Unit 4 of 4 · MBA Sem 1

Unit 4: Transportation, assignment and project scheduling

Quantitative Techniques notes · PTU syllabus (MBA 103-18)

3 min read4 topics10 exam questions
On this page
  1. Unit summary
  2. The transportation problem
  3. The assignment problem and Hungarian method
  4. Network models: PERT and CPM
  5. Slack and float; PERT probabilities
  6. Key terms
  7. Quick revision
  8. Important questions

Unit summary

Shipping goods, assigning jobs and scheduling projects are classic optimisation problems. This unit covers the transportation problem — North-West Corner, Least Cost and Vogel's methods with the MODI optimality test — the assignment problem by the Hungarian method, and PERT/CPM project networks with scheduling and the critical path.

After this unit you can

  • Find initial solutions of transportation problems by NWC, LCM and VAM
  • Test and improve solutions by the MODI method
  • Solve assignment problems by the Hungarian method
  • Construct PERT/CPM networks and find the critical path

PTU syllabus topics

  • Transportation problem — North-West Corner
  • Least Cost and Vogel's Approximation methods
  • optimality testing via MODI method
  • assignment problem via the Hungarian method
  • PERT/CPM project networks
  • scheduling with known activity times
  • critical path
ComparisonInitial solutions to a transportation problem
How
Quality

North-West Corner

Start top-left, fill in order

Quick, often far from optimal

Least Cost

Fill the cheapest cell first

Better

Vogel's Approximation

Use penalties (difference of two lowest costs)

Usually closest to optimal

1

Topic 1

The transportation problem

Minimise the cost of transporting goods from m sources (supply) to n destinations (demand).

  • Balanced problem: total supply = total demand; else add a dummy row/column with zero cost.
  • Methods for initial basic feasible solution (IBFS): North-West Corner Rule, Least Cost Method, Vogel's Approximation Method (VAM) — VAM usually gives the best start.
  • A non-degenerate solution has m + n − 1 allocations; fewer = degeneracy (add ε).
  • Optimality test: MODI (u–v) method — compute ui + vj = cij for occupied cells; for unoccupied cells, Δij = cij − (ui + vj); if all Δij ≥ 0 the solution is optimal; otherwise form a closed loop and reallocate.

Example

VAM: for each row and column, compute the penalty (difference between the two lowest costs); allocate as much as possible to the lowest-cost cell in the row/column with the highest penalty; repeat.

Example

Three factories (supply 20, 30, 50) and three warehouses (demand 30, 40, 30) — balanced (100 = 100). North-West Corner: allocate 20 to F1–W1; then F2–W1 10, F2–W2 20; F3–W2 20, F3–W3 30 — five allocations = m + n − 1 = 5 (non-degenerate).

2

Topic 2

The assignment problem and Hungarian method

Assign n jobs to n persons (one each) to minimise total cost or time.

ProcessHungarian method
  1. 1

    Row reduction

    Subtract the smallest element of each row

  2. 2

    Column reduction

    Subtract the smallest element of each column

  3. 3

    Cover all zeros with minimum lines

  4. 4

    If lines = n, make assignments

  5. 5

    Else subtract the smallest uncovered element from uncovered cells, add to intersections

  6. 6

    Repeat and assign one zero in each row and column

Example

Costs (rows A, B, C; columns J1, J2, J3): A 9, 2, 7; B 6, 4, 3; C 5, 8, 1. Row reduction gives A 7, 0, 5; B 3, 1, 0; C 4, 7, 0. Column reduction (subtract 3 from J1) gives A 4, 0, 5; B 0, 1, 0; C 1, 7, 0. Three lines cover all zeros → assign A–J2 (2), B–J1 (6), C–J3 (1): total cost 9.

  • Variations: maximisation (convert by subtracting from the largest), unbalanced (add dummy), restricted assignments (infinite cost), multiple optimal solutions.

Travelling salesman problem

A salesman visits each city once and returns home with minimum total distance — solved as an assignment problem with no self-assignment (diagonal = ∞) and the additional constraint that the solution must form a single complete tour (no sub-tours); if the assignment gives sub-tours, the next best zero is tried.

3

Topic 3

Network models: PERT and CPM

ComparisonPERT vs CPM
PERT
CPM

Origin

US Navy Polaris project (1958)

DuPont and Remington Rand (1957)

Activity times

Probabilistic — three estimates

Deterministic — one estimate

Orientation

Event-oriented

Activity-oriented

Used for

R&D, new projects with uncertainty

Construction, repetitive projects

Cost

Time-focused

Time–cost trade-off (crashing)

Construction of networks

  • Activity (arrow), event (node), dummy activity (dashed — shows dependency without time).
  • Rules: each activity has one arrow; no loops; no dangling events; only one start and one end node; dummies to avoid two activities with the same start and end nodes.
ProcessCritical path computation
  1. 1Forward pass

    Earliest start (ES) and earliest finish (EF)

  2. 2Backward pass

    Latest finish (LF) and latest start (LS)

  3. 3Compute floats
  4. 4Critical activities have zero total float
  5. 5Critical path = longest path = project duration
4

Topic 4

Slack and float; PERT probabilities

Key formulasFloat and PERT formulas
  • Total float

    LS − ES (or LF − EF)

  • Free float

    ES of successor − EF of the activity

  • Independent float

    ES of successor − LF of predecessor − duration

  • Event slack

    Latest event time − Earliest event time

  • PERT expected time

    te = (to + 4tm + tp) ÷ 6

  • Activity variance

    σ² = [(tp − to) ÷ 6]²

  • Probability of completion

    Z = (Scheduled time − Expected project time) ÷ √(Sum of critical variances)

Example

Activity estimates: optimistic 4, most likely 7, pessimistic 16 days → te = (4 + 28 + 16) ÷ 6 = 8 days; σ² = (12 ÷ 6)² = 4. If the critical path expected time is 40 days with total variance 16 (σ = 4), the probability of finishing in 44 days: Z = (44 − 40) ÷ 4 = 1 → about 84%.

Key terms

Transportation problem
Minimising cost of shipping from sources to destinations
VAM
Vogel's approximation method using penalties
MODI method
Optimality test using ui + vj = cij
Hungarian method
Algorithm for assignment problems
Critical path
Longest path determining project duration

Quick revision

  • Balanced TP; IBFS by NWC, LCM, VAM; m + n − 1 allocations.
  • MODI: Δij ≥ 0 for optimality; loop to improve.
  • Hungarian: row/column reduction, cover zeros, adjust.
  • PERT te = (to + 4tm + tp)/6; CPM deterministic.
  • Critical activities have zero float.

Important exam questions

Practice questions written to the PTU exam pattern for this unit's syllabus: short answers (Section A style) and long answers (Sections B and C style).

Short-answer questions

  1. Q1.What is a balanced transportation problem?
  2. Q2.State the North-West Corner rule.
  3. Q3.What is the MODI method?
  4. Q4.How is an unbalanced assignment problem solved?
  5. Q5.Distinguish PERT and CPM.
  6. Q6.What is total float?

Long-answer questions

  1. Q1.Explain methods of finding an initial basic feasible solution of a transportation problem.
  2. Q2.Explain the MODI method of testing optimality.
  3. Q3.Explain the Hungarian method of solving assignment problems.
  4. Q4.Explain the construction of networks and determination of the critical path in PERT/CPM.

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