1. Shortest Paths using LP: (7 points)
Shortest paths can be cast as an LP using distances dv from the source s to a particular vertex v as
• We can compute the shortest path from s to t in a weighted directed graph by solving.
ds = 0
dv – du ≤ w(u,v) for all (u,v)E
• We can compute the single-source by changing the objective function to
max ∑𝑣∈𝑉 𝑑𝑣
Use linear programming to answer the questions below. State the objective function and constraints for
each problem and include a copy of the LP code and output.
a) Find the distance of the shortest path from G to C in the graph below.
b) Find the distances of the shortest paths from G to all other vertices.
CS 325 HW 6
2. Product Mix: (7 points)
Acme Industries produces four types of men’s ties using three types of
material. Your job is to determine how many of each type of tie to make each month. The goal is to
maximize profit, profit per tie = selling price – labor cost – material cost. Labor cost is $0.75 per tie for
all four types of ties. The material requirements and costs are given below.
Type of Tie
Silk Polyester Blend 1
Silk 0.125 0 0 0
Polyester 0 0.08 0.05 0.03
Cotton 0 0 0.05 0.07
Formulate the problem as a linear program with an objective function and all constraints. Determine the
optimal solution for the linear program using any software you want. Include a copy of the code and
output. What are the optimal numbers of ties of each type to maximize profit?
Material Cost per yard Yards available
Silk $20 1,000
Polyester $6 2,000
Cotton $9 1,250
Type of Tie
Silk = s Poly = p Blend1 = b Blend2 = c
Selling Price per tie $6.70 $3.55 $4.31 $4.81
Monthly Minimum units 6,000 10,000 13,000 6,000
Monthly Maximum units 7,000 14,000 16,000 8,500
CS 325 HW 6
3. Transshipment Model (10 points)
This is an extension of the transportation model. There are now intermediate transshipment points
added between the sources (plants) and destinations (retailers). Items being shipped from a Plant (pi)
must be shipped to a Warehouse (wj) before being shipped to the Retailer (rk). Each Plant will have an
associated supply (si) and each Retailer will have a demand (dk). The number of plants is n, number of
warehouses is q and the number of retailers is m. The edges (i,j) from plant (pi)to warehouse (wj) have
costs associated denoted cp(i,j). The edges (j,k) from a warehouse (wj)to a retailer (rk) have costs
associated denoted cw(j,k).
The graph below shows the transshipment map for a manufacturer of refrigerators. Refrigerators are
produced at four plants and then shipped to a warehouse (weekly) before going to the retailer.
Below are the costs of shipping from a plant to a warehouse and then a warehouse to a retailer. If it is
impossible to ship between the two locations an X is placed in the table.
cost W1 W2 W3
P1 $10 $15 X
P2 $11 $8 X
P3 $13 $8 $9
P4 X $14 $8
CS 325 HW 6
cost R1 R2 R3 R4 R5 R6 R7
W1 $5 $6 $7 $10 X X X
W2 X X $12 $8 $10 $14 X
W3 X X X $14 $12 $12 $6
The tables below give the capacity of each plant (supply) and the demand for each retailer (per week).
P1 P2 P3 P4
Supply 150 450 250 150
R1 R2 R3 R4 R5 R6 R7
Demand 100 150 100 200 200 150 100
Part A: Determine the number of refrigerators to be shipped from the plants to the warehouses and
then warehouses to retailers to minimize the cost. Formulate the problem as a linear program with an
objective function and all constraints. Determine the optimal solution for the linear program using any
software you want. What are the optimal shipping routes and minimum cost?
Part B: Due to old infrastructure Warehouse 2 is going to close eliminating all of the associated routes.
What is the optimal solution for this modified model? Is it feasible to ship all the refrigerators to either
warehouse 1 or 3 and then to the retailers without using warehouse 2? Why or why not?
Part C: Instead of closing Warehouse 2 management has decide to keep a portion of it open but limit
shipments to 100 refrigerators per week. Is this feasible? If so what is the optimal solution when
warehouse 2 is limited to 100 refrigerators?
Note: Include a copy of the code for all parts of the problem.
CS 325 HW 6
4. Making Change (6 points)
Given coins of denominations (value) 1 = v1 < v2< … < vn, we wish to make change for an amount A using as few coins as possible. Assume that vi’s and A are integers. Since v1= 1 there will always be a solution. Solve the coin change using integer programming. For each the following denomination sets and amounts formulate the problem as an integer program with an objective function and constraints, determine the optimal solution. What is the minimum number of coins used in each case and how many of each coin is used? Include a copy of your code. a) V = [1, 5, 10, 25] and A = 202. b) V = [1, 3, 7, 12, 27] and A = 293