104 FRONTIERS OF EVOLUTIONARY COMPUTATION
format, permitting solutions to be derived by a common, rather than tailor-made, heuristic method.
|where Q is an||by||matrix of constants and x is an||of zero-one|
variables. QUIP is notable for its ability to represent a significant variety of important problems. The applicability of this representation has been reported in diverse settings such as social psychology (Harary, 1954), financial analysis (Laughunn, 1970), (McBride and Yormack, 1980), computer aided design (Krarup and Pruzan, 1978), traffic management (Gallo et al., 1980), (Witsgall, 1975), machine scheduling (Alidaee et al., 1994), cellular radio channel allocation (Chardaire and Sutler, 1994), and molecular conformation (Phillips Moreover, many combinatorial optimization problems and Rosen, 1994).
pertaining to graphs such as determining maximum cliques, maximum cuts, maximum vertex packing, minimum coverings, maximum independent sets, and maximum independent weighted sets are known to be capable of being
We take as our starting point the constrained problem
|where the matrix||D||and the additive constant||result directly from the ma|
trix multiplication indicated. Dropping the additive constant, the equivalent unconstrained version of our constrained problem becomes,