The Optimization Problems in WDM Optical Networks
An in-depth analytical study on various optimization problems in wavelength-routed optical networks
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The static and semi-dynamic routing problems in theWavelength Division Multiplexing (WDM) networks aregenerally very complicated. Finding the exact optimafor most of these optimization problems is usuallyimpossible with today s computation facility even forthe medium size networks. Therefore, finding asub-optimal solution within a reasonable computationtime is the only choice, while knowing the proximityof the sub-optimal solution to the exact-optimumwould be an additional advantage.Different from most of the existing heuristicapproaches, this book provides strict formulationsand mathematical ...
The static and semi-dynamic routing problems in the
Wavelength Division Multiplexing (WDM) networks are
generally very complicated. Finding the exact optima
for most of these optimization problems is usually
impossible with today s computation facility even for
the medium size networks. Therefore, finding a
sub-optimal solution within a reasonable computation
time is the only choice, while knowing the proximity
of the sub-optimal solution to the exact-optimum
would be an additional advantage.
Different from most of the existing heuristic
approaches, this book provides strict formulations
and mathematical solutions with polynomial
complexities for various optimization problems,
including Min-Cost Problem, Max-RWA Problem, Traffic
Grooming Routing Problem, and Semi-Dynamic
Optimization Problem. The results are compared with
other state-of-the-art solutions, such as
LP-relaxation and branch-and-bound methods.
The solution framework provided in this book has been
proven to be very computationally efficient, while
generating results with good optimality, at the same
time providing tight theoretical bounds. The
computation time can be further reduced by reusing
the optimized results.
Wavelength Division Multiplexing (WDM) networks are
generally very complicated. Finding the exact optima
for most of these optimization problems is usually
impossible with today s computation facility even for
the medium size networks. Therefore, finding a
sub-optimal solution within a reasonable computation
time is the only choice, while knowing the proximity
of the sub-optimal solution to the exact-optimum
would be an additional advantage.
Different from most of the existing heuristic
approaches, this book provides strict formulations
and mathematical solutions with polynomial
complexities for various optimization problems,
including Min-Cost Problem, Max-RWA Problem, Traffic
Grooming Routing Problem, and Semi-Dynamic
Optimization Problem. The results are compared with
other state-of-the-art solutions, such as
LP-relaxation and branch-and-bound methods.
The solution framework provided in this book has been
proven to be very computationally efficient, while
generating results with good optimality, at the same
time providing tight theoretical bounds. The
computation time can be further reduced by reusing
the optimized results.
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