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Our adaption of TS to the EPP brought up the necessity for more dynamics in the generation of tabu tenure values, for reasons we will show in detail later Thus, we calculate the tabu tenure using an adequate periodic function g : , with g(i), i , being the tabu tenure value to be used when TS has reached the i-th iteration As a further component of TS, the aspiration criterion is somewhat the dual of the concept of working with tabus, allowing, under certain circumstances, a transition of some kind of global improvement to be made even though it might be prohibited by a tabu In the most common interpretation of this idea, the aspiration criterion ignores a tabu on any transition that yields an improvement over the best solution obtained so far in a TS search The criteria for TS termination are usually kept simple.

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i = 1,2, ...

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TS terminates if for a given number of iterations there is no further improvement in the cost function This termination condition is sufficient in most cases, and we use it as is in the current development state of our TS 1252 Definition of the Neighborhood As already pointed out in the description of the basic TS framework, we must first give a definition of the neighborhood That is, for each instance of Problem 1 and each B , where denotes the set of all possible ensemble assignments, we must define a set N(B) representing the neighborhood of B in To simplify matters, we do not define N(B) directly, but rather introduce a set M(B) of admissible elementary moves m on B, with m(B) denoting the resulting ensemble assignment when applying m to B, and then set N(B) := {m(B) | m M(B)}.

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In our approach, an elementary move m M(B), for an ensemble assignment B , is specified as a quadrupel m = (v, u, z, s), with v V, u {0, , |Bv |}, z {0, , |Bv | + 1}, u z and s S Furthermore, in the case that u 0 we demand that s Bu, where Bu Bv is the ensemble of vertex v with index u (Here we assume for each v V that the ensembles of Bv carry indices from 1 to |Bv | Then, for i = 1, , |Bv |, Bi Bv is the ensemble of v with index i) Under these assumptions, an elementary move m = (v, u, z, s) M(B) is interpreted as the transfer of service s, which is an element of the source ensemble Bu Bv of m, to the target ensemble Bz Bv of m.

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The result that a two-stage process is as good as any one-stage process seems so obvious that it may be appropriate to point out that it is not always true There are examples of multiuser channels where the decomposition breaks down We also consider two simple situations where the theorem appears to be misleading A simple example is that of sending English text over an erasure channel We can look for the most ef cient binary representation of the text and send it over the channel But the errors will be very dif cult to decode If, however, we send the English text directly over the channel, we can lose up to about half the letters and yet be able to make sense out of the message.

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