dtonhofer

dtonhofer

Functional Programming in Java, Second Edition: p 148 "An optimization problem" & "Plain-Vanilla Recursion" problems

On page 148, “An optimization problem” we read:

We’ll employ a solution for a company that buys rods at wholesale and sells them at retail. They figured that by cutting the rods into different sizes, they could maximize profits. The price that the company can charge for different lengths of rod changes often, so the company wants us to write a program to reveal what the maximum profit would be for a given size of rod. 

The above is not computing the profit, but computing the revenue. The profit is revenue - expenses, but we don’t know the expenses, it might include manpower costs, machine costs etc.

The problem would also be more interesting if a rod of length 1 could only be sold at price 0 (i.e. it is wastage), at price 2 it’s too easy.

More seriously, on page 149, “Plain-Vanilla Recursion”, we read:

Continuing with this approach, we find that the maximum profit [revenue] for an arbitrary length n is the maximum of the profits [revenues] from each of the possible 2^(n-1) cuts length. That is, max(no cut, cut(1, n - 1), cut(2, n - 2), …), for a given length n.

It don’t understand the max() notation here, there should probably at least be revenue(.) of a cut schedule in there :thinking:

In any case, the 2^(n-1) is imprecise Not considering symmetries, each cut point at marginal width 1 of which there are n-1, for example for width = 6:

≣|≣|≣|≣|≣|≣

can be switched on or off, giving us indeed 2^(n-1) “cut schedules.”

But considering all symmetries (to collapse similar “cut schedules”, consider only “cut schedules” where the width of a cut is monotonically (but not strictly) increasing from left to right), the number of possible “cut schedules” for width = n is then given by

[A000041 - OEIS] - the number of partitions of n (the partition numbers)

(I didn’t find this by myself, I first wrote the program to list the schedules, then duckduckgoed the sequence)

For example for width = 6, there are only 11 distinct ways to cut:

Number of ways of cutting for width = 6: 11
≣≣≣≣≣≣
≣|≣≣≣≣≣
≣≣|≣≣≣≣
≣≣≣|≣≣≣
≣|≣|≣≣≣≣
≣|≣≣|≣≣≣
≣≣|≣≣|≣≣
≣|≣|≣|≣≣≣
≣|≣|≣≣|≣≣
≣|≣|≣|≣|≣≣
≣|≣|≣|≣|≣|≣

Only increasing slowly:

|Width|Schedules|2^(n-1)|
|---|---|---|
|1|1|1|
|2|2|2|
|3|3|4|
|4|5|8|
|5|7|16|
|6|11|32|
|7|15|64|
|8|22|128|
|9|30|256|
|10|42|512|
|11|56|1024|
|12|77|2048|
|13|101|4096|
|14|135|8192|
|15|176|16384|
|16|231|32768|
|17|297|65536|
|18|385|131072|
|19|490|262144|
|20|627|524288|

Code to compute the above (unabashedly recursive, not memoizing/caching, slows down quickly with larger n. The SortedSet could be replaced by an array and “insertion sorting” if one wants “efficiency”)

import org.junit.jupiter.api.Test;

import java.util.*;
import java.util.stream.IntStream;

import static java.util.stream.Collectors.joining;

class CutSchedule implements Comparable<CutSchedule> {

    public List<Integer> increasingWidths = new ArrayList<>();

    public boolean verify() {
        if (increasingWidths.isEmpty()) {
            return false;
        }
        if (increasingWidths.get(0) <= 0) {
            return false;
        }
        for (int i = 1; i < increasingWidths.size(); i++) {
            if (increasingWidths.get(i - 1) > increasingWidths.get(i)) {
                return false;
            }
        }
        return true;
    }

    private static String toRodString(int width, char ch) {
        StringBuilder buf = new StringBuilder();
        IntStream.range(0, width).forEach(i -> buf.append(ch));
        return buf.toString();
    }

