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Its image on the objective space, Znd = {z : z = f (x), x ∈ Xnd } is called nondominated front. Definition 6 (Pareto set and front) The set Xpar = {x : x is nondominated in Xf } is called Pareto set. Its image on the objective space Zef f = {z : z = f (x), x ∈ Xpar } is called Efficient set or equivalently Pareto front. Definition 7 (Euclidean distance) The Euclidean distance between two vectors (of n 1 2 2 dimension n) z1 and z2 is defined as z1 − z2 = i=1 (zi − zi ) . After these ground-laying definitions, in the rest of this section we first briefly explain an exact method for solving multiobjective optimization problems, namely the lexicographic weighted Tchebycheff method which was introduced by Steuer and Choo [92].

The work in [95] presents an exploration algorithm for parameterized memory architectures. The inputs to the exploration algorithm are timing and energy constraints obtained from the application tasks and the memory architecture specifications. The goal is to identify the system time/energy trade-off, when each task data member is assigned a target memory component. Exact and heuristic algorithms are given for solving different instances of the problem. However, only one type of heuristic (based on a branch and bound algorithm) is used, and no comparison with other heuristics is given.

G. processors, memories, interconnect busses) are used to capture dynamic information which is essential for the computation of power and performance metrics. More recently, Ascia et al. [2] have also applied a genetic algorithm to solve the same problem. The work in [95] presents an exploration algorithm for parameterized memory architectures. The inputs to the exploration algorithm are timing and energy constraints obtained from the application tasks and the memory architecture specifications.

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