node.js - Resource Optimization: which one to use Knapsack, brute-force or any other approach? -

in resource allocation problem have n bucket sizes , m resources. resources should allocated buckets in such way there max utilization. need write algorithm in node js

here's problem: let's have 2 buckets of sizes 50 , 60 respectively. resource sizes 20, 25, 40. following more proper representation possible solutions:

solution 1:

| bucket size | resource(s) allocated | utilization |

|             50             |                       20, 25                   |    45/50 = 0.9    |
|             60             |                          40                      |  40/60 = 0.667  |
total utilization in case >1.5

solution 2:

| bucket size | resource(s) allocated | utilization |

|             50             |                          25                      |    25/50 = 0.5    |
|             60             |                       20, 40                   |    60/60 = 1.0    |
total utilization in case 1.5

inference:
-- knapsack approach return solution 2 because optimization based on higher bucket size.
-- brute-force approach return both solutions. 1 concern approach have is; given have use node js , single threaded, little skeptic performance when n (buckets) , m (resources) large.

will brute-force fine or there better way/algorithm can solve problem? also, concern i've cited above valid in sense?

knapsack problem (and knapsack problem) npc, means, can find solution brute-force or alghoritms have o-complexity same bruteforce, can better in average case...

it single threaded, little skeptic performance when n (buckets) , m (resources) large.

i not sure, if know how thing works. if not create child threads , handle them (which not easy), every standard language work in 1 thread, therefore in 1 processor. , if want more processors much, can create child threads in node.js. in complexity problems, not matter, if solution takes multiple-time more, if "multiple" constant. in case, suppose "multiple" means 4, if have quad-core.

there 2 solutions :

1)backtracking - advanced brute-force mechanism, can in same cases return solution faster.

2)dynamic programming - if have items relatively low-values, while classic brute-force not able find solution 200 items in expected time of universe itself, dynamic approach can give solution in (mili)seconds.