I have a question in dynamic programming, If I have a set of sensors covering targets ( a target might be covered by mutiple sensors) how can I find the minimum cost subset of sensors knowing that each sensors has its own cost?
I thought a lot about this, but I cant reach the recursive forumla to write my program? greedy algorithm gives me wrong minimum cost subset sometimes, and my problem is that sensors overlap in covering targets, any help?
For Example:
I have set of sensors with cost/weight = {s1:1,s2:2.5,s3:2} and I have three targets = {t1,t2,t3}. sensors coverage as following:={s1:t1 t2,s2:t1 t2 t3,s3:t2 t3} I need to get minimum cost subset by dynamic programming, for the above example if I use greedy algorithm I would get s1,s3 but the right answer is s2 only
check section 3 it labels the
Dynamic programming algorithm for the MWCDC
https://docs.google.com/viewer?a=v&q=cache:5vPrmVg7jDMJ:www.cs.iit.edu/~wan/Journal/tcs10.pdf+&hl=en&gl=us&pid=bl&srcid=ADGEESglfvp6XtFIkqDZZ-E-Tun4AWPTZV_V7z32pTvJ05K6tdkCoefpsAxPxdK44jYDvPNLDEwYI8uK-PMlLGthsaV8-ow63utalgWPnyLrUUBKhoTTVuYwUiKSHlCXU-HXKHVeHvh4&sig=AHIEtbQGka8F39MaT8yAy4G9Kvv8TPsvJA