# Scheduling priority tasks in limited time and minimizing loss

Last Updated : 14 Mar, 2023

Given n tasks with arrival time, priority and number of time units they need. We need to schedule these tasks on a single resource. The objective is to arrange tasks such that maximum priority tasks are taken. Objective is to minimize sum of product of priority and left time of tasks that are not scheduled due to limited time. This criteria simply means that the scheduling should cause minimum possible loss. Examples:

```Input : Total time = 3
Task1: arrival = 1, units = 2, priority = 300
Task2: arrival = 2, units = 2, priority = 100
Output : 100
Explanation : Two tasks are given and time to finish
them is 3 units. First task arrives at time 1 and it
needs 2 units. Since no other task is running at that
time, we take it. 1 unit of task 1 is over. Now task 2
(300 > 100) thus 1 more unit  of task 1 is employed.
Now 1 unit of time is left and we have 2 units of task
2 to be done. So simply 1 unit of task 2 is done and
the answer is ( units of task 2 left X priority of
task 2 ) = 1 X 100 = 100

Input : Total Time = 3
Task1: arrival = 1, units = 1, priority = 100
Task2: arrival = 2, units = 2, priority = 300
Output : 0```

We use a priority queue and schedule one unit of task at a time.

1. Initialize total loss as sum of each priority and units. The idea is to initialize result as maximum, then one by one subtract priorities of tasks that are scheduled.
2. Sort all tasks according to arrival time.
3. Process through each unit of time from 1 to total time. For current time, pick the highest priority task that is available. Schedule 1 unit of this task and subtract its priority from total loss.

Below is C++ implementation of above steps.

## CPP

 `// C++ code for task scheduling on basis ` `// of priority and arrival time ` `#include "bits/stdc++.h" ` `using` `namespace` `std; `   `// t is total time. n is number of tasks. ` `// arriv[] stores arrival times. units[] ` `// stores units of time required. prior[] ` `// stores priorities. ` `int` `minLoss(``int` `n, ``int` `t, ``int` `arriv[], ` `   ``int` `units[], ``int` `prior[]) ` `{ ` ` ``// Calculating maximum possible answer ` ` ``// that could be calculated. Later we ` ` ``// will subtract the tasks from it ` ` ``// accordingly. ` ` ``int` `ans = 0; ` ` ``for` `(``int` `i = 0; i < n; i++) ` `  ``ans += prior[i] * units[i]; `   ` ``// Pushing tasks in a vector so that they ` ` ``// could be sorted according with their ` ` ``// arrival time ` ` ``vector > v; ` ` ``for` `(``int` `i = 0; i < n; i++) ` `  ``v.push_back({ arriv[i], i }); `   ` ``// Sorting tasks in vector identified by ` ` ``// index and arrival time with respect ` ` ``// to their arrival time ` ` ``sort(v.begin(), v.end()); `   ` ``// Priority queue to hold tasks to be ` ` ``// scheduled. ` ` ``priority_queue > pq; `   ` ``// Consider one unit of time at a time. ` ` ``int` `ptr = 0; ``// index in sorted vector ` ` ``for` `(``int` `i = 1; i <= t; i++) { `   `  ``// Push all tasks that have arrived at ` `  ``// this time. Note that the tasks that ` `  ``// arrived earlier and could not be scheduled ` `  ``// are already in pq. ` `  ``while` `(ptr < n and v[ptr].x == i) { ` `   ``pq.push({ prior[v[ptr].y], units[v[ptr].y] }); ` `   ``ptr++; ` `  ``} `   `  ``// Remove top priority task to be scheduled ` `  ``// at time i. ` `  ``if` `(!pq.empty()) { ` `   ``auto` `tmp = pq.top(); ` `   ``pq.pop(); `   `   ``// Removing 1 unit of task ` `   ``// from answer as we could ` `   ``// schedule it. ` `   ``ans -= tmp.x; ` `   ``tmp.y--; ` `   ``if` `(tmp.y) ` `    ``pq.push(tmp); ` `  ``} ` ` ``} `   ` ``return` `ans; ` `} `   `// driver code ` `int` `main() ` `{ ` ` ``int` `n = 2, t = 3; ` ` ``int` `arriv[] = { 1, 2 }; ` ` ``int` `units[] = { 2, 2 }; ` ` ``int` `prior[] = { 100, 300 }; `   ` ``printf``(``"%d\n"``, minLoss(n, t, arriv, units, prior)); ` ` ``return` `0; ` `} `

## Java

 `// Java code for task scheduling on basis` `// of priority and arrival time` `import` `java.util.*;`   `// Pair class definition` `class` `Pair {`   `  ``// Data members` `  ``private` `X key;` `  ``private` `Y value;`   `  ``// Constructor` `  ``public` `Pair(X x, Y y)` `  ``{` `    ``this``.key = x;` `    ``this``.value = y;` `  ``}`   `  ``// Getters` `  ``public` `X getKey() { ``return` `key; }`   `  ``public` `Y getValue() { ``return` `value; }`   `  ``// Setters` `  ``public` `void` `setKey(X x) { key = x; }`   `  ``public` `void` `setValue(Y y) { value = y; }` `}`   `class` `GFG {`   `  ``// t is total time. n is number of tasks.` `  ``// arriv[] stores arrival times. units[]` `  ``// stores units of time required. prior[]` `  ``// stores priorities.` `  ``static` `int` `minLoss(``int` `n, ``int` `t, ``int` `arriv[],` `                     ``int` `units[], ``int` `prior[])` `  ``{` `    ``// Calculating maximum possible answer` `    ``// that could be calculated. Later we` `    ``// will subtract the tasks from it` `    ``// accordingly.` `    ``int` `ans = ``0``;` `    ``for` `(``int` `i = ``0``; i < n; i++)` `      ``ans += prior[i] * units[i];`   `    ``// Pushing tasks in a ArrayList so that they` `    ``// could be sorted according with their` `    ``// arrival time` `    ``ArrayList > v` `      ``= ``new` `ArrayList >();` `    ``for` `(``int` `i = ``0``; i < n; i++)` `      ``v.add(``new` `Pair(arriv[i], i));`   `    ``// Sorting tasks in ArrayList identified by` `    ``// index and arrival time with respect` `    ``// to their arrival time` `    ``Collections.sort(` `      ``v, ``new` `Comparator >() {` `        ``public` `int` `compare(` `          ``Pair p1,` `          ``Pair p2)` `        ``{` `          ``return` `p1.getKey() - p2.getKey();` `        ``}` `      ``});`   `    ``// Priority queue to hold tasks to be` `    ``// scheduled.` `    ``PriorityQueue > pq` `      ``= ``new` `PriorityQueue >(` `      ``new` `Comparator >() {` `        ``public` `int` `compare(` `          ``Pair p1,` `          ``Pair p2)` `        ``{` `          ``if` `(p1.getKey() != p2.getKey())` `            ``return` `p2.getKey()` `            ``- p1.getKey();`   `          ``return` `p1.getValue()` `            ``- p2.getValue();` `        ``}` `      ``});`   `    ``// Consider one unit of time at a time.` `    ``int` `ptr = ``0``; ``// index in sorted ArrayList` `    ``for` `(``int` `i = ``1``; i <= t; i++) {`   `      ``// Push all tasks that have arrived at` `      ``// this time. Note that the tasks that` `      ``// arrived earlier and could not be scheduled` `      ``// are already in pq.` `      ``while` `(ptr < n && v.get(ptr).getKey() == i) {` `        ``pq.add(``new` `Pair(` `          ``prior[v.get(ptr).getValue()],` `          ``units[v.get(ptr).getValue()]));` `        ``ptr++;` `      ``}`   `      ``// Remove top priority task to be` `      ``// scheduled at time i.` `      ``if` `(!pq.isEmpty()) {` `        ``Pair tmp = pq.peek();` `        ``pq.poll();`   `        ``// Removing 1 unit of task` `        ``// from answer as we could` `        ``// schedule it.` `        ``ans -= tmp.getKey();` `        ``tmp.setValue(tmp.getValue() - ``1``);` `        ``if` `(tmp.getValue() > ``0``)` `          ``pq.add(tmp);` `      ``}` `    ``}`   `    ``return` `ans;` `  ``}`   `  ``// driver code` `  ``public` `static` `void` `main(String[] args)` `  ``{` `    ``int` `n = ``2``, t = ``3``;` `    ``int` `arriv[] = { ``1``, ``2` `};` `    ``int` `units[] = { ``2``, ``2` `};` `    ``int` `prior[] = { ``100``, ``300` `};`   `    ``System.out.println(` `      ``minLoss(n, t, arriv, units, prior));` `  ``}` `}`

