Statistical mechanics of the multi-constraint continuous knapsack problem

Physics – Condensed Matter – Disordered Systems and Neural Networks

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Latex 13 pages using IOP style file, 5 figures

Scientific paper

10.1088/0305-4470/30/4/008

We apply the replica analysis established by Gardner to the multi-constraint continuous knapsack problem,which is one of the linear programming problems and a most fundamental problem in the field of operations research (OR). For a large problem size, we analyse the space of solution and its volume, and estimate the optimal number of items to go into the knapsack as a function of the number of constraints. We study the stability of the replica symmetric (RS) solution and find that the RS calculation cannot estimate the optimal number of items in knapsack correctly if many constraints are required.In order to obtain a consistent solution in the RS region,we try the zero entropy approximation for this continuous solution space and get a stable solution within the RS ansatz.On the other hand, in replica symmetry breaking (RSB) region, the one step RSB solution is found by Parisi's scheme. It turns out that this problem is closely related to the problem of optimal storage capacity and of generalization by maximum stability rule of a spherical perceptron.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Statistical mechanics of the multi-constraint continuous knapsack problem does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Statistical mechanics of the multi-constraint continuous knapsack problem, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Statistical mechanics of the multi-constraint continuous knapsack problem will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-183239

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.