CSES Solutions - Factory Machines
Last Updated :
23 Jul, 2025
A factory has N machines which can be used to make products. Your goal is to make a total of T products.
For each machine, you know the number of seconds it needs to make a single product, given as array K[]. The machines can work simultaneously, and you can freely decide their schedule.
What is the shortest time needed to make T products?
Examples:
Input: N = 3, T = 7, K[] = {3, 2, 5}
Output: 8
Explanation:
- Machine 1 will make 2 products. Total time taken = 3 * 2 = 6 seconds.
- Machine 2 will make 4 products. Total time taken = 2 * 4 = 8 seconds.
- Machine 3 will make 1 product. Total time taken = 5 * 1 = 5 seconds.
Shortest time to make 7 products = 8 seconds.
Input: N = 2, T = 5, K[] = {1, 2}
Output: 4
Explanation:
- Machine 1 will make 3 products. Total time taken = 1 * 3 = 3 seconds.
- Machine 2 will make 2 products. Total time taken = 2 * 2 = 4 seconds
Shortest time to make 5 products = 4 seconds.
Approach: To solve the problem, follow the below idea:
The problem can be solved using Binary Search on Answer. We can binary search for the time needed to make the T products. If we observe carefully, the time to make T products will be at least 1 second and the maximum time to make T products will be when we have only 1 machine and it takes maximum amount of time to make one product. So, we can initialize low = 1 and high = T * min value in K[]. Now, we can find mid and find the total number of products we can making using all machines. If the total number of products is less than T, then it means we need more time so we will shift lo = mid + 1. Otherwise, we shift high = mid - 1 and update the answer. We keep on searching till low <= high and after all the iterations, we can return the final answer.
Step-by-step algorithm:
- Maintain a function check(mid, N, T, K) to check whether it is possible to make T products in time <= mid.
- Also maintain a variable ans to store the minimum time to make T products.
- Declare the range in which our answer can lie, that is low = 1, high = T * min value in K[].
- Iterate till low <= high,
- Find the mid in range [low, high] and check if we can make T products in time <= mid.
- If we can make T products in time <= mid, then update the answer and reduce search space by moving high to mid - 1.
- Otherwise, move low = mid + 1.
- After all the iterations, return ans as the final answer.
Below is the implementation of the algorithm:
C++
#include <bits/stdc++.h>
#define ll long long int
using namespace std;
// Make the check function to check if we can make T
// products in time <= mid
bool check(ll mid, ll N, ll T, ll* K)
{
// Variable to count the number of products made
ll sum = 0;
for (int i = 0; i < N; i++) {
sum += (mid / K[i]);
if (sum >= T)
return true;
}
return false;
}
// Function to find the minimum time to make T products
ll solve(ll N, ll T, ll* K)
{
// Define the range in which our answer can lie
ll low = 1, high = (*min_element(K, K + N)) * T ;
ll ans;
// Binary Search for the minimum time to make T products
while (low <= high) {
ll mid = (low + high) / 2;
// Check if we can make T products in time <= mid
if (check(mid, N, T, K)) {
// Update the answer and reduce search space by
// moving high to mid - 1
ans = mid;
high = mid - 1;
}
else {
// Reduce the search space by moving low to mid
// + 1
low = mid + 1;
}
}
return ans;
}
int main()
{
// Sample Input
ll N = 3, T = 7;
ll K[] = { 3, 2, 5 };
cout << solve(N, T, K);
}
Java
import java.util.Arrays;
public class Main {
// Function to check if we can make T products in time <= mid
static boolean check(long mid, long N, long T, long[] K) {
// Variable to count the number of products made
long sum = 0;
for (int i = 0; i < N; i++) {
sum += (mid / K[i]);
if (sum >= T)
return true;
}
return false;
}
// Function to find the minimum time to make T products
static long solve(long N, long T, long[] K) {
// Define the range in which our answer can lie
long low = 1, high = Arrays.stream(K).min().getAsLong() * T; // Updated high value
long ans = 0;
// Binary Search for the minimum time to make T products
while (low <= high) {
long mid = (low + high) / 2;
// Check if we can make T products in time <= mid
if (check(mid, N, T, K)) {
// Update the answer and reduce search space by
// moving high to mid - 1
ans = mid;
high = mid - 1;
} else {
// Reduce the search space by moving low to mid + 1
low = mid + 1;
}
}
return ans;
}
public static void main(String[] args) {
// Sample Input
long N = 3, T = 7;
long[] K = { 3, 2, 5 };
System.out.println(solve(N, T, K));
}
}
// This code is contributed by shivamgupta0987654321
Python
def check(mid, N, T, K):
# Variable to count the number of products made
sum_val = 0
for i in range(N):
sum_val += (mid // K[i])
if sum_val >= T:
return True
return False
def solve(N, T, K):
# Define the range in which our answer can lie
low, high = 1, min(K) * T
ans = 0
# Binary Search for the minimum time to make T products
while low <= high:
mid = (low + high) // 2
# Check if we can make T products in time <= mid
if check(mid, N, T, K):
# Update the answer and reduce search space by moving high to mid - 1
ans = mid
high = mid - 1
else:
# Reduce the search space by moving low to mid + 1
low = mid + 1
return ans
if __name__ == "__main__":
# Sample Input
N = 3
T = 7
K = [3, 2, 5]
# Output the result
print(solve(N, T, K))
C#
using System;
using System.Linq;
class Program
{
// Function to check if we can make T products in time <= mid
static bool Check(long mid, long N, long T, long[] K)