    public String toString(boolean numeric) {
        if (numeric) {
            return increasingWidths.stream().map(width -> Integer.toString(width)).collect(joining(","));
        } else {
            return increasingWidths.stream().map(width -> toRodString(width, '≣')).collect(joining("|"));
        }
    }

    public String toString() {
        return toString(false);
    }

    public int totalWidth() {
        return increasingWidths.stream().mapToInt(width -> width).sum();
    }

    public int cutCount() {
        return increasingWidths.size() - 1;
    }

    @Override
    public boolean equals(Object o) {
        if (o == null || !(o instanceof CutSchedule)) {
            return false;
        }
        return this.compareTo((CutSchedule) o) == 0;
    }

    @Override
    public int compareTo(CutSchedule o) {
        assert o != null;
        int widthDelta = this.totalWidth() - o.totalWidth();
        if (widthDelta != 0) {
            // if total width is smaller, the CutSchedule is "smaller"
            return widthDelta;
        }
        int cutCountDelta = this.cutCount() - o.cutCount();
        if (cutCountDelta != 0) {
            // if cut count is smaller, the CutSchedule is "smaller"
            return cutCountDelta;
        }
        for (int i = 0; i < cutCount(); i++) {
            int deltaCutWidth = this.increasingWidths.get(i) - o.increasingWidths.get(i);
            if (deltaCutWidth != 0) {
                // the first having a smaller cut at position i is "smaller"
                return deltaCutWidth;
            }
        }
        return 0;
    }
}

public class RodCuttingOptimization {

    private static void extendToFullWidthAndCollect(final SortedSet<CutSchedule> csSetForSmallerWidth, final int width, final int firstCutWidth, final Set<CutSchedule> res) {
        for (CutSchedule subCs : csSetForSmallerWidth) {
            assert subCs.verify();
            assert subCs.totalWidth() == width - firstCutWidth;
            CutSchedule cs = new CutSchedule();
            cs.increasingWidths.add(firstCutWidth);
            cs.increasingWidths.addAll(subCs.increasingWidths);
            res.add(cs);
        }
    }

    private static SortedSet<CutSchedule> generateAllCutsSchedulesForGivenNumCutsAndWidth(final int numCuts, final int width, final int minCutWidth) {
        assert numCuts >= 0;
        assert width > 0;
        assert minCutWidth > 0;
        SortedSet<CutSchedule> res = new TreeSet<>();
        if (numCuts == 0) {
            CutSchedule cs = new CutSchedule();
            cs.increasingWidths.add(width);
            res.add(cs);
        } else {
            // Make the first cut at increasingly larger positions. It must be the smallest cut made!
            IntStream.rangeClosed(minCutWidth, width / 2).forEach(firstCutWidth -> {
                SortedSet<CutSchedule> csSetForSmallerWidth =
                        Collections.unmodifiableSortedSet(
                                generateAllCutsSchedulesForGivenNumCutsAndWidth(
                                        numCuts - 1,
                                        width - firstCutWidth,
                                        firstCutWidth
                                ));
                extendToFullWidthAndCollect(csSetForSmallerWidth, width, firstCutWidth, res);
            });
        }
        return res;
    }

    private static void verifyAll(final Set<CutSchedule> csSet, int width, final Set<CutSchedule> mustNotContain) {
        csSet.stream().forEach(cs -> {
            assert cs.verify();
            assert cs.totalWidth() == width;
            assert !mustNotContain.contains(cs);
        });
    }

    private static SortedSet<CutSchedule> tryingAllCutsForWidth(final int width) {
        final int minNumCuts = 0;
        final int maxNumCuts = width - 1;
        SortedSet<CutSchedule> res = new TreeSet<>();
        IntStream.rangeClosed(minNumCuts, maxNumCuts).forEach(numCuts -> {
            Set<CutSchedule> csSetForWidth = generateAllCutsSchedulesForGivenNumCutsAndWidth(numCuts, width, 1);
            verifyAll(csSetForWidth, width, res);
            res.addAll(csSetForWidth);
        });
        return res;
    }

    private final static boolean withPrintout = false;

