SlideServe
Télécharger Obtenir Pro
Menu
Accueil Pro
Préférences
ApparenceLight Aide et commentaires
© SlideServe · v2026

Optimizing Facility Location: P-Median and Maximum Covering Methods Explained

lillith-best avatar
lillith-best
15 diapositives · 288 Views · Nov 12, 2014

This guide explores the P-Median and Maximum Covering Problems in facility location. The P-Median Problem aims to minimize the average weighted distance to customers when locating facilities, considering numerous potential sites, while the Maximum Covering Problem seeks to maximize customer coverage within a specified distance using a minimal number of facilities. Additional methods like break-even analysis and multiple linear regression are discussed to assess fixed and variable costs and identify optimal locations for new facilities. Valuable insights for effective service facility placement are provided.

#optimizing facility location: p-median and maximum covering methods explained #optimizing facility location: p-median and maximum covering methods explained ppt #powerpoint #presentation
Optimizing Facility Location: P-Median and Maximum Covering Methods Explained - slide 1
01 / 15Optimizing Facility Location: P-Median and Maximum Covering Methods Explained
1 / 17

Télécharger la présentation

Optimizing Facility Location: P-Median and Maximum Covering Methods Explained
Une image / un lien ci-dessous est fourni (tel quel) pour télécharger la présentation

Politique de téléchargement : le contenu du site vous est fourni TEL QUEL pour votre information et votre usage personnel ; il ne peut être vendu, concédé sous licence ni partagé sur d’autres sites sans l’accord de son auteur.Le contenu vous est fourni TEL QUEL, pour votre information et votre usage personnel uniquement. Téléchargez la présentation en cliquant sur ce lien. Lors du téléchargement, si vous ne parvenez pas à télécharger une présentation, l’éditeur a peut-être supprimé le fichier de son serveur.Pendant le téléchargement, si vous ne parvenez pas à obtenir une présentation, le fichier a peut-être été supprimé par l’éditeur.

F I N

Plus de contenu associé

Transcription de la présentation

  1. Dr. Ron Lembke Other location methods

  2. P-Median Problem • Minimize average weighted distance to customers, when locating P facilities, where P>=1. • Can consider 100s of locations. • Complex to solve – there is software for this.

  3. Maximum Covering Problem • A facility can “cover” a customer if the customer is within X miles of the facility. • Try to find the best location, and minimum number of facilities to cover all demands. • Cover a table with plates to cover coins sprinkled across it • Math also very hard.

  4. Max Covering 10 = 82%

  5. Max Covering 20 = 97%

  6. Comparison of Results (Using Distances of 150, 200, 250,250) Demand Covered Number of Facilities

  7. Solving large problems

  8. Break-Even Analysis • Determine fixed and variable costs for each location • Fixed cost: how much it would cost to open a facility there • Variable cost: how much total costs would increase as production increases: • Transportation costs • Labor costs • Taxes • Increased construction costs • Hey – this sounds familiar!

  9. Locating Service Facilities with Multiple Linear Regression • Collect data about your current facilities • Median income, # homes sold, education level, population, • Use regression to determine which variables have a significant impact on profits • Choose new facilities which have these characteristics

  10. Incremental or clean-slate approach • Take into account existing facilities • What is the best location to add, given the existing facilities? • What is the best to add, if we were to close down one of the current facilities? • Unfortunately, only P-Median or Maximum Covering can deal with these.

  11. Possible Approach • Use Centroid (Center of Gravity) to find out which general regions to locate in (state / county). • Choose city: • Factor weighting (services, or revenue focus) • Break-even (cost focus)

  12. Method Comparison • Center of gravity minimizes average distance for one facility only. • Breakeven: fixed & variable costs. • Factor weighting considers many other important aspects of location, but does not minimize distance.

  13. Transportation Method You have 3 DCs, and need to deliver product to 4 customers. Find cheapest way to satisfy all demand D 2 A 10 E 4 B 10 F 12 C 10 G 11

  14. Solving Transportation Problems • Trial and Error • Linear Programming – ooh, what’s that?! • Tell me more!

  15. Summary • Other methods: • P-Median: minimize average distances • Maximum covering: get as many customers as possible within 100 miles • Break-even analysis • Approach of centroid followed by factor rating or break-even