, supply and demand requirements, product and component supply balance, capacity limitations and business rules in order to minimize costs and complexity associated with the production of a concentrated consumable product while maximizing quality, thereby optimizing the blending plan.

Abstract: A blending plan for concentrated consumable products, such as liquid food and beverage products, may be optimized by utilizing a computer device executing a software algorithm. The computing device receives one or more inputs associated with the blending of various components employed in producing quantities of a concentrated consumable product over a predetermined time interval. The computing device may be further utilized to apply constraints to each of the one or more inputs. The constraints may be utilized to enforce quality, raw material and component bounds, supply and demand requirements, product and component supply balance, capacity limitations and business rules in order to minimize costs and complexity associated with the production of a concentrated consumable product while maximizing quality, thereby optimizing the blending plan.

Abstract: A blending plan for not-from-concentrate consumable products, such as liquid food and beverage products, may be optimized by utilizing a computing device executing a software algorithm. The computing device may receive inputs associated with a blending plan for the production of a consumable product over a predetermined time interval. The computing device may further apply constraints to each of the one or more inputs. The computing device may further assess penalties in a mathematical function which includes the inputs and the constraints. The function may then generate an optimized blending plan, using the applied constraints and the penalties, which minimizes costs and complexity associated with the production of the consumable product while maximizing quality.

Abstract: A system for optimizing blending. The system can include a processor configured to aggregate material information, aggregate production information, model consumer liking of the at least one product, and provide plan information for controlling production resources based on the material information, the production information, and the consumer liking. The material information can be associated with a product input of the at least one product. The production information can be associated with the production resources of the at least one product.

Abstract: A system for optimizing blending. The system can include a processor configured to aggregate material information, aggregate production information, model consumer liking of the at least one product, and provide plan information for controlling production resources based on the material information, the production information, and the consumer liking. The material information can be associated with a product input of the at least one product. The production information can be associated with the production resources of the at least one product.

Abstract: A system for simulating drink production. The system can include a processor configured to aggregate existing material information, receive predicted material information, aggregate production information, receive timing information of at least one drink product, model consumer liking of the at least one drink product, and determine a production plan based on the existing material information, the predicted material information, the production information, the timing information and the consumer liking. The existing material information can be associated with a beverage input of at least one drink product. The predicted material information can be associated with the beverage input of the at least one drink product. The production information is associated with production resources of the at least one drink product.

Abstract: A system for managing an agricultural commodity based production system. The system can include a processor configured to aggregate material information, aggregate production information, receive production limits, receive product limits, and at least one of maximize or minimize a parameter of a product lineup including the at least one product based on the aggregate material information, the production information, the production limits; and the product limits. The material information can include quantity information, availability information, and quality information. The material information can be variable. The production information is associated with production resources of the at least one product. The production limits can establish operating tolerances of the production resources. The product limits can establish valid product configurations of at least one product.

Abstract: A system for simulating drink production. The system can include a processor configured to aggregate existing material information, receive predicted material information, aggregate production information, receive timing information of at least one drink product, model consumer liking of the at least one drink product, and determine a production plan based on the existing material information, the predicted material information, the production information, the timing information and the consumer liking. The existing material information can be associated with a beverage input of at least one drink product. The predicted material information can be associated with the beverage input of the at least one drink product. The production information is associated with production resources of the at least one drink product.

Abstract: A system for optimizing blending. The system can include a processor configured to aggregate material information, aggregate production information, model consumer liking of the at least one product, and provide plan information for controlling production resources based on the material information, the production information, and the consumer liking. The material information can be associated with a product input of the at least one product. The production information can be associated with the production resources of the at least one product.