Maximise discount at a bookstore
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| Type: | discrete NLP |
| Rating: | 2 (easy-medium) |
| Description: | A bookstore has the following discount policy: For each $1 you spend you get 0.1% discount on your next purchase. Example: If you have to buy three books that cost $10, $20 and $30, you could buy the $30 book today, the $10 book tomorrow (on which you'll get a 3% discount), and the $20 book the following day (on which you'll get a 1% discount). Or you could buy the $30 book and the $20 book today, and the $10 book tomorrow (with a 5% discount). What is the cheapest way to buy N books (for given prices) ? |
| File(s): | bookdisc.mos |
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| bookdisc.mos |
(!*********************************************************************
Mosel NL examples
=================
file bookdisc.mos
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A bookstore has the following discount policy:
For each $1 you spend you get 0.1% discount on your next purchase.
Example:
If you have to buy three books that cost $10, $20 and $30, you could
buy the $30 book today, the $10 book tomorrow (on which you'll get
a 3% discount), and the $20 book the following day (on which you'll get
a 1% discount). Or you could buy the $30 book and the $20 book today,
and the $10 book tomorrow (with a 5% discount).
What is the cheapest way to buy N books (for given prices) ?
Based on AMPL model bookdisc.mos by M.J.Chlond
Reference: J. & L. Poniachik, Hard-to-Solve Brainteasers (p16), Sterling
(c) 2008 Fair Issac Corporation
author: S. Heipcke, Jul. 2003, rev. Mar 2013
*********************************************************************!)
model "bookdisc"
uses "mmxnlp"
parameters
N = 8 ! Number of books
D = 4 ! Number of days
DISC = 0.001 ! Discount factor
end-parameters
declarations
BOOKS = 1..N ! Set of books
DAYS = 1..D ! Set of days
COST: array(BOOKS) of real ! Cost of books
ifbuy: array(BOOKS,DAYS) of mpvar ! ifbuy[i,j]=1 if book i bought on day j, 0 otherwise
total: array(DAYS) of mpvar ! Total cost of books on day j
totcost: mpvar ! Total cost of all books
end-declarations
forall(i in BOOKS,j in DAYS) ifbuy(i,j) is_binary
! forall(j in DAYS) total(j) is_integer
! Generate random book prices
setrandseed(3)
forall(i in BOOKS) COST(i):= 10+round(50*random)
! Objective: total cost
totcost = sum(i in BOOKS) COST(i) -
sum(k in DAYS | k>1) DISC*total(k-1)*total(k)
! Total cost per day
forall(j in DAYS) total(j) = sum(i in BOOKS) COST(i)*ifbuy(i,j)
! Every book is bought on one day
forall(i in BOOKS) sum(j in DAYS) ifbuy(i,j) = 1
! Solve the problem
setparam("xnlp_verbose",true)
setparam("xnlp_solver",0)
minimize(totcost)
! Solution printing
TOTCOST:= sum(i in BOOKS) COST(i)
writeln("Total cost: ", strfmt(getsol(totcost),5,2), " (orig: ", TOTCOST, ") discount:",
strfmt((TOTCOST-totcost.sol)/TOTCOST * 100,5,2), "%" )
forall(i in BOOKS) BDay(i):=round(getsol(sum(j in DAYS) j*ifbuy(i,j)))
forall(i in BOOKS)
writeln("Book ", i, " bought on day ", BDay(i), " at ",
strfmt(COST(i)*(1-if(BDay(i)>1, DISC*total(BDay(i)-1).sol,0)),5,2),
" (orig: ", strfmt(COST(i),5,2), ")" )
end-model
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