    @Test
    public void loopOverWidths() {
        final int minWidth = 1;
        final int maxWidth = 100;
        IntStream.rangeClosed(minWidth, maxWidth).forEach(width -> {
            SortedSet<CutSchedule> all = tryingAllCutsForWidth(width);
            System.out.println("Number of ways of cutting for width = " + width + ": " + all.size());
            if (withPrintout) {
                all.stream().forEach(cs -> System.out.println(cs.toString(false)));
            }
        });
    }

}

First Post!

venkats

venkats

Author of Programming Kotlin, Rediscovering JavaScript (and 6 other titles)

We can assume the given values are profit instead of revenue. The exponential time complexity also comes from the worst case scenario.

Where Next?

Popular Pragmatic Bookshelf topics Top

jimschubert
In Chapter 3, the source for index introduces Config on page 31, followed by more code including tests; Config isn’t introduced until pag...
New
New
iPaul
page 37 ANTLRInputStream input = new ANTLRInputStream(is); as of ANTLR 4 .8 should be: CharStream stream = CharStreams.fromStream(i...
New
sdmoralesma
Title: Web Development with Clojure, Third Edition - migrations/create not working: p159 When I execute the command: user=&gt; (create-...
New
simonpeter
When I try the command to create a pair of migration files I get an error. user=&gt; (create-migration "guestbook") Execution error (Ill...
New
lirux
Hi Jamis, I think there’s an issue with a test on chapter 6. I own the ebook, version P1.0 Feb. 2019. This test doesn’t pass for me: ...
New
jskubick
I found an issue in Chapter 7 regarding android:backgroundTint vs app:backgroundTint. How to replicate: load chapter-7 from zipfile i...
New
brunogirin
When installing Cards as an editable package, I get the following error: ERROR: File “setup.py” not found. Directory cannot be installe...
New
brunogirin
When trying to run tox in parallel as explained on page 151, I got the following error: tox: error: argument -p/–parallel: expected one...
New
creminology
Skimming ahead, much of the following is explained in Chapter 3, but new readers (like me!) will hit a roadblock in Chapter 2 with their ...
New

Other popular topics Top

AstonJ
What chair do you have while working… and why? Is there a ‘best’ type of chair or working position for developers?
New
DevotionGeo
I know that -t flag is used along with -i flag for getting an interactive shell. But I cannot digest what the man page for docker run com...
New
AstonJ
I’ve been hearing quite a lot of comments relating to the sound of a keyboard, with one of the most desirable of these called ‘thock’, he...
New
AstonJ
This looks like a stunning keycap set :orange_heart: A LEGENDARY KEYBOARD LIVES ON When you bought an Apple Macintosh computer in the e...
New
PragmaticBookshelf
Learn different ways of writing concurrent code in Elixir and increase your application's performance, without sacrificing scalability or...
New
PragmaticBookshelf
Create efficient, elegant software tests in pytest, Python's most powerful testing framework. Brian Okken @brianokken Edited by Kat...
New
DevotionGeo
I have always used antique keyboards like Cherry MX 1800 or Cherry MX 8100 and almost always have modified the switches in some way, like...
New
First poster: bot
zig/http.zig at 7cf2cbb33ef34c1d211135f56d30fe23b6cacd42 · ziglang/zig. General-purpose programming language and toolchain for maintaini...
New
PragmaticBookshelf
Develop, deploy, and debug BEAM applications using BEAMOps: a new paradigm that focuses on scalability, fault tolerance, and owning each ...
New
PragmaticBookshelf
Explore the power of Ash Framework by modeling and building the domain for a real-world web application. Rebecca Le @sevenseacat and ...
New

Latest in Functional Programming in Java, Second Edition

Functional Programming in Java, Second Edition Portal

Sub Categories: