For example we have array of meeting objects:

const data = [
{ name: "m1", hours: },
{ name: "m2", hours: },
{ name: "m3", hours: },
{ name: "m4", hours: },
{ name: "m5", hours: }
];

For a day, 8 hours, we want to take as any meetings as possible:

const res = optimizeMeetings(data, );

You should write function 'optimizeMeetings', get the results of selected meetings to attend.

This problem is the same as Knapack problem, we can construct a table:

hours / total 1 2 3 4 5 6 7 8
2  0  2  2  2  2  2  2
4  0  2  2  4  4  6  6  6
3  0  2  3  4  5  6  7 7
3  0  2  3  4  5  6  7  8
1  1  2  3  4  5  6  7 8

The max hours we can take is the last row & col value, which in the end should be 8.

Then we should trace back the table to find which items should be included.

Final Code:

/**@description
* When we have our result for Knapsack problem, we want to back trace to get the selected items.
*
* What we need to do is trace form last item of the memo, moving up
*/
const backTrace = (hours, totalHours, memo) => {
function helper(memo, row, col) {
let current = memo[row][col];
let selected = [];
while (current >= && row >= && col >= ) {
// If we reach the first row, then check whether we have the remaining?
// If yes then we need to add this row item into final result
if (row === && current !== ) {
selected.push(row);
break;
} let sameRowPrevCol = memo[row][col - ];
let prevRowSameCol = memo[row - ][col]; if (current !== sameRowPrevCol && prevRowSameCol !== current) {
// Item should be selected if the value with sibling values are differnet
selected.push(row);
// calcuate the remaining
col = current - hours[row] - ;
row = row - ;
} else if (prevRowSameCol === current && current !== sameRowPrevCol) {
// current is coming from previous row with the same column, reset row
row = row - ;
} else if (current === sameRowPrevCol && prevRowSameCol !== current) {
// current is coming from previous column with the same row, reset column
col = col - ;
}
// Update current with new row and new column
current = memo[row][col];
}
return selected;
} return helper(memo, hours.length - , totalHours.length - );
}; const getMaxHours = (hours, totalHours) => {
let memo = [...new Array(hours.length)].map(
x => new Array(totalHours.length)
);
function helper(hours, totalHours, memo) {
for (let row in hours) {
const value = hours[row];
for (let col in totalHours) {
// Fill in the first row
if (!memo[row - ]) {
memo[row][col] = value <= totalHours[col] ? value : ;
continue;
} // if the current value is larger than constrain, we use previous value
const prevRowSameCol = memo[row - ][col];
if (value > totalHours[col]) {
memo[row][col] = prevRowSameCol;
continue;
} // if the current value is equal to constrain, then Max{value, prevRowSameCol}
if (value === totalHours[col]) {
memo[row][col] = Math.max(value, prevRowSameCol);
} // if the current value is smaller than constrain
// Math {value + memo[row - 1][diff]: where diff is constrain-value, prevRowSameCol}
if (value < totalHours[col]) {
const diff = totalHours[col] - value - ;
memo[row][col] = Math.max(
prevRowSameCol,
value + memo[row - ][diff]
);
}
}
}
return memo;
}
memo = helper(hours, totalHours, memo);
const selectedIndex = backTrace(hours, totalHours, memo); return {
memo,
selectedIndex
};
}; function* genearteNumberAry(start, num) {
let i = start;
while (i <= num) {
yield i;
i++;
}
} /**
* Main
*/
/**
* @param meetings: [{name: string, hours: number}]
* @param haveHours: number
*
* @returns [meetings]
*/
function optimizeMeetings(meetings, haveHours) {
const hours = meetings.map(m => m.hours);
const haveHoursAry = Array.from(genearteNumberAry(, haveHours));
const { selectedIndex } = getMaxHours(hours, haveHoursAry);
return selectedIndex.map(i => meetings[i]);
} const data = [
{ name: "m1", hours: },
{ name: "m2", hours: },
{ name: "m3", hours: },
{ name: "m4", hours: },
{ name: "m5", hours: }
]; const res = optimizeMeetings(data, );
console.log(JSON.stringify(res)); // [{"name":"m4","hours":3},{"name":"m3","hours":3},{"name":"m1","hours":2}]

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