1 / 12

Formulation of cut order planning problem network

Mathematical models

Dharshini5
Télécharger la présentation

Formulation of cut order planning problem network

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. THIS IS YOUR PRESENTATION TITLE

  2. The cut order planning problem involves determining the most efficient way to cut raw materials (such as wood, metal, or fabric) into smaller pieces to fulfill a set of orders while minimizing waste. This problem can be formulated as a network optimization problem, typically using integer linear programming (ILP) or similar techniques. Here's a basic outline of how you can formulate the problem using ILP: ~ Parameters ~ Decision Variables ~ Objective Function ~ Constraints This formulation ensures that each order is satisfied while minimizing the total cost and adhering to the constraints on raw material usage. The binary variables determine which raw materials are cut to fulfill each order.

  3. SHADE SORTING OF COLORED SAMPLES TO AN ACCEPTABLE TOLERANCE BY HIERARCHICAL CLUSTERING:

  4.  EXAMPLE PYTHON IMPLEMENTATION:   python from scipy.cluster.hierarchy import dendrogram, linkage import matplotlib.pyplot as plt # Example data (RGB values) X = [[255, 0, 0], [0, 255, 0], [0, 0, 255], [255, 255, 0], [0, 255, 255]] # Perform hierarchical clustering Z = linkage(X, 'ward') # Plot dendrogram plt.figure(figsize=(10, 5)) dendrogram(Z) plt.title('Hierarchical Clustering Dendrogram') plt.xlabel('Sample Index') plt.ylabel('Distance') plt.show() This example demonstrates how to perform hierarchical clustering using the Ward method and plot the resulting dendrogram. You can customize the distance metric and clustering method based on your specific requirements

  5. Inventory control for factory parts involves mathematical modeling and analysis to optimize the management of inventory levels while balancing the costs associated with holding inventory, ordering, and stockouts. Various mathematical techniques are employed to achieve efficient inventory management: Pharetra Purus # Inventory Models # Demand Forecasting # Inventory Costs Analysis #Optimization Techniques  Overall, inventory control for factory parts relies heavily on mathematical techniques to effectively manage inventory levels, optimize ordering decisions, and minimize costs while ensuring timely availability of parts to support production operations

  6. Search for and tracking of submarines: Searchingforandtrackingsubmarinesisacomplextaskthatinvolvesvarious mathematicalprinciplesandtechniques,includingsignalprocessing, estimationtheory,optimization,andprobabilitytheory.Here'sahigh-level overviewofsomemathematicalaspectsinvolved: 1.SignalProcessing: ~SonarSignals 2.EstimationTheory: ~KalmanFiltering ~ParticleFiltering 3.Optimization: ~OptimalSensorPlacement ~TrajectoryOptimization 4.ProbabilityTheory: ~BayesianInference ~HiddenMarkovModels(HMMs) 5.DataFusion: WWW.YOURWEBSITE.COM ~Multi-SensorFusion

  7. By leveraging these mathematical principles and techniques, naval forces and researchers can develop advanced systems for searching, detecting, and tracking submarines with high accuracy and efficiency.

  8. The motion of a space vehicle can be described using mathematical principles such as Newton's laws of motion and equations of motion. These equations can involve concepts like velocity, acceleration, position, and time. Additionally, orbital mechanics and celestial mechanics are often employed to model the trajectory and behavior of space vehicles in various scenarios, including orbiting, rendezvous, and interplanetary travel. MOTION OF A SPACE VEHICLE: www.yourwebsite.com

  9. SCELERISQUE mathematical modeling is crucial for designing and evaluating aircraft systems, including avionics, propulsion, aerodynamics, and weapon systems. Computational methods are used to simulate flight dynamics, control systems, and sensor performance to ensure the aircraft meets survivability and effectiveness requirements. Overall, mathematics plays a fundamental role in understanding, designing, and optimizing aircraft survivability and effectiveness in various operational environments.

  10. CRAS A PELLENTESQUE Maecenas fermentum felis mollis, viverra eros non, consequat odio. Fusce eget mattis massa. Nullam at laoreet neque. Vestibulum dictum pretium vehicula. Maecenas luctus tortor felis, non fringilla lorem lobortis ac. Cras a pellentesque urna, sed bibendum dui.

  11. DONEC PHARETRA .Mathematically, it involves analyzing the interference patterns created by combining these signals to construct high-resolution images of astronomical sources. Key mathematical concepts involved include Fourier transforms, aperture synthesis, and signal processing techniques such as correlation and deconvolution. These mathematical tools help astronomers reconstruct images of astronomical objects with much higher resolution

  12. THANKS  FOR LISTENING

More Related