The basic principle using the branchand-
bound strategy to solve the traveling
salesperson optimization problem (TSP)
consists of two parts.
There is a way to split the solution space.
There is a way to predict a lower bound for a
class of solutions.
There is also a way to find an upper bound of
an optimal solution.
If the lower bound of a solution exceeds this
upper bound, this solution cannot be optimal.
Thus, we should terminate the branching
associated with this solution.
WSNs being energy constrained systems, one major problem is to employ the sensor nodes in such a manner so as to ensure maximum coverage and connectivity with minimal or optimal number of nodes and furthermore elongate network lifetime with maximum energy utilization.
The problem addressed has been tackled for 1-D linear array and further extended to 2-Dimensions as stated in the next slides.
Traveling Salesperson Problem
Our branch-and-strategy splits a branch and bound solution into two groups:
one group including a particular arc and the other excluding this arc.
1.Each splitting incurs a lower bound and we shall traverse the searching tree with the "lower" lower bound.
2.If a constant subtracted from any row
or any column of the cost matrix, an
optimal solution does not change.
