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Management science, Sensitivity, Problem - Coggle Diagram

- - - - To design and implement new operations.
      - To evaluate ongoing Operations and Procedures.
      - To determine and recommend corrective actions.
  - - - simplex method
        
        objective function & constrain
        
        optimal vlaues
        
        shadow price - how much increase for each
      - proportionality
      - Additivity
      - certinity
      - Continuity
      - Laptop example
- - - - Traveling salesman
        
        Uses
        
        Routing around Cities – travel maps
        
        • Computer Wiring
        
        • Genome Sequencing
        
        • Job Sequencing - sequencing jobs in order to minimise total set-up to
        
        between jobs
        
        Solutions
        
        Every possibility (n1)! - take centuries
        
        Bruce Force
        
        Optimizing methods - Optimal but take long time
        
        Branch and Bound
        
        Heuristic method - good and quick, intuitive
        
        nearest neighbor
        
        Specific set of problem soltions
        
        Brue force approach (Navie) - find optimal
        
        Find all possible and then shortest
        
        Branch and Bound method
        
        Divide to sub problems and solve
        
        Nearest neighbour
        
        intuitive
      - Shortest path between two nodes
      - Spanning tree - extending a network by connecting all nodes
        
        Uses
        
        Construction of paved roads that link several towns
        
        • laying cables of electrical wiring
        
        • In network designing
        
        • To make protocols in network cycles
        
        algorithm
        
        Prim's
        
        Kruskal
      - Critical path (what to compress)
        
        no slack time
        
        The critical path is the longest path of the network diagram
        
        If an activity of this path is delayed, the project will be delayed.
      - Transportation problem (Supply & demand)
        
        Constraints
        
        • capacity constraints
        
        • demand constraints
        
        Solutions
        
        linear programming,
        
        mixed-integer/integer linear programming,
        
        Nonlinear programming,
        
        stochastic programming,
        
        Heuristics and metaheuristics algorithms
      - 6.Assignment problem (Facilities &Jobs)
        
        Uses
        
        Applied when one-to-one assignments are needed
        
        Solutions
        
        Liner programming
      - Multiples objective problems
        
        Multi-Criteria decision making
        
        Solutions
        
        2) analytical hierarchy process
        
        APH
        
        • Popular method for multi-criteria decision making.
        
        • AHP can be used for decision evaluations when there is qualitative, as
        
        well as quantitative criteria in the evaluations. :star:
        
        • AHP provides a comprehensive and rational framework for structuring a
        
        decision problem
        
        examples
        
        1 more item...
        
        approch
        
        4 more items...
        
        Algorithm
        
        1 more item...
        
        3) scoring
        
        1) goal programming, :star:
        
        Modeling
        
        Objective considers as goals
        
        1 more item...
        
        might achchive all the golas or might have to compormise
        
        Goal prioritize Approach
        
        2 more items...
        
        Identify object variables
        
        2 more items...
        
        To satisfy
        
        How to slove
        
        Try to minimize the deviation from actual goal
        
        3 more items...
      - 7.Optmization problem
      - Identification of problem
        
        Product mix / Profit maximization
        
        Single objective
        
        Product mix - but several other objectives are also there
        
        More than 1 objective
        
        Objective conflict with each other
    - - Transportation
        
        Node to node
      - Transshipment
        
        node -> distribution -> customer/node
  - - - Constant time – O (1)
      - Linear time – O (n)
      - Logarithmic time – O (log n)
      - Quadratic time – O (n^2)
      - Cubic time – O (n^3)
- - - - Framework
        
        A list of alternatives.
        
        A list of possible future states/outcomes.
        
        Payoffs/Profits associated with each alternative and
        
        future states/outcomes
        
        Degree of certainty of possible future events.
        
        A decision criterion
  - - - Made under certinity
      - under risk
      - under uncertainty
        
        1.Non- deterministic uncertainty / complete uncertinity
        
        1.max approach
        
        most favorable state
        Select the maximum reward for each decision
        
        3.equal likelihood approach
        
        Any status can occur, highest average payoff
        
        Weighted average / Hurwitz / Reaism
        
        The decision maker needs to specify a degree of optimism (coefficient of optimism α)
        
        The decision maker needs to specify a degree of optimism (coefficient of optimism α)
        
        with possible values from 0 to 1.00.
        
        If the selected value α is closer to 1.00, the decision making is more optimistic
        
        If the selected value α is closer to 1.00, the decision making is more pessimistic
        
        2.Maxmin approach
        
        least favourable state
        Select the minimum reward for each decision
        
        Minimax regret approach
        
        If I knew the future, how much I had regretted my decision
        
        Select the lowest maximum regret
        
        2.Probabilistic uncertainty (risk)
        
        Decision makers know the probability of occurrence for each possible
        outcome
        
        Maximization of expected reward (Expected Monetary Value (EMV))
        
        Represents an average payoff for each alternative, considering the probabilities
        
        Minimization of expected regret (Expected opportunity loss (EOL)
        
        Computes average opportunity loss and select the smallest expected loss
        
        Expected Value of Perfect Information (EVPI)
        
        3.Decision tree
- - - - liner programming
      - non liner
      - integer
      - stochastic
      - dynamic
        
        optimality
        
        resolve recuring or evolving problems
        
        In CS - dynamic = recursion + memorization
      - Linear
        
        Asummptions
        
        Adivity
        
        Proportionality
        
        Certainty
        
        Continuity
        
        Problem
        
        Resolve with simplex
        
        Optimization
        
        Solution
        
        Graphical
        
        https://www.youtube.com/watch?v=-OnRFdLTTlE
        
        Modeling of liner
        
        EX: Bob the carpenter. wood and chair : :pencil2:
        
        Objective function
        
        https://www.youtube.com/watch?v=uPfbNyAla6c
        
        constrains
        
        parameters
        
        decision variable
        
        To optimize