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

jon
Some minor things in the paper edition that says “3 2020” on the title page verso, not mentioned in the book’s errata online: p. 186 But...
New
ianwillie
Hello Brian, I have some problems with running the code in your book. I like the style of the book very much and I have learnt a lot as...
New
jesse050717
Title: Web Development with Clojure, Third Edition, pg 116 Hi - I just started chapter 5 and I am stuck on page 116 while trying to star...
New
mikecargal
Title: Hands-On Rust (Chapter 11: prefab) Just played a couple of amulet-less games. With a bit of debugging, I believe that your can_p...
New
fynn
This is as much a suggestion as a question, as a note for others. Locally the SGP30 wasn’t available, so I ordered a SGP40. On page 53, ...
New
jskubick
I’m under the impression that when the reader gets to page 136 (“View Data with the Database Inspector”), the code SHOULD be able to buil...
New
adamwoolhether
Is there any place where we can discuss the solutions to some of the exercises? I can figure most of them out, but am having trouble with...
New
mert
AWDWR 7, page 152, page 153: Hello everyone, I’m a little bit lost on the hotwire part. I didn’t fully understand it. On page 152 @rub...
New
gorkaio
root_layout: {PentoWeb.LayoutView, :root}, This results in the following following error: no “root” html template defined for PentoWeb...
New
SlowburnAZ
Getting an error when installing the dependencies at the start of this chapter: could not compile dependency :exla, "mix compile" failed...
New

Other popular topics Top

PragmaticBookshelf
Andy and Dave wrote this influential, classic book to help their clients create better software and rediscover the joy of coding. Almost ...
New
AstonJ
I ended up cancelling my Moonlander order as I think it’s just going to be a bit too bulky for me. I think the Planck and the Preonic (o...
New
AstonJ
Do the test and post your score :nerd_face: :keyboard: If possible, please add info such as the keyboard you’re using, the layout (Qw...
New
PragmaticBookshelf
Learn different ways of writing concurrent code in Elixir and increase your application's performance, without sacrificing scalability or...
New
PragmaticBookshelf
Build highly interactive applications without ever leaving Elixir, the way the experts do. Let LiveView take care of performance, scalabi...
New
Margaret
Hello everyone! This thread is to tell you about what authors from The Pragmatic Bookshelf are writing on Medium.
1147 29994 760
New
PragmaticBookshelf
Build efficient applications that exploit the unique benefits of a pure functional language, learning from an engineer who uses Haskell t...
New
New
PragmaticBookshelf
Author Spotlight: Peter Ullrich @PJUllrich Data is at the core of every business, but it is useless if nobody can access and analyze ...
New
New

Latest in Functional Programming in Java, Second Edition

Functional Programming in Java, Second Edition Portal

Sub Categories: