Abstract:
Optimal utilization of resources in present-
day communication networks is a challenging task. Rout-
ing plays an important role in achieving optimal re-
source utilization. The open shortest path rst (OSPF)
routing protocol is widely used for routing packets from
a source node to a destination node. This protocol as-
signs weights (or costs) to the links of a network. These
weights are used to determine the shortest path be tween all sources to all destination nodes. Assignment
of these weights to the links is classi ed as an NP-hard
problem. This paper formulates the OSPF weight set-
ting problem as a multi-objective optimization prob-
lem, with maximum utilization, number of congested
links, and number of unused links as the optimization
objectives. Since the objectives are con
icting in na-
ture, an e cient approach is needed to balance the
trade-o between these objectives. Fuzzy logic has been
shown to e ciently solve multi-objective optimization
problems. A fuzzy cost function for the OSPF weight
setting problem is developed in this paper based on the
Uni ed And-OR (UAO) operator. Two iterative heuris-
tics, namely, simulated annealing (SA) and simulated
evolution (SimE) have been implemented to solve the
multi-objective OSPF weight setting problem using a
fuzzy cost function. Results are compared with that
found using other cost functions proposed in the literature [1]. Results suggest that, overall, the fuzzy cost
function performs better than existing cost functions,
with respect to both SA and SimE. Furthermore, SimE
shows superior performance compared to SA. In addi-
tion, a comparison of SimE with NSGA-II shows that,
overall, SimE demonstrates slightly better performance
in terms of quality of solutions.-