## Python3

 `# Python3 code for task scheduling on basis` `# of priority and arrival time` `import` `heapq`   `# t is total time. n is number of tasks.` `# arriv[] stores arrival times. units[]` `# stores units of time required. prior[]` `# stores priorities.` `def` `minLoss(n, t, arriv, units, prior):` `    ``# Calculating maximum possible answer` `    ``# that could be calculated. Later we` `    ``# will subtract the tasks from it` `    ``# accordingly.` `    ``ans ``=` `0` `    ``for` `i ``in` `range``(n):` `        ``ans ``+``=` `prior[i] ``*` `units[i]` `    `  `    ``# Pushing tasks in a list so that they ` `    ``# could be sorted according with their ` `    ``# arrival time ` `    ``v ``=` `[] ` `    ``for` `i ``in` `range``(n): ` `        ``v.append((arriv[i], i)) ` `    `  `    ``# Sorting tasks in list identified by ` `    ``# index and arrival time with respect ` `    ``# to their arrival time ` `    ``v.sort() ` `    `  `    ``# Priority queue to hold tasks to be ` `    ``# scheduled. ` `    ``pq ``=` `[] ` `    `  `    ``# Consider one unit of time at a time. ` `    ``ptr ``=` `0` `# index in sorted list ` `    ``for` `i ``in` `range``(``1``, t``+``1``): ` `    `  `        ``# Push all tasks that have arrived at ` `        ``# this time. Note that the tasks that ` `        ``# arrived earlier and could not be scheduled ` `        ``# are already in pq. ` `        ``while` `ptr < n ``and` `v[ptr][``0``] ``=``=` `i: ` `            ``pq.append((``-``prior[v[ptr][``1``]], units[v[ptr][``1``]])) ` `            ``ptr ``+``=` `1` `        `  `        ``pq.sort()` `        `  `        ``# Remove top priority task to be ` `        ``# scheduled at time i. ` `        ``if` `pq: ` `            ``tmp ``=` `heapq.heappop(pq) ` `    `  `            ``# Removing 1 unit of task ` `            ``# from answer as we could ` `            ``# schedule it. ` `            ``ans ``+``=` `tmp[``0``] ` `            ``tmp ``=` `(tmp[``0``], tmp[``1``]``-``1``) ` `            ``if` `tmp[``1``]: ` `                ``heapq.heappush(pq, tmp) ` `    `  `    ``return` `ans `   `# driver code` `n ``=` `2` `t ``=` `3` `arriv ``=` `[``1``, ``2``]` `units ``=` `[``2``, ``2``]` `prior ``=` `[``100``, ``300``]`   `print``(minLoss(n, t, arriv, units, prior))`   `# This code is contributed by phasing17.`

## C#

 `// C# code for task scheduling on basis` `// of priority and arrival time` `using` `System;` `using` `System.Collections.Generic;`   `class` `TComparer : IComparer > {` `  ``public` `int` `Compare(Tuple<``int``, ``int``> p1,` `                     ``Tuple<``int``, ``int``> p2)` `  ``{` `    ``if` `(p1.Item1 != p2.Item1)` `      ``return` `p2.Item1 - p1.Item1;`   `    ``return` `p1.Item2 - p2.Item2;` `  ``}` `}`   `class` `GFG {`   `  ``// t is total time. n is number of tasks.` `  ``// arriv[] stores arrival times. units[]` `  ``// stores units of time required. prior[]` `  ``// stores priorities.` `  ``static` `int` `MinLoss(``int` `n, ``int` `t, ``int``[] arriv,` `                     ``int``[] units, ``int``[] prior)` `  ``{` `    ``// Calculating maximum possible answer` `    ``// that could be calculated. Later we` `    ``// will subtract the tasks from it` `    ``// accordingly.` `    ``int` `ans = 0;` `    ``for` `(``int` `i = 0; i < n; i++)` `      ``ans += prior[i] * units[i];`   `    ``// Pushing tasks in a List so that they` `    ``// could be sorted according with their` `    ``// arrival time` `    ``List > v` `      ``= ``new` `List >();` `    ``for` `(``int` `i = 0; i < n; i++)` `      ``v.Add(``new` `Tuple<``int``, ``int``>(arriv[i], i));`   `    ``// Sorting tasks in List identified by` `    ``// index and arrival time with respect` `    ``// to their arrival time` `    ``v.Sort((a, b) => a.Item1.CompareTo(b.Item1));`   `    ``// Sorted list to hold tasks to be` `    ``// scheduled.