Abstract
The time-cost optimization (TCO) problem is a multiobjective optimization problem, which attempts to strike a balance between resource allocation costs and project schedule duration. In this paper, memetic algorithm (MA) which uses order crossover and a new mutation based on neighborhood search after each crossover and mutation operation, and an improved simulated annealing algorithm utilized for local search, is employed to model time-cost optimization problem. A prototype example using MA for TCO problem is simulated with Matlab7.0. The test results show that the MA based model can generate a more optimal cost under the same duration and achieve a better Pareto front than other models. Therefore, the MA can be regarded as a useful approach for solving construction project TCO problems.
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