id: 02209665
dt: a
an: 02209665
au: Rego, César
ti: RAMP: a new metaheuristic framework for combinatorial optimization.
so: Rego, César (ed.) et al., Metaheuristic optimization via memory and
    evolution. Tabu search and scatter search. Boston, MA: Kluwer Academic
    Publishers (ISBN 1-4020-8134-0/hbk). Operations Research/Computer
    Science Interfaces Series 30, 441-460 (2005).
py: 2005
pu: Boston, MA: Kluwer Academic Publishers
la: EN
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ab: Summary: We propose a new metaheuristic framework embodied in two
    approaches, Relaxation Adaptive Memory Programming (RAMP) and its
    primal-dual extension (PD-RAMP). The RAMP method, at the first level,
    operates by combining fundamental principles of mathematical relaxation
    with those of adaptive memory programming, as expressed in tabu search.
    The extended PD-RAMP method, at the second level, integrates the RAMP
    approach with other more advanced strategies. We identity specific
    combinations of such strategies at both levels, based on Lagrangean and
    surrogate constraint relaxation on the dual side and on scatter search
    and path relinking on the primal side, in each instance joined with
    appropriate guidance from adaptive memory processes. The framework
    invites the use of alternative procedures for both its primal and dual
    components, including other forms of relaxations and evolutionary
    approaches such as genetic algorithms and other procedures based on
    metaphors of nature.
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