` `    ``SortedList, ``bool``> sl` `      ``= ``new` `SortedList, ``bool``>(` `      ``new` `TComparer >());`   `    ``// Consider one unit of time at a time.` `    ``int` `ptr = 0; ``// index in sorted List` `    ``for` `(``int` `i = 1; i <= t; i++) {`   `      ``// Push all tasks that have arrived at` `      ``// this time. Note that the tasks that` `      ``// arrived earlier and could not be scheduled` `      ``// are already in sl.` `      ``while` `(ptr < n && v[ptr].Item1 == i) {` `        ``sl.Add(``new` `Tuple<``int``, ``int``>(` `          ``prior[v[ptr].Item2],` `          ``units[v[ptr].Item2]),` `               ``true``);` `        ``ptr++;` `      ``}`   `      ``// Remove top priority task to be` `      ``// scheduled at time i.` `      ``if` `(sl.Count > 0) {` `        ``Tuple<``int``, ``int``> tmp = sl.Keys[0];` `        ``sl.RemoveAt(0);`   `        ``// Removing 1 unit of task` `        ``// from answer as we could` `        ``// schedule it.` `        ``ans -= tmp.Item1;` `        ``tmp = Tuple.Create(tmp.Item1,` `                           ``tmp.Item2 - 1);` `        ``if` `(tmp.Item2 > 0)` `          ``sl.Add(tmp, ``true``);` `      ``}` `    ``}`   `    ``return` `ans;` `  ``}`   `  ``// driver code` `  ``public` `static` `void` `Main(``string``[] args)` `  ``{` `    ``int` `n = 2, t = 3;` `    ``int``[] arriv = { 1, 2 };` `    ``int``[] units = { 2, 2 };` `    ``int``[] prior = { 100, 300 };`   `    ``Console.WriteLine(` `      ``MinLoss(n, t, arriv, units, prior));` `  ``}` `}`   `// This code is contributed by phasing17`

## Javascript

 `function` `MinLoss(n, t, arriv, units, prior) {` `  ``// Calculating maximum possible answer` `  ``// that could be calculated. Later we` `  ``// will subtract the tasks from it` `  ``// accordingly.` `    ``let ans = 0;` `    ``for` `(let i = 0; i < n; i++)` `      ``ans += prior[i] * units[i];`   `  ``// Pushing tasks in an array so that they` `  ``// could be sorted according with their` `  ``// arrival time` `    ``let v = [];` `    ``for` `(let i = 0; i < n; i++)` `      ``v.push([arriv[i], i]);`   `  ``// Sorting tasks in array identified by` `  ``// index and arrival time with respect` `  ``// to their arrival time` `    ``v.sort((a, b) => a[0] - b[0]);`   `  ``// Sorted list to hold tasks to be` `  ``// scheduled.` `    ``let sl = [];` `    ``let compare = (a, b) => b[0] - a[0] || a[1] - b[1]`   `  ``// Consider one unit of time at a time.` `    ``let ptr = 0; ``// index in sorted array` `    ``for` `(let i = 1; i <= t; i++) {`   `  ``// Push all tasks that have arrived at` `  ``// this time. Note that the tasks that` `  ``// arrived earlier and could not be scheduled` `  ``// are already in sl.` `      ``while` `(ptr < n && v[ptr][0] == i) {` `        ``sl.push([prior[v[ptr][1]], units[v[ptr][1]]]);` `        ``ptr++;` `      ``}`   `  ``// Remove top priority task to be` `  ``// scheduled at time i.` `      ``if` `(sl.length > 0) {` `        ``sl.sort(compare);` `        ``let tmp = sl.shift();`   `  ``// Removing 1 unit of task` `  ``// from answer as we could` `  ``// schedule it.` `        ``ans -= tmp[0];` `        ``tmp[1] -= 1;` `        ``if` `(tmp[1] > 0)` `          ``sl.push(tmp);` `      ``}` `    ``}`   `    ``return` `ans;` `  ``}`   `// driver code` `  ``let n = 2, t = 3;` `  ``let arriv = [ 1, 2 ];` `  ``let units = [ 2, 2 ];` `  ``let prior = [ 100, 300 ];`   `  ``console.log(MinLoss(n, t, arriv, units, prior));`

Output:

`100`

Time Complexity: O(nlogn), used for sorting the array
Auxiliary Space: O(n), as extra space of size n, is used to make a vector of pairs.

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