RESEARCH TEAM

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RESEARCH TEAM
Industrial Engineering Industrial
Engineering Textiles Engineering, Chem. and
Science Industrial Engineering
INVESTIGATORS R. King S. Fang J. Joines H.
Nuttle
STUDENTS N. Arefi Y. Dai S. Lertworasirikul
MR. Industrial Engineering Ph.D. Industrial
Engineering Ph.D. Industrial Engineering
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OBJECTIVES

• Models and tools to support collaborative efforts
  in a B2B environment.
• Investigate DEA and cooperative game theory for
  partnership formation and contract negotiation.
• Incorporate vagueness and uncertainty through the
  use of Fuzzy Mathematics.
• Demonstrate prototypes.

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DEA DATA ENVELOPMENT ANALYSIS

• A tool for performance assessment of business
  entities performing similar functions under
  uncertain environment
• DEA evaluates business entities based on the
  ratio of weighted sum of outputs to weighted sum
  of inputs
• Example collaborative partner selection
• Inputs unit cost, logistic cost
• Outputs leadtime, quality, reliability,
  capacity
• Incorporate vagueness and uncertainty through
  the use of fuzzy sets, e.g., high unit cost,
  long leadtime.
• ? FUZZY DEA

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DEA METHODOLOGY

• Fuzzy DEA is in the form of fuzzy linear
  program.
• Issue Fuzzy LPs are not well defined due to the
  ambiguity in the ranking of fuzzy sets.

APPROACHES

• a -level based approach
• - Apply parametric programming using a cuts.
• - Four models Best-Best, Best-Worst,
• Worst-Best,
  Worst-Worst

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DEA APPROACHES (continued)

• Possibility approach
• - Deal with uncertainty in fuzzy objectives and
  constraints through the use of possibility
  measures.
• - Possibility programming model
• Credibility approach
• - Replace fuzzy variables by expected credits
  which are derived by using credibility measures.
• - Credibility programming model

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DEA FUZZY DEA SOFTWARE

• Prototype Implementation
• Parameter Setting
• Input output data and membership
  functions
• Data Evaluation
• Calculate of efficiency measures
• Report
• Obtain detailed efficiency measure report

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DEA PARAMETER SETTING
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DEA PARAMETER SETTING
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DEA DATA EVALUATION AND RESULTS
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Game Theoretic Approach to Supply Chain
Coordination

• What is game theory?
• Analysis of situations involving conflicting
  interests.
• Why game theory?
• A softgoods supply chain involves the activity
  and interaction of many players. Individual
  players are usually more interested in maximizing
  their own profits rather than those of the supply
  chain as a whole.
• How to Apply?
• Use channel coordination to optimize the
  performance of the entire supply chain.

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Game Theoretic Approach to Supply Chain
Coordination
Example Capacity allocation problem with market
search
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Game Theoretic Approach to Supply Chain
Coordination
Example Capacity allocation problem with market
search

• Capacity allocation problem
• When the total order from the retailers exceeds
  the supplier's capacity, the supplier needs to
  allocate his/her supply according to allocation
  rules.
• Market search
• Customers, whose demand cannot be satisfied by
  one retailer due to a stockout, may visit another
  retailer.
• Questions
• How should the retailers place orders?
• How to maximize the performance of the entire
  supply chain?

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Game Theoretic Approach to Supply Chain
Coordination

• Channel coordination
• Decentralized system
• The players behave to maximize their own profit.
• ? Use Game theory to find an equilibrium
  solution.
• Centralized system
• Suppose the entire supply chain is owned by one
  company.
• ? Optimal solution which maximizes the total
  expected profit.
• Integrate
• Modify the players' payoffs (e.g., wholesale
  prices) to make the decentralized equilibrium
  solution achieve the total expected profit of the
  centralized system.

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Due-Date Negotiator

• A support system for decision making and
  negotiation between sales management and
  customers.
• Achieve realistic promise dates for order
  delivery.
• Methodology Genetic Algorithm, Fuzzy Modeling
  and Logic.

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Due-Date NegotiatorData entry
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Due-Date NegotiatorOrder loading
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Due-Date NegotiatorReports