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1

What is the difference between risk and uncertainty?

Risk

Present when managers know the possible outcomes of a particular course of action and can assign probabilities to them

Uncertainty

The future is unknown, and probabilities cannot be given for outcomes

2

What is the expected utility theory?

  • Actual decisions made depend on the willingness to accept risk
  • Expected utility theory allows for different attitudes towards risk-taking in decision making
    • Managers are assumed to derive utility from earning profits

 

  • Managers make risky decisions in a way that maximises expected utility of the profit outcomes
  • Utility function measures utility associated with a particular level of profit

    • Index to measure level of utility received for a given amount of earned profit

 

  • Managers attitude toward risk
    • Determined by the manager’s marginal utility of profit
    • Marginal utility (slope of utility curve) determines attitude towards risk

3

How can you tell if someone is risk averse from the utility curve?

You are risk averse with respect to a gamble if you prefer the expected value of the gamble with certainty to the gamble itself.

You are risk averse if the expected value is greater than the certainty equivalent.

4

Explain the flaws in the utility model by comparing it with the prospect model

5

Explain how to carry out project planning and control

Project planning and control

Stage 1: Understand the project environment

  • Geo-social environment
    • Geography and national culture
  • Econo-political environment
    • Economy and government
  • Business environment
    • Customers, competitors and suppliers
  • Internal environment
    • Company strategy, resources and other projects

Stage 2: Project definition

  • Aim, strategy and scope

Stage 3: Project planning

  • Objectives: what is the goal and estimate of cost/ time
  • Project scope: how to approach, feasibility, major tasks
  • Contract requirements: reporting and performance, responsibilities
  • Schedules: activities, tasks, timelines, milestones
  • Resources: budget and budget control
  • Personnel
  • Control: monitoring and evaluating progress and performance
  • Risk analysis

 

  • Identify activities
  • Estimate the times and resources for activities
  • Identify relationship and dependencies between activities
  • Identify time and resource schedule constraints
  • Fix the schedule for time and resources

Stage 4: Technical execution

Stage 5: Project control

  • Earned value analysis
  • Probabilistic analysis: program evaluation and review technique
    • Most likely time (m), optimistic time (a), pessimistic time (b)
    • Mean = a + 4m + b / 6
    • Variance = (b – a / 6) ^2
    • Use expected times to identify critical path, and compute slack and project time
    • Total project variance = Sum of variance of critical path activities
    • Project variance is a measure of the risk involved in the project
  • Crashing project networks
    • Process of reducing time spans on activities so that the project is completed in less time.
    • Focus must be on critical path activities 
    • In order to decide which activity to crash, the ‘crash cost slope’ of each is calculated (crash cost per time period). 
    • Crash the activity on the critical path which has the lowest crash cost slope.

6

Explain the components of a simple queuing system. Give examples

The calling population

  • The population which customers/jobs originate
  • The size can be finite or infinite (the latter is most common)
  • Can be homogeneous (only one type of customer/job) or heterogeneous

The arrival process

  • Determines how, when and where customer/jobs arrive to system
  • The important characteristic is the customers/jobs inter arrival times
  • Correct specification of the arrival process requires data collection of interarrival times and statistical analysis

The queue configuration

  • Specifies the number of queues
  • Their location
  • Effect on customer behaviour (balking or reneging)
  • The max size the queue can hold (infinite/finite capacity)

Service mechanism

  • Can involve one or several service facilities with one or several parallel service channelsThe service provided by a server is characterised by its service time
    • Typically involves data gathering and statistical analysis
    • Most analytical queuing models are based on the assumption of exponentially distributed service times

The queue discipline

  • Specifies the order by which jobs in the queue are served
  • Most common principle is FIFO
  • Other rules are: LIFO, SPIT, EDD
  • Can entail prioritisation based on customer type

 

Examples of world queuing systems:

Commercial queuing systems

  • Commercial organisations serving external customers
  • E.g. dentist, bank, ATM, petrol stations, plumber, garage …

Transportation service systems

  • Vehicles are customers or servers
  • E.g. vehicles waiting at toll stations and traffic lights, trucks or ships waiting to be loaded, taxi cabs, fire engines, lifts and buses

Business – internal service systems

  • Customers receiving service are internal to the organisation providing the service
  • E.g. inspection stations, conveyor belts, computer support …

Social service systems

  • E.g. ER at a hospital, waiting lists for organ transplants, waiting lists for primary school places

7

What are the advantages of multiple line queues vs single line queues

Multiple line vs single

 

Multiple:

  • Service provided can be differentiated
  • Labour specialisation possible
  • Customer has more flexibility
  • Balking behaviour may be deterred: several medium length queues are less intimidating

Single

  • Guarantees fairness
  • No customer anxiety regarding choice of queue
  • Most efficient set up for minimising time in the queue
  • Jockeying (queue switching) is avoided

8

Explain the importance of variability in queuing

If there were no variability, there would be no need for queues to occur

Statistically, the usual measure for indicating the spread of a distribution is its standard deviation sigma. 

