Search

This work shows the infrastructure investment decision is essentially a 0-1, nonlinear, multiobjective knapsack problem. It argues that, without making substantial simplification on some of the practical considerations, a conventional mathematical optimization approach may not be suitable for solving the problem. Further, the use of explicit heuristics may sometimes be unwieldy dependent on the system parameters. An innovative approach based on the concept of genetic algorithms is proposed in the work to tackle the nonlinearity in the decision problem. Based on the experimental results, the proposed approach is capable of producing good quality results. The key success feature of the proposed approach resides in the unique and innovative modeling of system parameters by genetic coding in the algorithms. [ABSTRACT FROM AUTHOR]