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This book covers local search for combinatorial optimization and its extension to mixed-variable optimization. Although not however understood from the theoretical perspective, local search is the paradigm of choice for tackling big-scale precise-life optimization points. At current’s end-customers demand interactivity with selection assist strategies. For optimization software, this suggests buying good-high high quality choices shortly. Fast iterative enchancment methods, like local search, are suited to satisfying such needs. Proper right here the authors current local search in a model new light, notably presenting a model new kind of mathematical programming solver, particularly LocalSolver, based on neighborhood search.
First, an iconoclast methodology is launched to design and engineer local search algorithms. The authors’ concern referring to industrializing local search approaches is of particular curiosity for practitioners. This technique is utilized to unravel two industrial points with high monetary stakes. Software program program based on local search induces further costs in enchancment and maintenance as in contrast with the direct use of mixed-integer linear programming solvers. The authors then switch on to present the LocalSolver enterprise whose goal is to provide the power of local search by means of a model-and-run solver for large-scale zero-1 nonlinear programming. They conclude by presenting their ongoing and future work on LocalSolver in the direction of a full mathematical programming solver based on local search.
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