However, variation does not only depend on standard deviation.

To normalise standard deviation, it is divided by the mean of its distribution. The measure it called the variation of the distribution.

 

 

9

Describe the different between steady and transient state

Steady state condition

  • Enough time has passed for the system state to be independent of the initial state as well as the elapsed time
  • The probability distribution of the state of the system remains the same over time (is stationary).

Transient condition

  • Prevalent when a queuing system has recently begun operations
  • The state of the system is greatly affected by the initial state and by the time elapsed since operations startedas

10

Explain Little's Law

11

What is the probability that there is n jobs in the system in a queue in the M/M/1 model. 

12

In the M/M/1 model what is:

Expected number of customers in the system

Expected time a job spends in the system

Expected number of customers in queue

Expected time a job spends in the queue

13

What are the different shortage costs in queuing and how do you analyse design costs trade offs?

1. External customers arrive to the system

  • Profit organizations
    • The shortage cost is primarily related to lost revenues “Bad Will”
  • Non profit
    • The shortage cost is related to a societal cost

2. Internal customers arrive to the system

  • The shortage cost is related to productivity loss and associated profit loss

Usually it is easier to estimate the shortage costs in situation 2 than in situation 1.

 

 

 

14

What is Operations Research? Give examples of the different types

OR professionals aim to provide a rational basis for decision making by seeking to understand and structure complex situations and to use this understanding to predict system behaviour and improve system performance.

Done using analytic and numeric techniques to develop and manipulate models of organisational systems.

 

Types of OR models

 

  • Linear programming: objective function and constraints are all linear functions of the decision variables
  • Network flow programming: special case of linear program where situation can be modelled as a network
  • Integer programming: variables are required to take integer values
  • Non-linear
  • Dynamic programming: process described in terms of states, decisions, transitions and returns. Problem is to find sequence that maximises total return.
  • Stochastic programming: Uses random variables for some aspects of the problem. Expression can be written for the expected value of the objective.

15

What is the common terminology for linear programming?

16

What are the assumptions in linear programming?

  • Proportionality

    • contribution of each activity Xj to the value of the objective function Z is proportional to the level of the activity Xj as represented by the CjXj term in the objective function. Similarly, the contribution of each activity to the left-hand side of each functional constraint is proportional to the level of the activity Xj, as represented by the AijXj term in the constraint.

  • Additivity

    • Every function in a linear programming model (whether the objective function or the function on the left-hand side of a functional constraint) is the sum of the individual contributions of the respective activities.

  • Divisibility

    • Decision variables in a linear programming model are allowed to take any values, including non-integer values, that satisfy the functional and non-negativity constraints.

    • Since each decision variable represents the level of some activity, it is assumed that the activities can be run at fractional levels.

  • Certainty

    • The value assigned to each parameter of a linear programming model is assumed to be a known constant.

17

Describe the algorithm for shortest path problem

Objective of the nth iteration:

  • Find the nth nearest node to the origin

 

Input to the nth iteration:

  • n-1 nearest nodes to the origin, including their shortest path and distance from the origin. (These nodes, plus the origin, will be called solved nodes)

 

Candidates for the nth nearest node:

  • Each solved node that is directly connected by a link to one or more unsolved nodes provides one candidate – the unsolved node with the shortest connecting link to this solved node. (Ties provide additional candidates).

 

Calculation of the nth nearest node

  • For each such solved node and its candidate, add the distance between them and the distance of the shortest path from the origin to this solved node. The candidate with the smallest such total distance is the nth nearest node (ties provide additional solved nodes), and its shortest path is the one generating this distance.

 

Applications

  • Minimising the distance travelled
  • Minimising the total cost of a sequence of activities
  • Minimising the total time of a sequence of activities

18

Describe the mimimum spanning tree algorithm and its applications in the real world

Algorithm to solve the MST problem

1. Select any node arbitrarily, and then connect it to the nearest distinct node

2. Identify the unconnected node that is closest to a connected node, and the connect these two nodes. Repeat this step until all nodes have been connected.

3. Tie breaking: Ties for the nearest distinct node (step 1) or the closest unconnected node (step 2) may be broken arbitrarily, and the algorithm must still yield an optimal solution. However, such ties are a signal that there may be (but need not be) multiple optimal solutions. All such optimal solutions can be identified by pursuing all ways of breaking ties to their conclusion.

 

 

Applications of the MST problem

  • Design of telecommunication networks
  • Design of a lightly used transportation network to minimise the total cost of providing the links
  • Design of a network of high voltage electrical power transmission lines
  • Design of a network of wiring on electrical equipment
  • Design of a network of pipelines to connect a number of locations

19

Explain the augmenting path algorithm

An augmenting path is a directed path from the source to the sink in the residual network such that every arc on this path has strictly positive residual capacity. The minimum of these residual capacities is called the residual capacity of the augmenting path because it represents the amount of flow that can feasibly be added to the entire path.

