Optimization models based on a nonlinear systems description often
possess multiple local optima. The objective of global optimization (GO)
is to find the best possible solution of multiextremal problems. This
volume illustrates the applicability of GO modeling techniques and
solution strategies to real-world problems.
The contributed chapters cover a broad range of applications from
agroecosystem management, assembly line design, bioinformatics,
biophysics, black box systems optimization, cellular mobile network
design, chemical process optimization, chemical product design,
composite structure design, computational modeling of atomic and
molecular structures, controller design for induction motors, electrical
engineering design, feeding strategies in animal husbandry, the inverse
position problem in kinematics, laser design, learning in neural nets,
mechanical engineering design, numerical solution of equations,
radiotherapy planning, robot design, and satellite data analysis. The
solution strategies discussed encompass a range of practically viable
methods, including both theoretically rigorous and heuristic approaches.