{
// Variable to count the number of products made
long sum = 0;
for (int i = 0; i < N; i++)
{
sum += (mid / K[i]);
if (sum >= T)
return true;
}
return false;
}
// Function to find the minimum time to make T products
static long Solve(long N, long T, long[] K)
{
// Define the range in which our answer can lie
long low = 1, high = K.Min() * T;
long ans = 0;
// Binary Search for the minimum time to make T products
while (low <= high)
{
long mid = (low + high) / 2;
// Check if we can make T products in time <= mid
if (Check(mid, N, T, K))
{
// Update the answer and reduce search space by
// moving high to mid - 1
ans = mid;
high = mid - 1;
}
else
{
// Reduce the search space by moving low to mid + 1
low = mid + 1;
}
}
return ans;
}
static void Main(string[] args)
{
// Sample Input
long N = 3, T = 7;
long[] K = { 3, 2, 5 };
Console.WriteLine(Solve(N, T, K));
}
}
JavaScript
// Make the check function to check if we can make T
// products in time <= mid
function check(mid, N, T, K) {
// Variable to count the number of products made
let sum = 0;
for (let i = 0; i < N; i++) {
sum += Math.floor(mid / K[i]);
if (sum >= T)
return true;
}
return false;
}
// Function to find the minimum time to make T products
function solve(N, T, K) {
// Define the range in which our answer can lie
let low = 1, high = Math.min(...K) * T;
let ans;
// Binary Search for the minimum time to make T products
while (low <= high) {
let mid = Math.floor((low + high) / 2);
// Check if we can make T products in time <= mid
if (check(mid, N, T, K)) {
// Update the answer and reduce search space by
// moving high to mid - 1
ans = mid;
high = mid - 1;
} else {
// Reduce the search space by moving low to mid
// + 1
low = mid + 1;
}
}
return ans;
}
// Sample Input
let N = 3, T = 7;
let K = [3, 2, 5];
console.log(solve(N, T, K));
// This code is contributed by Ayush Mishra
Time Complexity: O(N * log(T * max(K[]))), N is the number of machines, T is the number of products and K[] is the array of time which each machine takes to make 1 product.
Auxiliary Space: O(1)
Similar Reads
Non-linear Components In electrical circuits, Non-linear Components are electronic devices that need an external power source to operate actively. Non-Linear Components are those that are changed with respect to the voltage and current. Elements that do not follow ohm's law are called Non-linear Components. Non-linear Co
11 min read
Binary Search Algorithm - Iterative and Recursive Implementation Binary Search Algorithm is a searching algorithm used in a sorted array by repeatedly dividing the search interval in half. The idea of binary search is to use the information that the array is sorted and reduce the time complexity to O(log N). Binary Search AlgorithmConditions to apply Binary Searc
15 min read
Spring Boot Tutorial Spring Boot is a Java framework that makes it easier to create and run Java applications. It simplifies the configuration and setup process, allowing developers to focus more on writing code for their applications. This Spring Boot Tutorial is a comprehensive guide that covers both basic and advance
10 min read
Dynamic Programming or DP Dynamic Programming is an algorithmic technique with the following properties.It is mainly an optimization over plain recursion. Wherever we see a recursive solution that has repeated calls for the same inputs, we can optimize it using Dynamic Programming. The idea is to simply store the results of
3 min read
Class Diagram | Unified Modeling Language (UML) A UML class diagram is a visual tool that represents the structure of a system by showing its classes, attributes, methods, and the relationships between them. It helps everyone involved in a projectâlike developers and designersâunderstand how the system is organized and how its components interact
12 min read
Python Variables In Python, variables are used to store data that can be referenced and manipulated during program execution. A variable is essentially a name that is assigned to a value. Unlike many other programming languages, Python variables do not require explicit declaration of type. The type of the variable i
6 min read
Spring Boot Interview Questions and Answers Spring Boot is a Java-based framework used to develop stand-alone, production-ready applications with minimal configuration. Introduced by Pivotal in 2014, it simplifies the development of Spring applications by offering embedded servers, auto-configuration, and fast startup. Many top companies, inc
15+ min read
Backpropagation in Neural Network Back Propagation is also known as "Backward Propagation of Errors" is a method used to train neural network . Its goal is to reduce the difference between the modelâs predicted output and the actual output by adjusting the weights and biases in the network.It works iteratively to adjust weights and
9 min read
Polymorphism in Java Polymorphism in Java is one of the core concepts in object-oriented programming (OOP) that allows objects to behave differently based on their specific class type. The word polymorphism means having many forms, and it comes from the Greek words poly (many) and morph (forms), this means one entity ca
7 min read
What is an Operating System? An Operating System is a System software that manages all the resources of the computing device. Acts as an interface between the software and different parts of the computer or the computer hardware. Manages the overall resources and operations of the computer. Controls and monitors the execution o
5 min read