 

1. Identify an augmenting path by finding some directed path from source to sink in the residual network such that every arc on this path has strictly positive residual capacity. (if no augmenting path exists, the net flows already assigned constitute an optimal flow pattern)

 

2. Identify the residual capacity c* of this augmenting path by finding the minimum of the residual capacities of the arcs on this path. Increase the flow in this path by c*.

 

3. Decrease by c* the residual capacity of each arc on this augmenting path. Increase by c* the residual capacity of each arc in the opposite direction on this augmenting path. Return to step 1.

 

Some applications of the maximum flow problem

• Maximise the flow through a company’s distribution network from its factory to its customers

• Maximise the flow through a company’s supply network from its vendors to its factories

• Maximise the flow of oil through a system of pipelines

• Maximise the flow of water through a system of aqueducts

• Maximise the flow of vehicles through a transportation network

20

Explain the max-flow min-cut theorem

Max-flow min-cut theorem

 

The theorem states that, for any network with a single source and sink, the maximum feasible flow from the source to the sink equals the minimum cut value over all cuts of the network.

 

Equivalently, optimality has been attained whenever there exists a cut in the residual network whose value is zero.

21

What are the examples of some logical constraints?

22

What is a supply network?

Supply Network: A set of connected but geographically dispersed firms involved in making and delivery of product/service to end customers

23

What are the different supply network decisions?

Strategic

  • investment in plants: numbers, locations
  • introduction of new products: BOMs used
  • manufacturing technology
  • creation of logistics network
  • make vs buy, supplier selection

Tactical

  • manufacturing system
  • inventory policy
  • procurement policy
  • IT system and information flow
  • customer strategies, demand planning, forecasting

Scheduling of resources (labour, machine, vehicles)

Routing of raw materials and finished products

Solicitations of bids/quotations, order processing

24

What is procurement, explain the difference between direct and indirect procurement

Means purchasing inputs used in the firm’s value chain

  • Raw material
  • Supplies
  • Consumable items
  • Assets such as machinery, lab equipment, office equipment, buildings

Direct purchasing: buying for primary activities

Indirect purchasing: providing supplies and services for support activities

25

What are the different procurement strategies?

Performance based partnership

  • High dependence on one supplier
  • Used for strategic products

Competitive bidding

  • In general, no long-term supply contract, rather multiple sourcing
  • Used for interchangeable products

Securing continuity of supply

  • Securing supply of bottleneck products, if necessary, at additional cost
  • Reducing dependence on supplier by developing alternative products and looking for alternative suppliers

Category management and e-procurement solutions

  • MRO (maintenance, repair, operating supplies) products require a purchasing strategy which is aimed at reducing administrative and logistic complexity      
    • Electronic catalogues
    • Article catalogue (standardisation of product assortment)

26

Plot purchasing’s impact on financial results vs supply risk

27

How do you choose a sourcing strategy?

Single vs. multiple sourcing

  • Assessment with regards to dependence, supply risk and transaction costs

Global vs. local sourcing

  • Local sourcing preferred when product is a high-tech product for which specification often changes; high flexibility and precision required in terms of delivery

Partnership or competitive relationship

  • Competitive relationship mostly used when commodities are purchased, when the products are purchased in in large volumes and when many suppliers are available

Buying on contract or buying on spot basis

  • Contract buying preferred when prices are expected to rise

  • Advisable to choose a mix between contract and spot buying

Price agreement vs. performance agreement

  • Performance agreement often used when services are purchased (Service level agreement)
  • Price agreements might be sufficient if standard quality products are purchased (for example certain types of fabric)

28

What is the objective of locations strategy? What factors impact how it is picked?

Objective of location strategy: to maximise the benefits of location to the firm

 

Location decisions can be determined by:

  • Marketing strategy
    • Compete on cost: find low cost location
    • Compete on level of responsiveness: close to transportation networks/market
  • Cost of doing business
  • Growth
    • Potential access to more customers
    • Expanding product portfolio
  • Depletion of resources
    • Industries where resources determine key success

 

Factors influencing location decisions

  • Economic
    • Tariffs, taxes, trade concession, capital subsidies
  • Temporal
    • Competition, demand patterns, industry dynamics, presence of related industries (clustering), skilled employees’ engagement
  • Physical location
    • Labour cost, developed infrastructure, proximity to market, cost of inputs, competitors locations, specialised inputs
  • Organisational factors
    • Strategic role of a factory amongst multiple plants

29

Why do companies go abroad? What should they consider?

  • M&A
  • Business growth
  • Faster lead times/cost reduction
  • Increase of offshoring

Aspects countries should consider:

  • Country level
    • Political risks, legislation, economic issues (currency), location, labour, availability of suppliers
  • Region level
    • Labour, cost, regulations, proximity to resources, land cost
  • Site level
    • Site size/cost, distribution systems, proximity to suppliers, environmental impact, clustering

30

Why are location decisions so important?

Irreversible allocation of the firm’s capital – long term/strategic decision

Business continuity

Impact on supply chain performance

  • Lead times
  • Inventory
  • Responsiveness to demand
  • Flexibility
  • Quality