1 / 14

e-Procurement Using Goal Programming

Explore the integration of optimization techniques and multiple criteria decision analysis for configurable bids in e-procurement using Goal Programming. Learn how to select winning bids efficiently.

atolliver
Download Presentation

e-Procurement Using Goal Programming

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. e-Procurement Using Goal Programming S Kameshwaran kameshn@csa.iisc.ernet.in March 4, 2003

  2. e-Procurement • Internet-based business process for obtaining material and services. • Current Solutions: • Reverse Auctions • www.edeal.com • Optimization Techniques • www.emptoris.com, www.rapt.com • Multiple Criteria Decision Analysis • www.frictionless.com, www.perfect.com eEnterprises Lab, CSA, IISc

  3. Reverse Auctions • Supplier with lowest bid price is selected • Negotiation is only one dimension: Price • Competing on price alone makes the supplier feel de-branded and commoditized • Competitive bidding on price drives the manager down to the point of suppliers’ survival • With multiple attributes to bid, the suppliers can differentiate themselves eEnterprises Lab, CSA, IISc

  4. Optimization Techniques • Business rules are considered in selecting the winning bid(s) • # of winning suppliers: not more than 3 • % of business for a supplier: no more than 40% • Shipment constraints: not less than 20% • Cannot handle multiple attributes eEnterprises Lab, CSA, IISc

  5. Multiple Criteria Decision Analysis • Multiple attributes/criteria are considered in selecting the bids • Example: • Attributes: Cost, lead time, part failure rate • Weights: 0.5, 0.25, 0.25 • Scoring Function: • Cost: {(<$1000, 100), ([$1000-$1200], 80), ([$1200-1500], 60), …} • Lead Time: {([<5 days], 100), ([5-8], 70), …} • Part Failure Rate: {[<20%], 100], ([20-30%], 80), …} eEnterprises Lab, CSA, IISc

  6. Multiple Criteria Decision Analysis (contd) • Scoring function: converts the attributes values to a common virtual currency • Bid: • Bidding language (Attribute, Value): {(Cost, $1100), (Lead Time, 6 days), (Part failure rate, 10%)} • Bid Score: Weighted additive scoring • 0.5 x 80 + 0.25 x 70 + 0.25 x 100 = 82.5 • Bids are ranked by their total score and selected eEnterprises Lab, CSA, IISc

  7. Multiple Criteria Decision Analysis (contd) • Weights and scoring functions are subjective assessments (suppose to reflect the buyer’s true preferences and utility) • Effects of the weights on the output are clear • The weighted additive scheme does not reflect true utility of the buyer if the attributes are interdependent eEnterprises Lab, CSA, IISc

  8. Our Proposal • Configurable bids as bidding language • Goal programming for selecting winning bid(s) • Combines optimization techniques + multiple criteria decision analysis • Allows the suppliers to express their bids in more negotiable format eEnterprises Lab, CSA, IISc

  9. Configurable Bids • Example: Procuring SLR cameras • Attributes: Price, lens focus, warranty • Bid: Functions of Price • Warranty: • 2 yrs: $50 • 5 yrs: $150 eEnterprises Lab, CSA, IISc

  10. Configurable Bids • Each attribute can have more than one value: (lens focus: 3 values, warranty: 2 values) • For each value, Price is given as a function of quantity • Function: Piecewise linear (lens focus) or linear (warranty) • Piecewise linear: Price depends on quantity • Total Cost: Sum of all costs • Buyer configures the bid by choosing the best values for each attribute and the best quantity for each value • 100 units with lens focus28-200mm and 2 yrwarranty + 250 units with lens focus75-300mm and 5 yrwarranty eEnterprises Lab, CSA, IISc

  11. Multiple criteria decision analysis For less # of alternatives Utility and preferences are precisely known Useful for ranking few bids Multiattribute theory, AHA etc. Multiple criteria optimization For very large or infinite # of alternatives Utility and preferences are not explicitly known Useful for configurable bids: finding the best configuration of bids Goal programming, Compromise programming, etc Multiple Criteria Decision Making eEnterprises Lab, CSA, IISc

  12. Goal Programming (GP) • The objectives are formulated as Goals • Minimize cost as Cost <= $20,000 • Buyer specifies target or aspiration level for each objective • Cost: $20,000 • Lead Time: 5 days • Part failure rate: 20% • GP simultaneously satisfies all goals as closely as possible eEnterprises Lab, CSA, IISc

  13. GP Techniques • Weighted GP • Minimizes the weighted sum of deviations from target levels • Lexicographic GP • Minimizes the deviations of goals in preemptive manner • Interactive Sequential GP • Interactive with human intervention • The buyer can change the target levels of goals by learning from the intermediate solutions eEnterprises Lab, CSA, IISc

  14. Thank You • Our technique can handle: • Multiple criteria in bid evaluation • Business rules as side constraints For more details refer: “e-Procurement Using Goal Programming”: S Kameshwaran, Y Narahari, 2003. eEnterprises Lab, CSA, IISc

More Related