6 results about "Incremental costs" patented technology

The present application relates to the technical field of intelligent manufacturing and production scheduling, and particularly relates to a garment multi-process digital twin monitoring method, which comprises the following steps: establishing a process digital twin by using a colored time-delay Petri network and an event dictionary; hierarchically updating a processing time distribution and a line change cost matrix online; obtaining a coupling matrix and calculating a dual price vector by using a regularized optimal transport, and quantifying a work-in-process capacity upper limit as a work-in-process quota; calling a Koopman operator driven counterfactual generator to evaluate an incremental cost and generate a release sequence by optimal sorting within a rolling prediction window; locking and issuing a process path according to the quota, implementing a reversible fine-tuning based on a deviation, and triggering a withdrawal and path diversion according to a topological structure abstract. The present application reduces work-in-process peak value and line change loss, and improves production capacity utilization and stability of on-time delivery.

An online system computes an incremental cost prediction for each of a set of user-treatment pairs to select a set of treatments to apply to users to satisfy a predicted interaction gap. The online system generates a set of candidate user-treatment pairs that each include user data for a user of the online system and treatment data for a treatment of a set of treatments. The online system computes an incremental interaction prediction and a treatment cost prediction for each of the candidate user-treatment pairs by applying an incremental interaction model to the user data and the treatment data in each user-treatment pair. The online system computes incremental cost predictions for each of the user-treatment pairs based on the computed incremental interaction predictions and treatment cost predictions and selects which users to apply treatments to and which treatments to apply to those users based on the incremental cost predictions.

This invention discloses a near-zero energy building design optimization method for service areas based on the NSGA-II algorithm, belonging to the field of building design technology. The method includes: selecting a set of near-zero energy building technologies based on the heat distribution and environmental factors of the service area location; establishing a benchmark building and a building energy consumption analysis model using candidate technologies; using the benchmark building and the building energy consumption analysis model using candidate technologies to obtain energy consumption simulation results, calculating the building's comprehensive energy consumption and incremental cost; based on the comprehensive energy consumption and incremental cost, using the NSGA-II genetic algorithm model to form feasible solutions, and generating multi-dimensional indicators based on the feasible solutions; selecting the optimal near-zero energy building design optimization scheme for the service area through the multi-dimensional indicators. This method utilizes the efficient multi-objective optimization capability of the NSGA-II algorithm to comprehensively analyze various influencing factors and provide energy utilization efficiency for service area buildings in actual operation.

The application relates to the technical field of architectural design, and provides a three-star green building cost optimization method, device, equipment and medium, which can construct a full-life cycle incremental cost prediction model of a green scheme based on the interaction between technical measures, so as to accurately perform building cost prediction; a plurality of to-be-optimized technical measures are selected from each technical measure included in the green scheme through cost sensitivity analysis, so as to lock the technical measures with high conversion rates for optimization; a target function is constructed according to annual total energy consumption, annual carbon emission and the full-life cycle incremental cost prediction model, and a constraint condition is constructed according to a three-star green building scoring rule, so that multiple optimization targets can be considered; a Pareto front solution set of the optimization model is solved based on an orthogonal table, so that the solving efficiency can be improved; and a target scheme is selected from a plurality of candidate schemes according to a value coefficient and a dynamic benefit balance point, so that an optimal three-star green building cost optimization scheme can be reasonably selected.