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A novel canonical duality theory (CDT) is presented for solving general bilevel mixed integer nonlinear optimization governed by linear and quadratic knapsack problems. It shows that the challenging knapsack problems can be solved analytically in term of their canonical dual solutions. The existence and uniqueness of these analytical solutions are proved. NP-hardness of the knapsack problems is discussed. A powerful CDT algorithm combined with an alternative iteration and a volume reduction method is proposed for solving the NP-hard bilevel knapsack problems. Application is illustrated by benchmark problems in optimal topology design. The performance and novelty of the proposed method are compared with the popular commercial codes. [ABSTRACT FROM AUTHOR]

A methodology for determining the optimal spatial distribution of a river pollutant detection network using a geographic information system and genetic algorithms (GAs) is developed. Two case studies are investigated to evaluate the performance of the developed methodology: (1) a hypothesized river system consisting of only 11 reaches; (2) the Logan and Albert Rivers in Southeast Queensland. Plausible results are obtained, encouraging the possibility of applying GAs in designing a river monitoring network. [ABSTRACT FROM AUTHOR]